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115 Commits

Author SHA1 Message Date
ItzCrazyKns
046f159528 feat(widgets): use new classifier, implement new widget executor, delete registry 2025-12-02 11:52:40 +05:30
ItzCrazyKns
6899b49ca0 Merge branch 'feat/improve-search-architecture' of https://github.com/ItzCrazyKns/Perplexica into feat/improve-search-architecture 2025-12-02 11:52:31 +05:30
ItzCrazyKns
dbc2137efb Revise writer prompt for warmer, conversational tone 2025-12-02 11:51:17 +05:30
ItzCrazyKns
1ea348ddb7 feat(classifier-prompt): update and add showCalculationWidget 2025-12-02 11:50:54 +05:30
ItzCrazyKns
b8a7fb936f feat(classifier): add showCalculationWidget 2025-12-02 11:50:26 +05:30
ItzCrazyKns
33c8f454a3 feat(weather-widget): do not round temperature 2025-12-02 11:49:37 +05:30
Kushagra Srivastava
3e90305c12 Merge pull request #939 from ItzCrazyKns/master
Merge master into feat/improve-search-architecture
2025-12-01 20:29:52 +05:30
ItzCrazyKns
41c879cd86 feat(llm): use zod inferences at return type 2025-12-01 18:34:36 +05:30
ItzCrazyKns
9b3833f933 feat(classifier): switch to a fixed approach 2025-12-01 18:33:54 +05:30
ItzCrazyKns
610d06be36 refac(llm): LLM option handling for per request overrides 2025-12-01 18:28:20 +05:30
ItzCrazyKns
7757bbd253 feat(ollama-llm): explicitly disable think for reasoning models 2025-11-29 12:57:29 +05:30
ItzCrazyKns
e2a371936b feat(stock-widget): use names and ticker 2025-11-29 12:46:01 +05:30
Kushagra Srivastava
5901a965f7 Merge pull request #934 from PSYEONE/no-ads
Added ability to remove the widgets in the front empty page of the search. Specifically the Weather and News widget.
2025-11-28 20:03:00 +05:30
ItzCrazyKns
6150784c27 feat(app): lint & beautify 2025-11-28 18:41:11 +05:30
Kushagra Srivastava
cb30e2438a Update src/components/EmptyChat.tsx
Co-authored-by: cubic-dev-ai[bot] <191113872+cubic-dev-ai[bot]@users.noreply.github.com>
2025-11-28 18:17:07 +05:30
Kushagra Srivastava
ead2a5b215 Update src/components/EmptyChat.tsx
Co-authored-by: cubic-dev-ai[bot] <191113872+cubic-dev-ai[bot]@users.noreply.github.com>
2025-11-28 18:17:01 +05:30
PSYEONE
1df4d886ff Revert "Added updated README for this fork"
This reverts commit 2574287fa8.
2025-11-28 12:24:15 +00:00
PSYEONE
2574287fa8 Added updated README for this fork 2025-11-28 12:08:19 +00:00
PSYEONE
3005b379cf Added functionality for hiding weather and news widgets 2025-11-28 11:59:53 +00:00
ItzCrazyKns
f83bd06e89 feat(ollama-llm): remove explicit think parameter setting 2025-11-27 11:10:04 +05:30
ItzCrazyKns
7544bbafaf feat(weather-widget): prevent [object Object] from being sent by stringifying 2025-11-27 11:09:37 +05:30
ItzCrazyKns
0a62c60da2 feat(widgets): add LLM context to prevent context overflow 2025-11-24 15:35:00 +05:30
ItzCrazyKns
956a768a86 feat(app): handle new architecture 2025-11-23 19:58:46 +05:30
ItzCrazyKns
e0ba476ca4 feat(optimization): enable quality 2025-11-23 19:49:54 +05:30
ItzCrazyKns
cba3f43b19 feat(search-agent): add search agent flow 2025-11-23 19:49:36 +05:30
ItzCrazyKns
ec06a2b9ff feat(researcher): use patching, streaming 2025-11-23 19:48:44 +05:30
ItzCrazyKns
1b4e883f57 feat(prompts): add writer prompt 2025-11-23 19:48:12 +05:30
ItzCrazyKns
f15802b688 feat(prompts): update research prompt 2025-11-23 19:48:05 +05:30
ItzCrazyKns
8dec689a45 feat(prompts): update classifier prompt 2025-11-23 19:47:28 +05:30
ItzCrazyKns
730ee0ff41 feat(intents): add private search 2025-11-23 19:47:18 +05:30
ItzCrazyKns
7c9258cfc9 feat(intents): update intent prompt 2025-11-23 19:47:11 +05:30
ItzCrazyKns
4e7143ce0c feat(app): add initial widgets 2025-11-23 19:46:42 +05:30
ItzCrazyKns
d5f62f2dca feat(chat): prevent auto-scroll unless message sent 2025-11-23 19:46:02 +05:30
ItzCrazyKns
b7b280637f feat(providers): update ollama context window, temp 2025-11-23 19:26:47 +05:30
ItzCrazyKns
e22a39fd73 feat(routes): update routes to handle new llm types 2025-11-23 19:24:17 +05:30
ItzCrazyKns
6da6acbcd0 feat(agents): update media agents 2025-11-23 19:23:42 +05:30
ItzCrazyKns
0ac8569a9e feat(agents): update suggestion generator 2025-11-23 19:23:18 +05:30
ItzCrazyKns
74bc08d189 Refactor types and imports for consistency 2025-11-23 19:22:27 +05:30
ItzCrazyKns
d7dd17c069 feat(app): fix type resolving issues 2025-11-23 19:22:11 +05:30
ItzCrazyKns
6d35d60b49 Remove unused output parsers and document utility 2025-11-23 19:21:16 +05:30
ItzCrazyKns
d6c364fdcb feat(models): remove old providers 2025-11-22 22:23:10 +05:30
ItzCrazyKns
8d04f636d0 Delete index.ts 2025-11-22 22:22:43 +05:30
ItzCrazyKns
9ac2da3607 feat(app): remove old search agent 2025-11-22 22:22:34 +05:30
ItzCrazyKns
55cf88822d feat(package): add modules 2025-11-21 23:58:04 +05:30
ItzCrazyKns
c4acc83fd5 feat(agents): add search agent 2025-11-21 23:57:50 +05:30
ItzCrazyKns
08feb18197 feat(search-agent): add researcher, research actions 2025-11-21 23:57:29 +05:30
ItzCrazyKns
0df0114e76 feat(prompts): add researcher prompt 2025-11-21 23:54:30 +05:30
ItzCrazyKns
4016b21bdf Update formatHistory.ts 2025-11-21 23:54:16 +05:30
ItzCrazyKns
f7a43b3cb9 feat(session): use blocks, use rfc6902 for stream with patching 2025-11-21 23:52:55 +05:30
ItzCrazyKns
70bcd8c6f1 feat(types): add artifact to block, add more blocks 2025-11-21 23:51:09 +05:30
ItzCrazyKns
2568088341 feat(db): add new migration files 2025-11-21 23:49:52 +05:30
ItzCrazyKns
a494d4c329 feat(app): fix migration errors 2025-11-21 23:49:27 +05:30
ItzCrazyKns
9b85c63a80 feat(db): migrate schema 2025-11-21 23:49:14 +05:30
ItzCrazyKns
1614cfa5e5 feat(app): add widgets 2025-11-20 14:55:50 +05:30
ItzCrazyKns
036b44611f feat(search): add classifier 2025-11-20 14:55:24 +05:30
ItzCrazyKns
8b515201f3 feat(app): add search types 2025-11-20 14:53:03 +05:30
ItzCrazyKns
cbcb03c7ac feat(llm): update return type to partial 2025-11-20 14:52:41 +05:30
ItzCrazyKns
afc68ca91f feat(ollamaLLM): disable thinking in obj mode 2025-11-20 14:52:24 +05:30
ItzCrazyKns
3cc8882b28 feat(prompts): add classifier prompt 2025-11-20 14:51:49 +05:30
ItzCrazyKns
c3830795cb feat(app): add new session manager 2025-11-20 14:51:17 +05:30
ItzCrazyKns
f44ad973aa feat(types): add llm types 2025-11-18 14:39:43 +05:30
ItzCrazyKns
4bcbdad6cb feat(providers): implement custom classes 2025-11-18 14:39:04 +05:30
ItzCrazyKns
5272c7fd3e feat(models): add new base classes 2025-11-18 14:38:12 +05:30
ItzCrazyKns
657a577ec8 feat(app): enhance UI 2025-11-18 14:37:41 +05:30
ItzCrazyKns
f6dac43d7a feat(types): add message & chunk type 2025-11-18 01:17:19 +05:30
ItzCrazyKns
a00f2231d4 feat(chat-window): remove loading state 2025-11-14 23:17:41 +05:30
ItzCrazyKns
1da9b7655c Merge branch 'canary' into feat/improve-search-architecture 2025-11-14 14:38:58 +05:30
ItzCrazyKns
9934c1dbe0 Update README.md 2025-11-14 14:15:06 +05:30
ItzCrazyKns
f767717d7f Update README.md 2025-11-14 14:13:40 +05:30
ItzCrazyKns
e88e1c627c Update README.md 2025-11-14 14:12:43 +05:30
ItzCrazyKns
2edef888a3 Merge branch 'master' into canary 2025-11-14 13:29:22 +05:30
ItzCrazyKns
2dc8078848 Update Exa sponsor image and README styling 2025-11-14 13:23:50 +05:30
ItzCrazyKns
8df81c20cf Update README.md 2025-11-14 13:19:49 +05:30
ItzCrazyKns
34bd02236d Update README.md 2025-11-14 13:17:52 +05:30
ItzCrazyKns
2430376a0c feat(readme): update sponsers 2025-11-14 13:15:59 +05:30
ItzCrazyKns
bd5628b390 feat(package): bump langchain package 2025-11-14 11:45:48 +05:30
ItzCrazyKns
3d5d04eda0 Merge branch 'canary' into feat/improve-search-architecture 2025-11-13 11:54:24 +05:30
ItzCrazyKns
07a17925b1 feat(media-search): supply full history 2025-11-13 11:53:53 +05:30
ItzCrazyKns
3bcf646af1 feat(search-route): handle history processing after llm validation 2025-11-13 11:52:12 +05:30
ItzCrazyKns
e499c0b96e feat(app): migrate video search chain 2025-11-13 11:51:25 +05:30
ItzCrazyKns
33b736e1e8 feat(app): migrate image search chain 2025-11-13 11:51:13 +05:30
Kushagra Srivastava
5e1746f646 Merge pull request #928 from ItzCrazyKns/master
Merge master into canary
2025-11-13 11:49:42 +05:30
ItzCrazyKns
41fe009847 feat(app): migrate suggestion chain 2025-11-13 11:47:28 +05:30
ItzCrazyKns
1a8889c71c feat(app): add new agents directory 2025-11-10 16:45:48 +05:30
ItzCrazyKns
70c1f7230c feat(assets): remove old preview 2025-11-08 21:31:56 +05:30
ItzCrazyKns
c0771095a6 feat(app): lint & beautify 2025-10-30 17:21:48 +05:30
ItzCrazyKns
0856896aff feat(settings): fix text size, enhance UI 2025-10-30 17:21:40 +05:30
ItzCrazyKns
3da53aed03 Merge branch 'master' of https://github.com/ItzCrazyKns/Perplexica 2025-10-30 11:36:30 +05:30
ItzCrazyKns
244675759c feat(config): add getAutoMediaSearch, update uses 2025-10-30 11:29:14 +05:30
ItzCrazyKns
ce6a37aaff feat(settingsFields): add switch field 2025-10-30 11:28:15 +05:30
ItzCrazyKns
c3abba8462 feat(settings): separate personalization & preferences 2025-10-29 23:13:51 +05:30
ItzCrazyKns
f709aa8224 feat(config): add new switch config field 2025-10-29 23:12:09 +05:30
Kushagra Srivastava
22695f4ef6 Merge pull request #916 from skoved/gemini-embedding-fix
fix: list all available gemini embedding models
2025-10-28 21:56:44 +05:30
skoved
75ef2e0282 fix: list all available gemini embedding models
the new settings window does not list all available gemini embedding models. this happens because some gemini embedding models have `embedContent` instead of `embedText`
2025-10-28 11:31:41 -04:00
ItzCrazyKns
b0d97c4c83 feat(readme): revert to screenshot for now 2025-10-27 16:49:57 +05:30
ItzCrazyKns
6527388e25 Update demo.gif 2025-10-27 15:27:50 +05:30
ItzCrazyKns
7397e33f29 feat(app): rename providers to connection, enhance UX 2025-10-27 15:08:50 +05:30
ItzCrazyKns
f6ffa9ebe0 feat(readme): enhance readme 2025-10-27 13:09:59 +05:30
ItzCrazyKns
f9e675823b Create demo.gif 2025-10-27 12:57:34 +05:30
ItzCrazyKns
2e736613c5 Merge branch 'master' into canary 2025-10-27 11:43:18 +05:30
ItzCrazyKns
295334b195 feat(app): fix empty message being sent 2025-10-24 23:40:01 +05:30
ItzCrazyKns
b106abd77f feat(package): bump version 2025-10-24 23:00:07 +05:30
ItzCrazyKns
2d80fc400d feat(app): lint & beautify 2025-10-24 22:58:10 +05:30
ItzCrazyKns
097a5c55c6 feat(layout): add everything inside chat provider 2025-10-24 22:57:56 +05:30
ItzCrazyKns
d0719429b4 feat(app): fix issues with model selection 2025-10-24 22:56:23 +05:30
ItzCrazyKns
600d4ceb29 feat(hf-transformer): use langchain's inbuilt transformer class 2025-10-23 23:06:05 +05:30
ItzCrazyKns
4f50462f1d feat(package): bump version 2025-10-23 21:04:33 +05:30
ItzCrazyKns
231bc22a36 feat(docker): update searxng build script 2025-10-23 19:07:22 +05:30
ItzCrazyKns
cb1d85e458 feat(readme): add volumes 2025-10-21 16:57:57 +05:30
ItzCrazyKns
ce78b4ff62 feat(app): show "add model" button 2025-10-21 16:32:40 +05:30
ItzCrazyKns
88ae67065b feat(config): add measurement unit 2025-10-21 15:59:15 +05:30
ItzCrazyKns
f35d12f94c Update perplexica-screenshot.png 2025-10-21 15:26:29 +05:30
ItzCrazyKns
3d17975d83 feat(model-select): use values from localStorage 2025-10-21 15:25:38 +05:30
Kushagra Srivastava
950717e0cf Delete app.dockerfile 2025-10-21 15:13:17 +05:30
Kushagra Srivastava
4f39b5746a Merge pull request #906 from ItzCrazyKns/canary
Release v1.11.0
2025-10-21 15:07:55 +05:30
117 changed files with 5825 additions and 3529 deletions

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README.md
View File

@@ -1,74 +1,76 @@
# 🚀 Perplexica - An AI-powered search engine 🔎 <!-- omit in toc -->
<div align="center" markdown="1">
<sup>Special thanks to:</sup>
<br>
<br>
<a href="https://www.warp.dev/perplexica">
<img alt="Warp sponsorship" width="400" src="https://github.com/user-attachments/assets/775dd593-9b5f-40f1-bf48-479faff4c27b">
</a>
### [Warp, the AI Devtool that lives in your terminal](https://www.warp.dev/perplexica)
[Available for MacOS, Linux, & Windows](https://www.warp.dev/perplexica)
</div>
<hr/>
# Perplexica 🔍
[![GitHub Repo stars](https://img.shields.io/github/stars/ItzCrazyKns/Perplexica?style=social)](https://github.com/ItzCrazyKns/Perplexica/stargazers)
[![GitHub forks](https://img.shields.io/github/forks/ItzCrazyKns/Perplexica?style=social)](https://github.com/ItzCrazyKns/Perplexica/network/members)
[![GitHub watchers](https://img.shields.io/github/watchers/ItzCrazyKns/Perplexica?style=social)](https://github.com/ItzCrazyKns/Perplexica/watchers)
[![Docker Pulls](https://img.shields.io/docker/pulls/itzcrazykns1337/perplexica?color=blue)](https://hub.docker.com/r/itzcrazykns1337/perplexica)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/ItzCrazyKns/Perplexica/blob/master/LICENSE)
[![GitHub last commit](https://img.shields.io/github/last-commit/ItzCrazyKns/Perplexica?color=green)](https://github.com/ItzCrazyKns/Perplexica/commits/master)
[![Discord](https://dcbadge.limes.pink/api/server/26aArMy8tT?style=flat)](https://discord.gg/26aArMy8tT)
![preview](.assets/perplexica-screenshot.png?)
Perplexica is a **privacy-focused AI answering engine** that runs entirely on your own hardware. It combines knowledge from the vast internet with support for **local LLMs** (Ollama) and cloud providers (OpenAI, Claude, Groq), delivering accurate answers with **cited sources** while keeping your searches completely private.
## Table of Contents <!-- omit in toc -->
- [Overview](#overview)
- [Preview](#preview)
- [Features](#features)
- [Installation](#installation)
- [Getting Started with Docker (Recommended)](#getting-started-with-docker-recommended)
- [Non-Docker Installation](#non-docker-installation)
- [Ollama Connection Errors](#ollama-connection-errors)
- [Lemonade Connection Errors](#lemonade-connection-errors)
- [Using as a Search Engine](#using-as-a-search-engine)
- [Using Perplexica's API](#using-perplexicas-api)
- [Expose Perplexica to a network](#expose-perplexica-to-network)
- [One-Click Deployment](#one-click-deployment)
- [Upcoming Features](#upcoming-features)
- [Support Us](#support-us)
- [Donations](#donations)
- [Contribution](#contribution)
- [Help and Support](#help-and-support)
## Overview
Perplexica is an open-source AI-powered searching tool or an AI-powered search engine that goes deep into the internet to find answers. Inspired by Perplexity AI, it's an open-source option that not just searches the web but understands your questions. It uses advanced machine learning algorithms like similarity searching and embeddings to refine results and provides clear answers with sources cited.
Using SearxNG to stay current and fully open source, Perplexica ensures you always get the most up-to-date information without compromising your privacy.
![preview](.assets/perplexica-screenshot.png)
Want to know more about its architecture and how it works? You can read it [here](https://github.com/ItzCrazyKns/Perplexica/tree/master/docs/architecture/README.md).
## Preview
## ✨ Features
![video-preview](.assets/perplexica-preview.gif)
🤖 **Support for all major AI providers** - Use local LLMs through Ollama or connect to OpenAI, Anthropic Claude, Google Gemini, Groq, and more. Mix and match models based on your needs.
## Features
**Smart search modes** - Choose Balanced Mode for everyday searches, Fast Mode when you need quick answers, or wait for Quality Mode (coming soon) for deep research.
- **Local LLMs**: You can utilize local LLMs such as Qwen, DeepSeek, Llama, and Mistral.
- **Two Main Modes:**
- **Copilot Mode:** (In development) Boosts search by generating different queries to find more relevant internet sources. Like normal search instead of just using the context by SearxNG, it visits the top matches and tries to find relevant sources to the user's query directly from the page.
- **Normal Mode:** Processes your query and performs a web search.
- **Focus Modes:** Special modes to better answer specific types of questions. Perplexica currently has 6 focus modes:
- **All Mode:** Searches the entire web to find the best results.
- **Writing Assistant Mode:** Helpful for writing tasks that do not require searching the web.
- **Academic Search Mode:** Finds articles and papers, ideal for academic research.
- **YouTube Search Mode:** Finds YouTube videos based on the search query.
- **Wolfram Alpha Search Mode:** Answers queries that need calculations or data analysis using Wolfram Alpha.
- **Reddit Search Mode:** Searches Reddit for discussions and opinions related to the query.
- **Current Information:** Some search tools might give you outdated info because they use data from crawling bots and convert them into embeddings and store them in a index. Unlike them, Perplexica uses SearxNG, a metasearch engine to get the results and rerank and get the most relevant source out of it, ensuring you always get the latest information without the overhead of daily data updates.
- **API**: Integrate Perplexica into your existing applications and make use of its capibilities.
🎯 **Six specialized focus modes** - Get better results with modes designed for specific tasks: Academic papers, YouTube videos, Reddit discussions, Wolfram Alpha calculations, writing assistance, or general web search.
It has many more features like image and video search. Some of the planned features are mentioned in [upcoming features](#upcoming-features).
🔍 **Web search powered by SearxNG** - Access multiple search engines while keeping your identity private. Support for Tavily and Exa coming soon for even better results.
📷 **Image and video search** - Find visual content alongside text results. Search isn't limited to just articles anymore.
📄 **File uploads** - Upload documents and ask questions about them. PDFs, text files, images - Perplexica understands them all.
🌐 **Search specific domains** - Limit your search to specific websites when you know where to look. Perfect for technical documentation or research papers.
💡 **Smart suggestions** - Get intelligent search suggestions as you type, helping you formulate better queries.
📚 **Discover** - Browse interesting articles and trending content throughout the day. Stay informed without even searching.
🕒 **Search history** - Every search is saved locally so you can revisit your discoveries anytime. Your research is never lost.
**More coming soon** - We're actively developing new features based on community feedback. Join our Discord to help shape Perplexica's future!
## Sponsors
Perplexica's development is powered by the generous support of our sponsors. Their contributions help keep this project free, open-source, and accessible to everyone.
<div align="center">
<a href="https://www.warp.dev/perplexica">
<img alt="Warp Terminal" src=".assets/sponsers/warp.png" width="100%">
</a>
### **✨ [Try Warp - The AI-Powered Terminal →](https://www.warp.dev/perplexica)**
Warp is revolutionizing development workflows with AI-powered features, modern UX, and blazing-fast performance. Used by developers at top companies worldwide.
</div>
---
We'd also like to thank the following partners for their generous support:
<table>
<tr>
<td width="100" align="center">
<a href="https://dashboard.exa.ai" target="_blank">
<img src=".assets/sponsers/exa.png" alt="Exa" width="80" height="80" style="border-radius: .75rem;" />
</a>
</td>
<td>
<a href="https://dashboard.exa.ai">Exa</a> • The Perfect Web Search API for LLMs - web search, crawling, deep research, and answer APIs
</td>
</tr>
</table>
## Installation
@@ -79,19 +81,19 @@ There are mainly 2 ways of installing Perplexica - With Docker, Without Docker.
Perplexica can be easily run using Docker. Simply run the following command:
```bash
docker run -p 3000:3000 --name perplexica itzcrazykns1337/perplexica:latest
docker run -d -p 3000:3000 -v perplexica-data:/home/perplexica/data -v perplexica-uploads:/home/perplexica/uploads --name perplexica itzcrazykns1337/perplexica:latest
```
This will pull and start the Perplexica container with the bundled SearxNG search engine. Once running, open your browser and navigate to http://localhost:3000. You can then configure your settings (API keys, models, etc.) directly in the setup screen.
**Note**: The image includes both Perplexica and SearxNG, so no additional setup is required.
**Note**: The image includes both Perplexica and SearxNG, so no additional setup is required. The `-v` flags create persistent volumes for your data and uploaded files.
#### Using Perplexica with Your Own SearxNG Instance
If you already have SearxNG running, you can use the slim version of Perplexica:
```bash
docker run -p 3000:3000 -e SEARXNG_API_URL=http://your-searxng-url:8080 --name perplexica itzcrazykns1337/perplexica:slim-latest
docker run -d -p 3000:3000 -e SEARXNG_API_URL=http://your-searxng-url:8080 -v perplexica-data:/home/perplexica/data -v perplexica-uploads:/home/perplexica/uploads --name perplexica itzcrazykns1337/perplexica:slim-latest
```
**Important**: Make sure your SearxNG instance has:
@@ -118,7 +120,7 @@ If you prefer to build from source or need more control:
```bash
docker build -t perplexica .
docker run -p 3000:3000 --name perplexica perplexica
docker run -d -p 3000:3000 -v perplexica-data:/home/perplexica/data -v perplexica-uploads:/home/perplexica/uploads --name perplexica perplexica
```
5. Access Perplexica at http://localhost:3000 and configure your settings in the setup screen.

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@@ -1,37 +0,0 @@
FROM node:24.5.0-slim AS builder
RUN apt-get update && apt-get install -y python3 python3-pip sqlite3 && rm -rf /var/lib/apt/lists/*
WORKDIR /home/perplexica
COPY package.json yarn.lock ./
RUN yarn install --frozen-lockfile --network-timeout 600000
COPY tsconfig.json next.config.mjs next-env.d.ts postcss.config.js drizzle.config.ts tailwind.config.ts ./
COPY src ./src
COPY public ./public
COPY drizzle ./drizzle
RUN mkdir -p /home/perplexica/data
RUN yarn build
FROM node:24.5.0-slim
RUN apt-get update && apt-get install -y python3 python3-pip sqlite3 && rm -rf /var/lib/apt/lists/*
WORKDIR /home/perplexica
COPY --from=builder /home/perplexica/public ./public
COPY --from=builder /home/perplexica/.next/static ./public/_next/static
COPY --from=builder /home/perplexica/.next/standalone ./
COPY --from=builder /home/perplexica/data ./data
COPY drizzle ./drizzle
RUN mkdir /home/perplexica/uploads
COPY entrypoint.sh ./entrypoint.sh
RUN chmod +x ./entrypoint.sh
RUN sed -i 's/\r$//' ./entrypoint.sh || true
CMD ["/home/perplexica/entrypoint.sh"]

15
docker-compose.yaml Normal file
View File

@@ -0,0 +1,15 @@
services:
perplexica:
image: itzcrazykns1337/perplexica:latest
ports:
- '3000:3000'
volumes:
- data:/home/perplexica/data
- uploads:/home/perplexica/uploads
restart: unless-stopped
volumes:
data:
name: 'perplexica-data'
uploads:
name: 'perplexica-uploads'

View File

@@ -17,6 +17,7 @@ Before making search requests, you'll need to get the available providers and th
Returns a list of all active providers with their available chat and embedding models.
**Response Example:**
```json
{
"providers": [

View File

@@ -10,7 +10,7 @@ Simply pull the latest image and restart your container:
docker pull itzcrazykns1337/perplexica:latest
docker stop perplexica
docker rm perplexica
docker run -p 3000:3000 --name perplexica itzcrazykns1337/perplexica:latest
docker run -d -p 3000:3000 -v perplexica-data:/home/perplexica/data -v perplexica-uploads:/home/perplexica/uploads --name perplexica itzcrazykns1337/perplexica:latest
```
For slim version:
@@ -19,7 +19,7 @@ For slim version:
docker pull itzcrazykns1337/perplexica:slim-latest
docker stop perplexica
docker rm perplexica
docker run -p 3000:3000 -e SEARXNG_API_URL=http://your-searxng-url:8080 --name perplexica itzcrazykns1337/perplexica:slim-latest
docker run -d -p 3000:3000 -e SEARXNG_API_URL=http://your-searxng-url:8080 -v perplexica-data:/home/perplexica/data -v perplexica-uploads:/home/perplexica/uploads --name perplexica itzcrazykns1337/perplexica:slim-latest
```
Once updated, go to http://localhost:3000 and verify the latest changes. Your settings are preserved automatically.

View File

@@ -0,0 +1,15 @@
PRAGMA foreign_keys=OFF;--> statement-breakpoint
CREATE TABLE `__new_messages` (
`id` integer PRIMARY KEY NOT NULL,
`messageId` text NOT NULL,
`chatId` text NOT NULL,
`backendId` text NOT NULL,
`query` text NOT NULL,
`createdAt` text NOT NULL,
`responseBlocks` text DEFAULT '[]',
`status` text DEFAULT 'answering'
);
--> statement-breakpoint
DROP TABLE `messages`;--> statement-breakpoint
ALTER TABLE `__new_messages` RENAME TO `messages`;--> statement-breakpoint
PRAGMA foreign_keys=ON;

View File

@@ -0,0 +1,132 @@
{
"version": "6",
"dialect": "sqlite",
"id": "1c5eb804-d6b4-48ec-9a8f-75fb729c8e52",
"prevId": "6dedf55f-0e44-478f-82cf-14a21ac686f8",
"tables": {
"chats": {
"name": "chats",
"columns": {
"id": {
"name": "id",
"type": "text",
"primaryKey": true,
"notNull": true,
"autoincrement": false
},
"title": {
"name": "title",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"createdAt": {
"name": "createdAt",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"focusMode": {
"name": "focusMode",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"files": {
"name": "files",
"type": "text",
"primaryKey": false,
"notNull": false,
"autoincrement": false,
"default": "'[]'"
}
},
"indexes": {},
"foreignKeys": {},
"compositePrimaryKeys": {},
"uniqueConstraints": {},
"checkConstraints": {}
},
"messages": {
"name": "messages",
"columns": {
"id": {
"name": "id",
"type": "integer",
"primaryKey": true,
"notNull": true,
"autoincrement": false
},
"messageId": {
"name": "messageId",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"chatId": {
"name": "chatId",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"backendId": {
"name": "backendId",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"query": {
"name": "query",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"createdAt": {
"name": "createdAt",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"responseBlocks": {
"name": "responseBlocks",
"type": "text",
"primaryKey": false,
"notNull": false,
"autoincrement": false,
"default": "'[]'"
},
"status": {
"name": "status",
"type": "text",
"primaryKey": false,
"notNull": false,
"autoincrement": false,
"default": "'answering'"
}
},
"indexes": {},
"foreignKeys": {},
"compositePrimaryKeys": {},
"uniqueConstraints": {},
"checkConstraints": {}
}
},
"views": {},
"enums": {},
"_meta": {
"schemas": {},
"tables": {},
"columns": {}
},
"internal": {
"indexes": {}
}
}

View File

@@ -15,6 +15,13 @@
"when": 1758863991284,
"tag": "0001_wise_rockslide",
"breakpoints": true
},
{
"idx": 2,
"version": "6",
"when": 1763732708332,
"tag": "0002_daffy_wrecker",
"breakpoints": true
}
]
}

View File

@@ -1,6 +1,6 @@
{
"name": "perplexica-frontend",
"version": "1.11.0",
"version": "1.11.2",
"license": "MIT",
"author": "ItzCrazyKns",
"scripts": {
@@ -16,13 +16,14 @@
"@huggingface/transformers": "^3.7.5",
"@iarna/toml": "^2.2.5",
"@icons-pack/react-simple-icons": "^12.3.0",
"@langchain/anthropic": "^1.0.0",
"@langchain/community": "^1.0.0",
"@langchain/core": "^1.0.1",
"@langchain/google-genai": "^1.0.0",
"@langchain/groq": "^1.0.0",
"@langchain/ollama": "^1.0.0",
"@langchain/openai": "^1.0.0",
"@langchain/anthropic": "^1.0.1",
"@langchain/community": "^1.0.3",
"@langchain/core": "^1.0.5",
"@langchain/google-genai": "^1.0.1",
"@langchain/groq": "^1.0.1",
"@langchain/langgraph": "^1.0.1",
"@langchain/ollama": "^1.0.1",
"@langchain/openai": "^1.1.1",
"@langchain/textsplitters": "^1.0.0",
"@tailwindcss/typography": "^0.5.12",
"axios": "^1.8.3",
@@ -33,22 +34,29 @@
"framer-motion": "^12.23.24",
"html-to-text": "^9.0.5",
"jspdf": "^3.0.1",
"langchain": "^1.0.1",
"langchain": "^1.0.4",
"lightweight-charts": "^5.0.9",
"lucide-react": "^0.363.0",
"mammoth": "^1.9.1",
"markdown-to-jsx": "^7.7.2",
"mathjs": "^15.1.0",
"next": "^15.2.2",
"next-themes": "^0.3.0",
"ollama": "^0.6.3",
"openai": "^6.9.0",
"partial-json": "^0.1.7",
"pdf-parse": "^1.1.1",
"react": "^18",
"react-dom": "^18",
"react-text-to-speech": "^0.14.5",
"react-textarea-autosize": "^8.5.3",
"rfc6902": "^5.1.2",
"sonner": "^1.4.41",
"tailwind-merge": "^2.2.2",
"winston": "^3.17.0",
"yahoo-finance2": "^3.10.2",
"yet-another-react-lightbox": "^3.17.2",
"zod": "^3.22.4"
"zod": "^4.1.12"
},
"devDependencies": {
"@types/better-sqlite3": "^7.6.12",

View File

@@ -1,14 +1,10 @@
import crypto from 'crypto';
import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
import { EventEmitter } from 'stream';
import db from '@/lib/db';
import { chats, messages as messagesSchema } from '@/lib/db/schema';
import { and, eq, gt } from 'drizzle-orm';
import { getFileDetails } from '@/lib/utils/files';
import { searchHandlers } from '@/lib/search';
import { z } from 'zod';
import ModelRegistry from '@/lib/models/registry';
import { ModelWithProvider } from '@/lib/models/types';
import SearchAgent from '@/lib/agents/search';
import SessionManager from '@/lib/session';
import { ChatTurnMessage } from '@/lib/types';
export const runtime = 'nodejs';
export const dynamic = 'force-dynamic';
@@ -20,47 +16,25 @@ const messageSchema = z.object({
});
const chatModelSchema: z.ZodType<ModelWithProvider> = z.object({
providerId: z.string({
errorMap: () => ({
message: 'Chat model provider id must be provided',
}),
}),
key: z.string({
errorMap: () => ({
message: 'Chat model key must be provided',
}),
}),
providerId: z.string({ message: 'Chat model provider id must be provided' }),
key: z.string({ message: 'Chat model key must be provided' }),
});
const embeddingModelSchema: z.ZodType<ModelWithProvider> = z.object({
providerId: z.string({
errorMap: () => ({
message: 'Embedding model provider id must be provided',
}),
}),
key: z.string({
errorMap: () => ({
message: 'Embedding model key must be provided',
}),
message: 'Embedding model provider id must be provided',
}),
key: z.string({ message: 'Embedding model key must be provided' }),
});
const bodySchema = z.object({
message: messageSchema,
optimizationMode: z.enum(['speed', 'balanced', 'quality'], {
errorMap: () => ({
message: 'Optimization mode must be one of: speed, balanced, quality',
}),
message: 'Optimization mode must be one of: speed, balanced, quality',
}),
focusMode: z.string().min(1, 'Focus mode is required'),
history: z
.array(
z.tuple([z.string(), z.string()], {
errorMap: () => ({
message: 'History items must be tuples of two strings',
}),
}),
)
.array(z.tuple([z.string(), z.string()]))
.optional()
.default([]),
files: z.array(z.string()).optional().default([]),
@@ -78,7 +52,7 @@ const safeValidateBody = (data: unknown) => {
if (!result.success) {
return {
success: false,
error: result.error.errors.map((e) => ({
error: result.error.issues.map((e: any) => ({
path: e.path.join('.'),
message: e.message,
})),
@@ -91,151 +65,12 @@ const safeValidateBody = (data: unknown) => {
};
};
const handleEmitterEvents = async (
stream: EventEmitter,
writer: WritableStreamDefaultWriter,
encoder: TextEncoder,
chatId: string,
) => {
let receivedMessage = '';
const aiMessageId = crypto.randomBytes(7).toString('hex');
stream.on('data', (data) => {
const parsedData = JSON.parse(data);
if (parsedData.type === 'response') {
writer.write(
encoder.encode(
JSON.stringify({
type: 'message',
data: parsedData.data,
messageId: aiMessageId,
}) + '\n',
),
);
receivedMessage += parsedData.data;
} else if (parsedData.type === 'sources') {
writer.write(
encoder.encode(
JSON.stringify({
type: 'sources',
data: parsedData.data,
messageId: aiMessageId,
}) + '\n',
),
);
const sourceMessageId = crypto.randomBytes(7).toString('hex');
db.insert(messagesSchema)
.values({
chatId: chatId,
messageId: sourceMessageId,
role: 'source',
sources: parsedData.data,
createdAt: new Date().toString(),
})
.execute();
}
});
stream.on('end', () => {
writer.write(
encoder.encode(
JSON.stringify({
type: 'messageEnd',
}) + '\n',
),
);
writer.close();
db.insert(messagesSchema)
.values({
content: receivedMessage,
chatId: chatId,
messageId: aiMessageId,
role: 'assistant',
createdAt: new Date().toString(),
})
.execute();
});
stream.on('error', (data) => {
const parsedData = JSON.parse(data);
writer.write(
encoder.encode(
JSON.stringify({
type: 'error',
data: parsedData.data,
}),
),
);
writer.close();
});
};
const handleHistorySave = async (
message: Message,
humanMessageId: string,
focusMode: string,
files: string[],
) => {
const chat = await db.query.chats.findFirst({
where: eq(chats.id, message.chatId),
});
const fileData = files.map(getFileDetails);
if (!chat) {
await db
.insert(chats)
.values({
id: message.chatId,
title: message.content,
createdAt: new Date().toString(),
focusMode: focusMode,
files: fileData,
})
.execute();
} else if (JSON.stringify(chat.files ?? []) != JSON.stringify(fileData)) {
db.update(chats)
.set({
files: files.map(getFileDetails),
})
.where(eq(chats.id, message.chatId));
}
const messageExists = await db.query.messages.findFirst({
where: eq(messagesSchema.messageId, humanMessageId),
});
if (!messageExists) {
await db
.insert(messagesSchema)
.values({
content: message.content,
chatId: message.chatId,
messageId: humanMessageId,
role: 'user',
createdAt: new Date().toString(),
})
.execute();
} else {
await db
.delete(messagesSchema)
.where(
and(
gt(messagesSchema.id, messageExists.id),
eq(messagesSchema.chatId, message.chatId),
),
)
.execute();
}
};
export const POST = async (req: Request) => {
try {
const reqBody = (await req.json()) as Body;
const parseBody = safeValidateBody(reqBody);
if (!parseBody.success) {
return Response.json(
{ message: 'Invalid request body', error: parseBody.error },
@@ -265,48 +100,116 @@ export const POST = async (req: Request) => {
),
]);
const humanMessageId =
message.messageId ?? crypto.randomBytes(7).toString('hex');
const history: BaseMessage[] = body.history.map((msg) => {
const history: ChatTurnMessage[] = body.history.map((msg) => {
if (msg[0] === 'human') {
return new HumanMessage({
return {
role: 'user',
content: msg[1],
});
};
} else {
return new AIMessage({
return {
role: 'assistant',
content: msg[1],
});
};
}
});
const handler = searchHandlers[body.focusMode];
if (!handler) {
return Response.json(
{
message: 'Invalid focus mode',
},
{ status: 400 },
);
}
const stream = await handler.searchAndAnswer(
message.content,
history,
llm,
embedding,
body.optimizationMode,
body.files,
body.systemInstructions as string,
);
const agent = new SearchAgent();
const session = SessionManager.createSession();
const responseStream = new TransformStream();
const writer = responseStream.writable.getWriter();
const encoder = new TextEncoder();
handleEmitterEvents(stream, writer, encoder, message.chatId);
handleHistorySave(message, humanMessageId, body.focusMode, body.files);
let receivedMessage = '';
session.addListener('data', (data: any) => {
if (data.type === 'response') {
writer.write(
encoder.encode(
JSON.stringify({
type: 'message',
data: data.data,
}) + '\n',
),
);
receivedMessage += data.data;
} else if (data.type === 'sources') {
writer.write(
encoder.encode(
JSON.stringify({
type: 'sources',
data: data.data,
}) + '\n',
),
);
} else if (data.type === 'block') {
writer.write(
encoder.encode(
JSON.stringify({
type: 'block',
block: data.block,
}) + '\n',
),
);
} else if (data.type === 'updateBlock') {
writer.write(
encoder.encode(
JSON.stringify({
type: 'updateBlock',
blockId: data.blockId,
patch: data.patch,
}) + '\n',
),
);
} else if (data.type === 'researchComplete') {
writer.write(
encoder.encode(
JSON.stringify({
type: 'researchComplete',
}) + '\n',
),
);
}
});
session.addListener('end', () => {
writer.write(
encoder.encode(
JSON.stringify({
type: 'messageEnd',
}) + '\n',
),
);
writer.close();
session.removeAllListeners();
});
session.addListener('error', (data: any) => {
writer.write(
encoder.encode(
JSON.stringify({
type: 'error',
data: data.data,
}) + '\n',
),
);
writer.close();
session.removeAllListeners();
});
agent.searchAsync(session, {
chatHistory: history,
followUp: message.content,
config: {
llm,
embedding: embedding,
sources: ['web'],
mode: body.optimizationMode,
},
});
/* handleHistorySave(message, humanMessageId, body.focusMode, body.files); */
return new Response(responseStream.readable, {
headers: {

View File

@@ -1,7 +1,6 @@
import handleImageSearch from '@/lib/chains/imageSearchAgent';
import searchImages from '@/lib/agents/media/image';
import ModelRegistry from '@/lib/models/registry';
import { ModelWithProvider } from '@/lib/models/types';
import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
interface ImageSearchBody {
query: string;
@@ -13,16 +12,6 @@ export const POST = async (req: Request) => {
try {
const body: ImageSearchBody = await req.json();
const chatHistory = body.chatHistory
.map((msg: any) => {
if (msg.role === 'user') {
return new HumanMessage(msg.content);
} else if (msg.role === 'assistant') {
return new AIMessage(msg.content);
}
})
.filter((msg) => msg !== undefined) as BaseMessage[];
const registry = new ModelRegistry();
const llm = await registry.loadChatModel(
@@ -30,9 +19,9 @@ export const POST = async (req: Request) => {
body.chatModel.key,
);
const images = await handleImageSearch(
const images = await searchImages(
{
chat_history: chatHistory,
chatHistory: body.chatHistory,
query: body.query,
},
llm,

View File

@@ -1,8 +1,8 @@
import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
import { MetaSearchAgentType } from '@/lib/search/metaSearchAgent';
import { searchHandlers } from '@/lib/search';
import ModelRegistry from '@/lib/models/registry';
import { ModelWithProvider } from '@/lib/models/types';
import SessionManager from '@/lib/session';
import SearchAgent from '@/lib/agents/search';
import { ChatTurnMessage } from '@/lib/types';
interface ChatRequestBody {
optimizationMode: 'speed' | 'balanced';
@@ -30,12 +30,6 @@ export const POST = async (req: Request) => {
body.optimizationMode = body.optimizationMode || 'balanced';
body.stream = body.stream || false;
const history: BaseMessage[] = body.history.map((msg) => {
return msg[0] === 'human'
? new HumanMessage({ content: msg[1] })
: new AIMessage({ content: msg[1] });
});
const registry = new ModelRegistry();
const [llm, embeddings] = await Promise.all([
@@ -46,21 +40,26 @@ export const POST = async (req: Request) => {
),
]);
const searchHandler: MetaSearchAgentType = searchHandlers[body.focusMode];
const history: ChatTurnMessage[] = body.history.map((msg) => {
return msg[0] === 'human'
? { role: 'user', content: msg[1] }
: { role: 'assistant', content: msg[1] };
});
if (!searchHandler) {
return Response.json({ message: 'Invalid focus mode' }, { status: 400 });
}
const session = SessionManager.createSession();
const emitter = await searchHandler.searchAndAnswer(
body.query,
history,
llm,
embeddings,
body.optimizationMode,
[],
body.systemInstructions || '',
);
const agent = new SearchAgent();
agent.searchAsync(session, {
chatHistory: history,
config: {
embedding: embeddings,
llm: llm,
sources: ['web', 'discussions', 'academic'],
mode: 'balanced',
},
followUp: body.query,
});
if (!body.stream) {
return new Promise(
@@ -71,7 +70,7 @@ export const POST = async (req: Request) => {
let message = '';
let sources: any[] = [];
emitter.on('data', (data: string) => {
session.addListener('data', (data: string) => {
try {
const parsedData = JSON.parse(data);
if (parsedData.type === 'response') {
@@ -89,11 +88,11 @@ export const POST = async (req: Request) => {
}
});
emitter.on('end', () => {
session.addListener('end', () => {
resolve(Response.json({ message, sources }, { status: 200 }));
});
emitter.on('error', (error: any) => {
session.addListener('error', (error: any) => {
reject(
Response.json(
{ message: 'Search error', error },
@@ -124,14 +123,14 @@ export const POST = async (req: Request) => {
);
signal.addEventListener('abort', () => {
emitter.removeAllListeners();
session.removeAllListeners();
try {
controller.close();
} catch (error) {}
});
emitter.on('data', (data: string) => {
session.addListener('data', (data: string) => {
if (signal.aborted) return;
try {
@@ -162,7 +161,7 @@ export const POST = async (req: Request) => {
}
});
emitter.on('end', () => {
session.addListener('end', () => {
if (signal.aborted) return;
controller.enqueue(
@@ -175,7 +174,7 @@ export const POST = async (req: Request) => {
controller.close();
});
emitter.on('error', (error: any) => {
session.addListener('error', (error: any) => {
if (signal.aborted) return;
controller.error(error);

View File

@@ -1,7 +1,6 @@
import generateSuggestions from '@/lib/chains/suggestionGeneratorAgent';
import generateSuggestions from '@/lib/agents/suggestions';
import ModelRegistry from '@/lib/models/registry';
import { ModelWithProvider } from '@/lib/models/types';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
interface SuggestionsGenerationBody {
@@ -13,16 +12,6 @@ export const POST = async (req: Request) => {
try {
const body: SuggestionsGenerationBody = await req.json();
const chatHistory = body.chatHistory
.map((msg: any) => {
if (msg.role === 'user') {
return new HumanMessage(msg.content);
} else if (msg.role === 'assistant') {
return new AIMessage(msg.content);
}
})
.filter((msg) => msg !== undefined) as BaseMessage[];
const registry = new ModelRegistry();
const llm = await registry.loadChatModel(
@@ -32,7 +21,7 @@ export const POST = async (req: Request) => {
const suggestions = await generateSuggestions(
{
chat_history: chatHistory,
chatHistory: body.chatHistory,
},
llm,
);

View File

@@ -7,6 +7,7 @@ import { DocxLoader } from '@langchain/community/document_loaders/fs/docx';
import { RecursiveCharacterTextSplitter } from '@langchain/textsplitters';
import { Document } from '@langchain/core/documents';
import ModelRegistry from '@/lib/models/registry';
import { Chunk } from '@/lib/types';
interface FileRes {
fileName: string;
@@ -87,9 +88,17 @@ export async function POST(req: Request) {
}),
);
const embeddings = await model.embedDocuments(
splitted.map((doc) => doc.pageContent),
const chunks: Chunk[] = splitted.map((doc) => {
return {
content: doc.pageContent,
metadata: doc.metadata,
}
});
const embeddings = await model.embedChunks(
chunks
);
const embeddingsDataPath = filePath.replace(
/\.\w+$/,
'-embeddings.json',

View File

@@ -1,7 +1,6 @@
import handleVideoSearch from '@/lib/chains/videoSearchAgent';
import handleVideoSearch from '@/lib/agents/media/video';
import ModelRegistry from '@/lib/models/registry';
import { ModelWithProvider } from '@/lib/models/types';
import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
interface VideoSearchBody {
query: string;
@@ -13,16 +12,6 @@ export const POST = async (req: Request) => {
try {
const body: VideoSearchBody = await req.json();
const chatHistory = body.chatHistory
.map((msg: any) => {
if (msg.role === 'user') {
return new HumanMessage(msg.content);
} else if (msg.role === 'assistant') {
return new AIMessage(msg.content);
}
})
.filter((msg) => msg !== undefined) as BaseMessage[];
const registry = new ModelRegistry();
const llm = await registry.loadChatModel(
@@ -32,7 +21,7 @@ export const POST = async (req: Request) => {
const videos = await handleVideoSearch(
{
chat_history: chatHistory,
chatHistory: body.chatHistory,
query: body.query,
},
llm,

View File

@@ -1,17 +1,10 @@
'use client';
import ChatWindow from '@/components/ChatWindow';
import { useParams } from 'next/navigation';
import React from 'react';
import { ChatProvider } from '@/lib/hooks/useChat';
const Page = () => {
const { chatId }: { chatId: string } = useParams();
return (
<ChatProvider id={chatId}>
<ChatWindow />
</ChatProvider>
);
return <ChatWindow />;
};
export default Page;

View File

@@ -9,6 +9,7 @@ import { Toaster } from 'sonner';
import ThemeProvider from '@/components/theme/Provider';
import configManager from '@/lib/config';
import SetupWizard from '@/components/Setup/SetupWizard';
import { ChatProvider } from '@/lib/hooks/useChat';
const montserrat = Montserrat({
weight: ['300', '400', '500', '700'],
@@ -36,7 +37,7 @@ export default function RootLayout({
<body className={cn('h-full', montserrat.className)}>
<ThemeProvider>
{setupComplete ? (
<>
<ChatProvider>
<Sidebar>{children}</Sidebar>
<Toaster
toastOptions={{
@@ -47,7 +48,7 @@ export default function RootLayout({
},
}}
/>
</>
</ChatProvider>
) : (
<SetupWizard configSections={configSections} />
)}

View File

@@ -1,7 +1,5 @@
import ChatWindow from '@/components/ChatWindow';
import { ChatProvider } from '@/lib/hooks/useChat';
import { Metadata } from 'next';
import { Suspense } from 'react';
export const metadata: Metadata = {
title: 'Chat - Perplexica',
@@ -9,15 +7,7 @@ export const metadata: Metadata = {
};
const Home = () => {
return (
<div>
<Suspense>
<ChatProvider>
<ChatWindow />
</ChatProvider>
</Suspense>
</div>
);
return <ChatWindow />;
};
export default Home;

View File

@@ -0,0 +1,197 @@
'use client';
import { Brain, Search, FileText, ChevronDown, ChevronUp } from 'lucide-react';
import { motion, AnimatePresence } from 'framer-motion';
import { useEffect, useState } from 'react';
import { ResearchBlock, ResearchBlockSubStep } from '@/lib/types';
import { useChat } from '@/lib/hooks/useChat';
const getStepIcon = (step: ResearchBlockSubStep) => {
if (step.type === 'reasoning') {
return <Brain className="w-4 h-4" />;
} else if (step.type === 'searching') {
return <Search className="w-4 h-4" />;
} else if (step.type === 'reading') {
return <FileText className="w-4 h-4" />;
}
return null;
};
const getStepTitle = (
step: ResearchBlockSubStep,
isStreaming: boolean,
): string => {
if (step.type === 'reasoning') {
return isStreaming && !step.reasoning ? 'Thinking...' : 'Thinking';
} else if (step.type === 'searching') {
return `Searching ${step.searching.length} ${step.searching.length === 1 ? 'query' : 'queries'}`;
} else if (step.type === 'reading') {
return `Found ${step.reading.length} ${step.reading.length === 1 ? 'result' : 'results'}`;
}
return 'Processing';
};
const AssistantSteps = ({
block,
status,
}: {
block: ResearchBlock;
status: 'answering' | 'completed' | 'error';
}) => {
const [isExpanded, setIsExpanded] = useState(true);
const { researchEnded, loading } = useChat();
useEffect(() => {
if (researchEnded) {
setIsExpanded(false);
} else if (status === 'answering') {
setIsExpanded(true);
}
}, [researchEnded, status]);
if (!block || block.data.subSteps.length === 0) return null;
return (
<div className="rounded-lg bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 overflow-hidden">
<button
onClick={() => setIsExpanded(!isExpanded)}
className="w-full flex items-center justify-between p-3 hover:bg-light-200 dark:hover:bg-dark-200 transition duration-200"
>
<div className="flex items-center gap-2">
<Brain className="w-4 h-4 text-black dark:text-white" />
<span className="text-sm font-medium text-black dark:text-white">
Research Progress ({block.data.subSteps.length}{' '}
{block.data.subSteps.length === 1 ? 'step' : 'steps'})
</span>
</div>
{isExpanded ? (
<ChevronUp className="w-4 h-4 text-black/70 dark:text-white/70" />
) : (
<ChevronDown className="w-4 h-4 text-black/70 dark:text-white/70" />
)}
</button>
<AnimatePresence>
{isExpanded && (
<motion.div
initial={{ height: 0, opacity: 0 }}
animate={{ height: 'auto', opacity: 1 }}
exit={{ height: 0, opacity: 0 }}
transition={{ duration: 0.2 }}
className="border-t border-light-200 dark:border-dark-200"
>
<div className="p-3 space-y-2">
{block.data.subSteps.map((step, index) => {
const isLastStep = index === block.data.subSteps.length - 1;
const isStreaming = loading && isLastStep && !researchEnded;
return (
<motion.div
key={step.id}
initial={{ opacity: 0, x: -10 }}
animate={{ opacity: 1, x: 0 }}
transition={{ duration: 0.2, delay: 0 }}
className="flex gap-3"
>
{/* Timeline connector */}
<div className="flex flex-col items-center pt-0.5">
<div
className={`rounded-full p-1.5 bg-light-100 dark:bg-dark-100 text-black/70 dark:text-white/70 ${isStreaming ? 'animate-pulse' : ''}`}
>
{getStepIcon(step)}
</div>
{index < block.data.subSteps.length - 1 && (
<div className="w-0.5 flex-1 min-h-[20px] bg-light-200 dark:bg-dark-200 mt-1.5" />
)}
</div>
{/* Step content */}
<div className="flex-1 pb-1">
<span className="text-sm font-medium text-black dark:text-white">
{getStepTitle(step, isStreaming)}
</span>
{step.type === 'reasoning' && (
<>
{step.reasoning && (
<p className="text-xs text-black/70 dark:text-white/70 mt-0.5">
{step.reasoning}
</p>
)}
{isStreaming && !step.reasoning && (
<div className="flex items-center gap-1.5 mt-0.5">
<div
className="w-1.5 h-1.5 bg-black/40 dark:bg-white/40 rounded-full animate-bounce"
style={{ animationDelay: '0ms' }}
/>
<div
className="w-1.5 h-1.5 bg-black/40 dark:bg-white/40 rounded-full animate-bounce"
style={{ animationDelay: '150ms' }}
/>
<div
className="w-1.5 h-1.5 bg-black/40 dark:bg-white/40 rounded-full animate-bounce"
style={{ animationDelay: '300ms' }}
/>
</div>
)}
</>
)}
{step.type === 'searching' &&
step.searching.length > 0 && (
<div className="flex flex-wrap gap-1.5 mt-1.5">
{step.searching.map((query, idx) => (
<span
key={idx}
className="inline-flex items-center px-2 py-0.5 rounded-md text-xs font-medium bg-light-100 dark:bg-dark-100 text-black/70 dark:text-white/70 border border-light-200 dark:border-dark-200"
>
{query}
</span>
))}
</div>
)}
{step.type === 'reading' && step.reading.length > 0 && (
<div className="flex flex-wrap gap-1.5 mt-1.5">
{step.reading.slice(0, 4).map((result, idx) => {
const url = result.metadata.url || '';
const title = result.metadata.title || 'Untitled';
const domain = url ? new URL(url).hostname : '';
const faviconUrl = domain
? `https://s2.googleusercontent.com/s2/favicons?domain=${domain}&sz=128`
: '';
return (
<span
key={idx}
className="inline-flex items-center gap-1.5 px-2 py-0.5 rounded-md text-xs font-medium bg-light-100 dark:bg-dark-100 text-black/70 dark:text-white/70 border border-light-200 dark:border-dark-200"
>
{faviconUrl && (
<img
src={faviconUrl}
alt=""
className="w-3 h-3 rounded-sm flex-shrink-0"
onError={(e) => {
e.currentTarget.style.display = 'none';
}}
/>
)}
<span className="line-clamp-1">{title}</span>
</span>
);
})}
</div>
)}
</div>
</motion.div>
);
})}
</div>
</motion.div>
)}
</AnimatePresence>
</div>
);
};
export default AssistantSteps;

View File

@@ -7,11 +7,12 @@ import MessageBoxLoading from './MessageBoxLoading';
import { useChat } from '@/lib/hooks/useChat';
const Chat = () => {
const { sections, chatTurns, loading, messageAppeared } = useChat();
const { sections, loading, messageAppeared, messages } = useChat();
const [dividerWidth, setDividerWidth] = useState(0);
const dividerRef = useRef<HTMLDivElement | null>(null);
const messageEnd = useRef<HTMLDivElement | null>(null);
const lastScrolledRef = useRef<number>(0);
useEffect(() => {
const updateDividerWidth = () => {
@@ -22,35 +23,40 @@ const Chat = () => {
updateDividerWidth();
const resizeObserver = new ResizeObserver(() => {
updateDividerWidth();
});
const currentRef = dividerRef.current;
if (currentRef) {
resizeObserver.observe(currentRef);
}
window.addEventListener('resize', updateDividerWidth);
return () => {
if (currentRef) {
resizeObserver.unobserve(currentRef);
}
resizeObserver.disconnect();
window.removeEventListener('resize', updateDividerWidth);
};
}, []);
}, [sections.length]);
useEffect(() => {
const scroll = () => {
messageEnd.current?.scrollIntoView({ behavior: 'auto' });
};
if (chatTurns.length === 1) {
document.title = `${chatTurns[0].content.substring(0, 30)} - Perplexica`;
if (messages.length === 1) {
document.title = `${messages[0].query.substring(0, 30)} - Perplexica`;
}
const messageEndBottom =
messageEnd.current?.getBoundingClientRect().bottom ?? 0;
const distanceFromMessageEnd = window.innerHeight - messageEndBottom;
if (distanceFromMessageEnd >= -100) {
if (sections.length > lastScrolledRef.current) {
scroll();
lastScrolledRef.current = sections.length;
}
if (chatTurns[chatTurns.length - 1]?.role === 'user') {
scroll();
}
}, [chatTurns]);
}, [messages]);
return (
<div className="flex flex-col space-y-6 pt-8 pb-44 lg:pb-32 sm:mx-4 md:mx-8">
@@ -58,7 +64,7 @@ const Chat = () => {
const isLast = i === sections.length - 1;
return (
<Fragment key={section.userMessage.messageId}>
<Fragment key={section.message.messageId}>
<MessageBox
section={section}
sectionIndex={i}

View File

@@ -1,14 +1,12 @@
'use client';
import { Document } from '@langchain/core/documents';
import Navbar from './Navbar';
import Chat from './Chat';
import EmptyChat from './EmptyChat';
import { Settings } from 'lucide-react';
import Link from 'next/link';
import NextError from 'next/error';
import { useChat } from '@/lib/hooks/useChat';
import Loader from './ui/Loader';
import SettingsButtonMobile from './Settings/SettingsButtonMobile';
import { Block, Chunk } from '@/lib/types';
export interface BaseMessage {
chatId: string;
@@ -16,20 +14,27 @@ export interface BaseMessage {
createdAt: Date;
}
export interface Message extends BaseMessage {
backendId: string;
query: string;
responseBlocks: Block[];
status: 'answering' | 'completed' | 'error';
}
export interface UserMessage extends BaseMessage {
role: 'user';
content: string;
}
export interface AssistantMessage extends BaseMessage {
role: 'assistant';
content: string;
suggestions?: string[];
}
export interface UserMessage extends BaseMessage {
role: 'user';
content: string;
}
export interface SourceMessage extends BaseMessage {
role: 'source';
sources: Document[];
sources: Chunk[];
}
export interface SuggestionMessage extends BaseMessage {
@@ -37,11 +42,12 @@ export interface SuggestionMessage extends BaseMessage {
suggestions: string[];
}
export type Message =
export type LegacyMessage =
| AssistantMessage
| UserMessage
| SourceMessage
| SuggestionMessage;
export type ChatTurn = UserMessage | AssistantMessage;
export interface File {
@@ -50,15 +56,18 @@ export interface File {
fileId: string;
}
export interface Widget {
widgetType: string;
params: Record<string, any>;
}
const ChatWindow = () => {
const { hasError, isReady, notFound, messages } = useChat();
const { hasError, notFound, messages } = useChat();
if (hasError) {
return (
<div className="relative">
<div className="absolute w-full flex flex-row items-center justify-end mr-5 mt-5">
<Link href="/settings">
<Settings className="cursor-pointer lg:hidden" />
</Link>
<SettingsButtonMobile />
</div>
<div className="flex flex-col items-center justify-center min-h-screen">
<p className="dark:text-white/70 text-black/70 text-sm">
@@ -69,24 +78,18 @@ const ChatWindow = () => {
);
}
return isReady ? (
notFound ? (
<NextError statusCode={404} />
) : (
<div>
{messages.length > 0 ? (
<>
<Navbar />
<Chat />
</>
) : (
<EmptyChat />
)}
</div>
)
return notFound ? (
<NextError statusCode={404} />
) : (
<div className="flex flex-row items-center justify-center min-h-screen">
<Loader />
<div>
{messages.length > 0 ? (
<>
<Navbar />
<Chat />
</>
) : (
<EmptyChat />
)}
</div>
);
};

View File

@@ -1,3 +1,6 @@
'use client';
import { useEffect, useState } from 'react';
import { Settings } from 'lucide-react';
import EmptyChatMessageInput from './EmptyChatMessageInput';
import { File } from './ChatWindow';
@@ -5,8 +8,39 @@ import Link from 'next/link';
import WeatherWidget from './WeatherWidget';
import NewsArticleWidget from './NewsArticleWidget';
import SettingsButtonMobile from '@/components/Settings/SettingsButtonMobile';
import {
getShowNewsWidget,
getShowWeatherWidget,
} from '@/lib/config/clientRegistry';
const EmptyChat = () => {
const [showWeather, setShowWeather] = useState(() =>
typeof window !== 'undefined' ? getShowWeatherWidget() : true,
);
const [showNews, setShowNews] = useState(() =>
typeof window !== 'undefined' ? getShowNewsWidget() : true,
);
useEffect(() => {
const updateWidgetVisibility = () => {
setShowWeather(getShowWeatherWidget());
setShowNews(getShowNewsWidget());
};
updateWidgetVisibility();
window.addEventListener('client-config-changed', updateWidgetVisibility);
window.addEventListener('storage', updateWidgetVisibility);
return () => {
window.removeEventListener(
'client-config-changed',
updateWidgetVisibility,
);
window.removeEventListener('storage', updateWidgetVisibility);
};
}, []);
return (
<div className="relative">
<div className="absolute w-full flex flex-row items-center justify-end mr-5 mt-5">
@@ -19,14 +53,20 @@ const EmptyChat = () => {
</h2>
<EmptyChatMessageInput />
</div>
<div className="flex flex-col w-full gap-4 mt-2 sm:flex-row sm:justify-center">
<div className="flex-1 w-full">
<WeatherWidget />
{(showWeather || showNews) && (
<div className="flex flex-col w-full gap-4 mt-2 sm:flex-row sm:justify-center">
{showWeather && (
<div className="flex-1 w-full">
<WeatherWidget />
</div>
)}
{showNews && (
<div className="flex-1 w-full">
<NewsArticleWidget />
</div>
)}
</div>
<div className="flex-1 w-full">
<NewsArticleWidget />
</div>
</div>
)}
</div>
</div>
);

View File

@@ -15,14 +15,21 @@ const Copy = ({
return (
<button
onClick={() => {
const contentToCopy = `${initialMessage}${section?.sourceMessage?.sources && section.sourceMessage.sources.length > 0 && `\n\nCitations:\n${section.sourceMessage.sources?.map((source: any, i: any) => `[${i + 1}] ${source.metadata.url}`).join(`\n`)}`}`;
const contentToCopy = `${initialMessage}${
section?.message.responseBlocks.filter((b) => b.type === 'source')
?.length > 0 &&
`\n\nCitations:\n${section.message.responseBlocks
.filter((b) => b.type === 'source')
?.map((source: any, i: any) => `[${i + 1}] ${source.metadata.url}`)
.join(`\n`)}`
}`;
navigator.clipboard.writeText(contentToCopy);
setCopied(true);
setTimeout(() => setCopied(false), 1000);
}}
className="p-2 text-black/70 dark:text-white/70 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white"
className="p-2 text-black/70 dark:text-white/70 rounded-full hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white"
>
{copied ? <Check size={18} /> : <ClipboardList size={18} />}
{copied ? <Check size={16} /> : <ClipboardList size={16} />}
</button>
);
};

View File

@@ -1,4 +1,4 @@
import { ArrowLeftRight } from 'lucide-react';
import { ArrowLeftRight, Repeat } from 'lucide-react';
const Rewrite = ({
rewrite,
@@ -10,12 +10,11 @@ const Rewrite = ({
return (
<button
onClick={() => rewrite(messageId)}
className="py-2 px-3 text-black/70 dark:text-white/70 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white flex flex-row items-center space-x-1"
className="p-2 text-black/70 dark:text-white/70 rounded-full hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white flex flex-row items-center space-x-1"
>
<ArrowLeftRight size={18} />
<p className="text-xs font-medium">Rewrite</p>
<Repeat size={16} />
</button>
);
};
1;
export default Rewrite;

View File

@@ -10,6 +10,7 @@ import {
StopCircle,
Layers3,
Plus,
CornerDownRight,
} from 'lucide-react';
import Markdown, { MarkdownToJSX } from 'markdown-to-jsx';
import Copy from './MessageActions/Copy';
@@ -21,6 +22,9 @@ import { useSpeech } from 'react-text-to-speech';
import ThinkBox from './ThinkBox';
import { useChat, Section } from '@/lib/hooks/useChat';
import Citation from './Citation';
import AssistantSteps from './AssistantSteps';
import { ResearchBlock } from '@/lib/types';
import Renderer from './Widgets/Renderer';
const ThinkTagProcessor = ({
children,
@@ -45,12 +49,21 @@ const MessageBox = ({
dividerRef?: MutableRefObject<HTMLDivElement | null>;
isLast: boolean;
}) => {
const { loading, chatTurns, sendMessage, rewrite } = useChat();
const { loading, sendMessage, rewrite, messages, researchEnded } = useChat();
const parsedMessage = section.parsedAssistantMessage || '';
const parsedMessage = section.parsedTextBlocks.join('\n\n');
const speechMessage = section.speechMessage || '';
const thinkingEnded = section.thinkingEnded;
const sourceBlocks = section.message.responseBlocks.filter(
(block): block is typeof block & { type: 'source' } =>
block.type === 'source',
);
const sources = sourceBlocks.flatMap((block) => block.data);
const hasContent = section.parsedTextBlocks.length > 0;
const { speechStatus, start, stop } = useSpeech({ text: speechMessage });
const markdownOverrides: MarkdownToJSX.Options = {
@@ -71,7 +84,7 @@ const MessageBox = ({
<div className="space-y-6">
<div className={'w-full pt-8 break-words'}>
<h2 className="text-black dark:text-white font-medium text-3xl lg:w-9/12">
{section.userMessage.content}
{section.message.query}
</h2>
</div>
@@ -80,21 +93,50 @@ const MessageBox = ({
ref={dividerRef}
className="flex flex-col space-y-6 w-full lg:w-9/12"
>
{section.sourceMessage &&
section.sourceMessage.sources.length > 0 && (
<div className="flex flex-col space-y-2">
<div className="flex flex-row items-center space-x-2">
<BookCopy className="text-black dark:text-white" size={20} />
<h3 className="text-black dark:text-white font-medium text-xl">
Sources
</h3>
</div>
<MessageSources sources={section.sourceMessage.sources} />
{sources.length > 0 && (
<div className="flex flex-col space-y-2">
<div className="flex flex-row items-center space-x-2">
<BookCopy className="text-black dark:text-white" size={20} />
<h3 className="text-black dark:text-white font-medium text-xl">
Sources
</h3>
</div>
<MessageSources sources={sources} />
</div>
)}
{section.message.responseBlocks
.filter(
(block): block is ResearchBlock =>
block.type === 'research' && block.data.subSteps.length > 0,
)
.map((researchBlock) => (
<div key={researchBlock.id} className="flex flex-col space-y-2">
<AssistantSteps
block={researchBlock}
status={section.message.status}
/>
</div>
))}
{section.widgets.length > 0 && <Renderer widgets={section.widgets} />}
{isLast &&
loading &&
!researchEnded &&
!section.message.responseBlocks.some(
(b) => b.type === 'research' && b.data.subSteps.length > 0,
) && (
<div className="flex items-center gap-2 p-3 rounded-lg bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200">
<Disc3 className="w-4 h-4 text-black dark:text-white animate-spin" />
<span className="text-sm text-black/70 dark:text-white/70">
Brainstorming...
</span>
</div>
)}
<div className="flex flex-col space-y-2">
{section.sourceMessage && (
{sources.length > 0 && (
<div className="flex flex-row items-center space-x-2">
<Disc3
className={cn(
@@ -109,7 +151,7 @@ const MessageBox = ({
</div>
)}
{section.assistantMessage && (
{hasContent && (
<>
<Markdown
className={cn(
@@ -122,18 +164,15 @@ const MessageBox = ({
</Markdown>
{loading && isLast ? null : (
<div className="flex flex-row items-center justify-between w-full text-black dark:text-white py-4 -mx-2">
<div className="flex flex-row items-center space-x-1">
<div className="flex flex-row items-center justify-between w-full text-black dark:text-white py-4">
<div className="flex flex-row items-center -ml-2">
<Rewrite
rewrite={rewrite}
messageId={section.assistantMessage.messageId}
messageId={section.message.messageId}
/>
</div>
<div className="flex flex-row items-center space-x-1">
<Copy
initialMessage={section.assistantMessage.content}
section={section}
/>
<div className="flex flex-row items-center -mr-2">
<Copy initialMessage={parsedMessage} section={section} />
<button
onClick={() => {
if (speechStatus === 'started') {
@@ -142,12 +181,12 @@ const MessageBox = ({
start();
}
}}
className="p-2 text-black/70 dark:text-white/70 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white"
className="p-2 text-black/70 dark:text-white/70 rounded-full hover:bg-light-secondary dark:hover:bg-dark-secondary transition duration-200 hover:text-black dark:hover:text-white"
>
{speechStatus === 'started' ? (
<StopCircle size={18} />
<StopCircle size={16} />
) : (
<Volume2 size={18} />
<Volume2 size={16} />
)}
</button>
</div>
@@ -157,9 +196,9 @@ const MessageBox = ({
{isLast &&
section.suggestions &&
section.suggestions.length > 0 &&
section.assistantMessage &&
hasContent &&
!loading && (
<div className="mt-8 pt-6 border-t border-light-200/50 dark:border-dark-200/50">
<div className="mt-6">
<div className="flex flex-row items-center space-x-2 mb-4">
<Layers3
className="text-black dark:text-white"
@@ -173,20 +212,24 @@ const MessageBox = ({
{section.suggestions.map(
(suggestion: string, i: number) => (
<div key={i}>
{i > 0 && (
<div className="h-px bg-light-200/40 dark:bg-dark-200/40 mx-3" />
)}
<div className="h-px bg-light-200/40 dark:bg-dark-200/40" />
<button
onClick={() => sendMessage(suggestion)}
className="group w-full px-3 py-4 text-left transition-colors duration-200"
className="group w-full py-4 text-left transition-colors duration-200"
>
<div className="flex items-center justify-between gap-3">
<p className="text-sm text-black/70 dark:text-white/70 group-hover:text-[#24A0ED] transition-colors duration-200 leading-relaxed">
{suggestion}
</p>
<div className="flex flex-row space-x-3 items-center ">
<CornerDownRight
size={17}
className="group-hover:text-sky-400 transition-colors duration-200"
/>
<p className="text-sm text-black/70 dark:text-white/70 group-hover:text-sky-400 transition-colors duration-200 leading-relaxed">
{suggestion}
</p>
</div>
<Plus
size={16}
className="text-black/40 dark:text-white/40 group-hover:text-[#24A0ED] transition-colors duration-200 flex-shrink-0"
className="text-black/40 dark:text-white/40 group-hover:text-sky-400 transition-colors duration-200 flex-shrink-0"
/>
</div>
</button>
@@ -201,17 +244,17 @@ const MessageBox = ({
</div>
</div>
{section.assistantMessage && (
{hasContent && (
<div className="lg:sticky lg:top-20 flex flex-col items-center space-y-3 w-full lg:w-3/12 z-30 h-full pb-4">
<SearchImages
query={section.userMessage.content}
chatHistory={chatTurns.slice(0, sectionIndex * 2)}
messageId={section.assistantMessage.messageId}
query={section.message.query}
chatHistory={messages}
messageId={section.message.messageId}
/>
<SearchVideos
chatHistory={chatTurns.slice(0, sectionIndex * 2)}
query={section.userMessage.content}
messageId={section.assistantMessage.messageId}
chatHistory={messages}
query={section.message.query}
messageId={section.message.messageId}
/>
</div>
)}

View File

@@ -8,17 +8,16 @@ import {
PopoverPanel,
Transition,
} from '@headlessui/react';
import { Fragment, useEffect, useState } from 'react';
import { Fragment, useEffect, useMemo, useState } from 'react';
import { MinimalProvider } from '@/lib/models/types';
import { useChat } from '@/lib/hooks/useChat';
const ModelSelector = () => {
const [providers, setProviders] = useState<MinimalProvider[]>([]);
const [isLoading, setIsLoading] = useState(true);
const [searchQuery, setSearchQuery] = useState('');
const [selectedModel, setSelectedModel] = useState<{
providerId: string;
modelKey: string;
} | null>(null);
const { setChatModelProvider, chatModelProvider } = useChat();
useEffect(() => {
const loadProviders = async () => {
@@ -30,28 +29,8 @@ const ModelSelector = () => {
throw new Error('Failed to fetch providers');
}
const data = await res.json();
setProviders(data.providers || []);
const savedProviderId = localStorage.getItem('chatModelProviderId');
const savedModelKey = localStorage.getItem('chatModelKey');
if (savedProviderId && savedModelKey) {
setSelectedModel({
providerId: savedProviderId,
modelKey: savedModelKey,
});
} else if (data.providers && data.providers.length > 0) {
const firstProvider = data.providers.find(
(p: MinimalProvider) => p.chatModels.length > 0,
);
if (firstProvider && firstProvider.chatModels[0]) {
setSelectedModel({
providerId: firstProvider.id,
modelKey: firstProvider.chatModels[0].key,
});
}
}
const data: { providers: MinimalProvider[] } = await res.json();
setProviders(data.providers);
} catch (error) {
console.error('Error loading providers:', error);
} finally {
@@ -62,13 +41,32 @@ const ModelSelector = () => {
loadProviders();
}, []);
const orderedProviders = useMemo(() => {
if (!chatModelProvider?.providerId) return providers;
const currentProviderIndex = providers.findIndex(
(p) => p.id === chatModelProvider.providerId,
);
if (currentProviderIndex === -1) {
return providers;
}
const selectedProvider = providers[currentProviderIndex];
const remainingProviders = providers.filter(
(_, index) => index !== currentProviderIndex,
);
return [selectedProvider, ...remainingProviders];
}, [providers, chatModelProvider]);
const handleModelSelect = (providerId: string, modelKey: string) => {
setSelectedModel({ providerId, modelKey });
setChatModelProvider({ providerId, key: modelKey });
localStorage.setItem('chatModelProviderId', providerId);
localStorage.setItem('chatModelKey', modelKey);
};
const filteredProviders = providers
const filteredProviders = orderedProviders
.map((provider) => ({
...provider,
chatModels: provider.chatModels.filter(
@@ -140,15 +138,16 @@ const ModelSelector = () => {
<div className="flex flex-col px-2 py-2 space-y-0.5">
{provider.chatModels.map((model) => (
<PopoverButton
<button
key={model.key}
onClick={() =>
handleModelSelect(provider.id, model.key)
}
type="button"
className={cn(
'px-3 py-2 flex items-center justify-between text-start duration-200 cursor-pointer transition rounded-lg group',
selectedModel?.providerId === provider.id &&
selectedModel?.modelKey === model.key
chatModelProvider?.providerId === provider.id &&
chatModelProvider?.key === model.key
? 'bg-light-secondary dark:bg-dark-secondary'
: 'hover:bg-light-secondary dark:hover:bg-dark-secondary',
)}
@@ -158,8 +157,9 @@ const ModelSelector = () => {
size={15}
className={cn(
'shrink-0',
selectedModel?.providerId === provider.id &&
selectedModel?.modelKey === model.key
chatModelProvider?.providerId ===
provider.id &&
chatModelProvider?.key === model.key
? 'text-sky-500'
: 'text-black/50 dark:text-white/50 group-hover:text-black/70 group-hover:dark:text-white/70',
)}
@@ -167,8 +167,9 @@ const ModelSelector = () => {
<p
className={cn(
'text-sm truncate',
selectedModel?.providerId === provider.id &&
selectedModel?.modelKey === model.key
chatModelProvider?.providerId ===
provider.id &&
chatModelProvider?.key === model.key
? 'text-sky-500 font-medium'
: 'text-black/70 dark:text-white/70 group-hover:text-black dark:group-hover:text-white',
)}
@@ -176,7 +177,7 @@ const ModelSelector = () => {
{model.name}
</p>
</div>
</PopoverButton>
</button>
))}
</div>

View File

@@ -24,7 +24,7 @@ const OptimizationModes = [
},
{
key: 'quality',
title: 'Quality (Soon)',
title: 'Quality',
description: 'Get the most thorough and accurate answer',
icon: (
<Star
@@ -75,13 +75,11 @@ const Optimization = () => {
<PopoverButton
onClick={() => setOptimizationMode(mode.key)}
key={i}
disabled={mode.key === 'quality'}
className={cn(
'p-2 rounded-lg flex flex-col items-start justify-start text-start space-y-1 duration-200 cursor-pointer transition focus:outline-none',
optimizationMode === mode.key
? 'bg-light-secondary dark:bg-dark-secondary'
: 'hover:bg-light-secondary dark:hover:bg-dark-secondary',
mode.key === 'quality' && 'opacity-50 cursor-not-allowed',
)}
>
<div className="flex flex-row items-center space-x-1 text-black dark:text-white">

View File

@@ -6,11 +6,11 @@ import {
Transition,
TransitionChild,
} from '@headlessui/react';
import { Document } from '@langchain/core/documents';
import { File } from 'lucide-react';
import { Fragment, useState } from 'react';
import { Chunk } from '@/lib/types';
const MessageSources = ({ sources }: { sources: Document[] }) => {
const MessageSources = ({ sources }: { sources: Chunk[] }) => {
const [isDialogOpen, setIsDialogOpen] = useState(false);
const closeModal = () => {

View File

@@ -11,6 +11,7 @@ import {
} from '@headlessui/react';
import jsPDF from 'jspdf';
import { useChat, Section } from '@/lib/hooks/useChat';
import { SourceBlock } from '@/lib/types';
const downloadFile = (filename: string, content: string, type: string) => {
const blob = new Blob([content], { type });
@@ -28,35 +29,41 @@ const downloadFile = (filename: string, content: string, type: string) => {
const exportAsMarkdown = (sections: Section[], title: string) => {
const date = new Date(
sections[0]?.userMessage?.createdAt || Date.now(),
sections[0].message.createdAt || Date.now(),
).toLocaleString();
let md = `# 💬 Chat Export: ${title}\n\n`;
md += `*Exported on: ${date}*\n\n---\n`;
sections.forEach((section, idx) => {
if (section.userMessage) {
md += `\n---\n`;
md += `**🧑 User**
md += `\n---\n`;
md += `**🧑 User**
`;
md += `*${new Date(section.userMessage.createdAt).toLocaleString()}*\n\n`;
md += `> ${section.userMessage.content.replace(/\n/g, '\n> ')}\n`;
}
md += `*${new Date(section.message.createdAt).toLocaleString()}*\n\n`;
md += `> ${section.message.query.replace(/\n/g, '\n> ')}\n`;
if (section.assistantMessage) {
if (section.message.responseBlocks.length > 0) {
md += `\n---\n`;
md += `**🤖 Assistant**
`;
md += `*${new Date(section.assistantMessage.createdAt).toLocaleString()}*\n\n`;
md += `> ${section.assistantMessage.content.replace(/\n/g, '\n> ')}\n`;
md += `*${new Date(section.message.createdAt).toLocaleString()}*\n\n`;
md += `> ${section.message.responseBlocks
.filter((b) => b.type === 'text')
.map((block) => block.data)
.join('\n')
.replace(/\n/g, '\n> ')}\n`;
}
const sourceResponseBlock = section.message.responseBlocks.find(
(block) => block.type === 'source',
) as SourceBlock | undefined;
if (
section.sourceMessage &&
section.sourceMessage.sources &&
section.sourceMessage.sources.length > 0
sourceResponseBlock &&
sourceResponseBlock.data &&
sourceResponseBlock.data.length > 0
) {
md += `\n**Citations:**\n`;
section.sourceMessage.sources.forEach((src: any, i: number) => {
sourceResponseBlock.data.forEach((src: any, i: number) => {
const url = src.metadata?.url || '';
md += `- [${i + 1}] [${url}](${url})\n`;
});
@@ -69,7 +76,7 @@ const exportAsMarkdown = (sections: Section[], title: string) => {
const exportAsPDF = (sections: Section[], title: string) => {
const doc = new jsPDF();
const date = new Date(
sections[0]?.userMessage?.createdAt || Date.now(),
sections[0]?.message?.createdAt || Date.now(),
).toLocaleString();
let y = 15;
const pageHeight = doc.internal.pageSize.height;
@@ -86,44 +93,38 @@ const exportAsPDF = (sections: Section[], title: string) => {
doc.setTextColor(30);
sections.forEach((section, idx) => {
if (section.userMessage) {
if (y > pageHeight - 30) {
doc.addPage();
y = 15;
}
doc.setFont('helvetica', 'bold');
doc.text('User', 10, y);
doc.setFont('helvetica', 'normal');
doc.setFontSize(10);
doc.setTextColor(120);
doc.text(
`${new Date(section.userMessage.createdAt).toLocaleString()}`,
40,
y,
);
y += 6;
doc.setTextColor(30);
doc.setFontSize(12);
const userLines = doc.splitTextToSize(section.userMessage.content, 180);
for (let i = 0; i < userLines.length; i++) {
if (y > pageHeight - 20) {
doc.addPage();
y = 15;
}
doc.text(userLines[i], 12, y);
y += 6;
}
y += 6;
doc.setDrawColor(230);
if (y > pageHeight - 10) {
doc.addPage();
y = 15;
}
doc.line(10, y, 200, y);
y += 4;
if (y > pageHeight - 30) {
doc.addPage();
y = 15;
}
doc.setFont('helvetica', 'bold');
doc.text('User', 10, y);
doc.setFont('helvetica', 'normal');
doc.setFontSize(10);
doc.setTextColor(120);
doc.text(`${new Date(section.message.createdAt).toLocaleString()}`, 40, y);
y += 6;
doc.setTextColor(30);
doc.setFontSize(12);
const userLines = doc.splitTextToSize(section.message.query, 180);
for (let i = 0; i < userLines.length; i++) {
if (y > pageHeight - 20) {
doc.addPage();
y = 15;
}
doc.text(userLines[i], 12, y);
y += 6;
}
y += 6;
doc.setDrawColor(230);
if (y > pageHeight - 10) {
doc.addPage();
y = 15;
}
doc.line(10, y, 200, y);
y += 4;
if (section.assistantMessage) {
if (section.message.responseBlocks.length > 0) {
if (y > pageHeight - 30) {
doc.addPage();
y = 15;
@@ -134,7 +135,7 @@ const exportAsPDF = (sections: Section[], title: string) => {
doc.setFontSize(10);
doc.setTextColor(120);
doc.text(
`${new Date(section.assistantMessage.createdAt).toLocaleString()}`,
`${new Date(section.message.createdAt).toLocaleString()}`,
40,
y,
);
@@ -142,7 +143,7 @@ const exportAsPDF = (sections: Section[], title: string) => {
doc.setTextColor(30);
doc.setFontSize(12);
const assistantLines = doc.splitTextToSize(
section.assistantMessage.content,
section.parsedTextBlocks.join('\n'),
180,
);
for (let i = 0; i < assistantLines.length; i++) {
@@ -154,10 +155,14 @@ const exportAsPDF = (sections: Section[], title: string) => {
y += 6;
}
const sourceResponseBlock = section.message.responseBlocks.find(
(block) => block.type === 'source',
) as SourceBlock | undefined;
if (
section.sourceMessage &&
section.sourceMessage.sources &&
section.sourceMessage.sources.length > 0
sourceResponseBlock &&
sourceResponseBlock.data &&
sourceResponseBlock.data.length > 0
) {
doc.setFontSize(11);
doc.setTextColor(80);
@@ -167,7 +172,7 @@ const exportAsPDF = (sections: Section[], title: string) => {
}
doc.text('Citations:', 12, y);
y += 5;
section.sourceMessage.sources.forEach((src: any, i: number) => {
sourceResponseBlock.data.forEach((src: any, i: number) => {
const url = src.metadata?.url || '';
if (y > pageHeight - 15) {
doc.addPage();
@@ -198,15 +203,15 @@ const Navbar = () => {
const { sections, chatId } = useChat();
useEffect(() => {
if (sections.length > 0 && sections[0].userMessage) {
if (sections.length > 0 && sections[0].message) {
const newTitle =
sections[0].userMessage.content.length > 20
? `${sections[0].userMessage.content.substring(0, 20).trim()}...`
: sections[0].userMessage.content;
sections[0].message.query.substring(0, 30) + '...' ||
'New Conversation';
setTitle(newTitle);
const newTimeAgo = formatTimeDifference(
new Date(),
sections[0].userMessage.createdAt,
sections[0].message.createdAt,
);
setTimeAgo(newTimeAgo);
}
@@ -214,10 +219,10 @@ const Navbar = () => {
useEffect(() => {
const intervalId = setInterval(() => {
if (sections.length > 0 && sections[0].userMessage) {
if (sections.length > 0 && sections[0].message) {
const newTimeAgo = formatTimeDifference(
new Date(),
sections[0].userMessage.createdAt,
sections[0].message.createdAt,
);
setTimeAgo(newTimeAgo);
}

View File

@@ -97,7 +97,7 @@ const AddModel = ({
>
<DialogPanel className="w-full mx-4 lg:w-[600px] max-h-[85vh] flex flex-col border bg-light-primary dark:bg-dark-primary border-light-secondary dark:border-dark-secondary rounded-lg">
<div className="px-6 pt-6 pb-4">
<h3 className="text-black/90 dark:text-white/90 font-medium">
<h3 className="text-black/90 dark:text-white/90 font-medium text-sm">
Add new {type === 'chat' ? 'chat' : 'embedding'} model
</h3>
</div>
@@ -115,7 +115,7 @@ const AddModel = ({
<input
value={modelName}
onChange={(e) => setModelName(e.target.value)}
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-4 py-3 text-sm text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-4 py-3 text-[13px] text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
placeholder="e.g., GPT-4"
type="text"
required
@@ -128,7 +128,7 @@ const AddModel = ({
<input
value={modelKey}
onChange={(e) => setModelKey(e.target.value)}
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-4 py-3 text-sm text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-4 py-3 text-[13px] text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
placeholder="e.g., gpt-4"
type="text"
required
@@ -140,7 +140,7 @@ const AddModel = ({
<button
type="submit"
disabled={loading}
className="px-4 py-2 rounded-lg text-sm bg-sky-500 text-white font-medium disabled:opacity-85 hover:opacity-85 active:scale-95 transition duration-200"
className="px-4 py-2 rounded-lg text-[13px] bg-sky-500 text-white font-medium disabled:opacity-85 hover:opacity-85 active:scale-95 transition duration-200"
>
{loading ? (
<Loader2 className="animate-spin" size={16} />

View File

@@ -82,10 +82,10 @@ const AddProvider = ({
setProviders((prev) => [...prev, data]);
toast.success('Provider added successfully.');
toast.success('Connection added successfully.');
} catch (error) {
console.error('Error adding provider:', error);
toast.error('Failed to add provider.');
toast.error('Failed to add connection.');
} finally {
setLoading(false);
setOpen(false);
@@ -96,10 +96,10 @@ const AddProvider = ({
<>
<button
onClick={() => setOpen(true)}
className="px-3 md:px-4 py-1.5 md:py-2 rounded-lg text-xs sm:text-sm border border-light-200 dark:border-dark-200 text-black dark:text-white bg-light-secondary/50 dark:bg-dark-secondary/50 hover:bg-light-secondary hover:dark:bg-dark-secondary hover:border-light-300 hover:dark:border-dark-300 flex flex-row items-center space-x-1 active:scale-95 transition duration-200"
className="px-3 md:px-4 py-1.5 md:py-2 rounded-lg text-xs sm:text-xs border border-light-200 dark:border-dark-200 text-black dark:text-white bg-light-secondary/50 dark:bg-dark-secondary/50 hover:bg-light-secondary hover:dark:bg-dark-secondary hover:border-light-300 hover:dark:border-dark-300 flex flex-row items-center space-x-1 active:scale-95 transition duration-200"
>
<Plus className="w-3.5 h-3.5 md:w-4 md:h-4" />
<span>Add Provider</span>
<span>Add Connection</span>
</button>
<AnimatePresence>
{open && (
@@ -119,8 +119,8 @@ const AddProvider = ({
<DialogPanel className="w-full mx-4 lg:w-[600px] max-h-[85vh] flex flex-col border bg-light-primary dark:bg-dark-primary border-light-secondary dark:border-dark-secondary rounded-lg">
<form onSubmit={handleSubmit} className="flex flex-col flex-1">
<div className="px-6 pt-6 pb-4">
<h3 className="text-black/90 dark:text-white/90 font-medium">
Add new provider
<h3 className="text-black/90 dark:text-white/90 font-medium text-sm">
Add new connection
</h3>
</div>
<div className="border-t border-light-200 dark:border-dark-200" />
@@ -128,7 +128,7 @@ const AddProvider = ({
<div className="flex flex-col space-y-4">
<div className="flex flex-col items-start space-y-2">
<label className="text-xs text-black/70 dark:text-white/70">
Select provider type
Select connection type
</label>
<Select
value={selectedProvider ?? ''}
@@ -149,13 +149,13 @@ const AddProvider = ({
className="flex flex-col items-start space-y-2"
>
<label className="text-xs text-black/70 dark:text-white/70">
Name*
Connection Name*
</label>
<input
value={name}
onChange={(e) => setName(e.target.value)}
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-4 py-3 pr-10 text-sm text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
placeholder={'Provider Name'}
placeholder={'e.g., My OpenAI Connection'}
type="text"
required={true}
/>
@@ -178,7 +178,7 @@ const AddProvider = ({
[field.key]: event.target.value,
}))
}
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-4 py-3 pr-10 text-sm text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-4 py-3 pr-10 text-[13px] text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
placeholder={
(field as StringUIConfigField).placeholder
}
@@ -194,12 +194,12 @@ const AddProvider = ({
<button
type="submit"
disabled={loading}
className="px-4 py-2 rounded-lg text-sm bg-sky-500 text-white font-medium disabled:opacity-85 hover:opacity-85 active:scale-95 transition duration-200"
className="px-4 py-2 rounded-lg text-[13px] bg-sky-500 text-white font-medium disabled:opacity-85 hover:opacity-85 active:scale-95 transition duration-200"
>
{loading ? (
<Loader2 className="animate-spin" size={16} />
) : (
'Add Provider'
'Add Connection'
)}
</button>
</div>

View File

@@ -34,10 +34,10 @@ const DeleteProvider = ({
return prev.filter((p) => p.id !== modelProvider.id);
});
toast.success('Provider deleted successfully.');
toast.success('Connection deleted successfully.');
} catch (error) {
console.error('Error deleting provider:', error);
toast.error('Failed to delete provider.');
toast.error('Failed to delete connection.');
} finally {
setLoading(false);
}
@@ -51,7 +51,7 @@ const DeleteProvider = ({
setOpen(true);
}}
className="group p-1.5 rounded-md hover:bg-light-200 hover:dark:bg-dark-200 transition-colors group"
title="Delete provider"
title="Delete connection"
>
<Trash2
size={14}
@@ -76,14 +76,15 @@ const DeleteProvider = ({
<DialogPanel className="w-full mx-4 lg:w-[600px] max-h-[85vh] flex flex-col border bg-light-primary dark:bg-dark-primary border-light-secondary dark:border-dark-secondary rounded-lg">
<div className="px-6 pt-6 pb-4">
<h3 className="text-black/90 dark:text-white/90 font-medium">
Delete provider
Delete connection
</h3>
</div>
<div className="border-t border-light-200 dark:border-dark-200" />
<div className="flex-1 overflow-y-auto px-6 py-4">
<p className="text-SM text-black/60 dark:text-white/60">
Are you sure you want to delete the provider &quot;
<p className="text-sm text-black/60 dark:text-white/60">
Are you sure you want to delete the connection &quot;
{modelProvider.name}&quot;? This action cannot be undone.
All associated models will also be removed.
</p>
</div>
<div className="px-6 py-6 flex justify-end space-x-2">

View File

@@ -1,7 +1,7 @@
import { UIConfigField, ConfigModelProvider } from '@/lib/config/types';
import { cn } from '@/lib/utils';
import { AnimatePresence, motion } from 'framer-motion';
import { AlertCircle, ChevronDown, Pencil, Trash2, X } from 'lucide-react';
import { AlertCircle, Plug2, Plus, Pencil, Trash2, X } from 'lucide-react';
import { useState } from 'react';
import { toast } from 'sonner';
import AddModel from './AddModelDialog';
@@ -17,7 +17,7 @@ const ModelProvider = ({
fields: UIConfigField[];
setProviders: React.Dispatch<React.SetStateAction<ConfigModelProvider[]>>;
}) => {
const [open, setOpen] = useState(false);
const [open, setOpen] = useState(true);
const handleModelDelete = async (
type: 'chat' | 'embedding',
@@ -66,150 +66,157 @@ const ModelProvider = ({
}
};
const modelCount =
modelProvider.chatModels.filter((m) => m.key !== 'error').length +
modelProvider.embeddingModels.filter((m) => m.key !== 'error').length;
const hasError =
modelProvider.chatModels.some((m) => m.key === 'error') ||
modelProvider.embeddingModels.some((m) => m.key === 'error');
return (
<div
key={modelProvider.id}
className="border border-light-200 dark:border-dark-200 rounded-lg overflow-hidden"
className="border border-light-200 dark:border-dark-200 rounded-lg overflow-hidden bg-light-primary dark:bg-dark-primary"
>
<div
className={cn(
'group px-5 py-4 flex flex-row justify-between w-full cursor-pointer hover:bg-light-secondary hover:dark:bg-dark-secondary transition duration-200 items-center',
!open && 'rounded-lg',
)}
onClick={() => setOpen(!open)}
>
<p className="text-sm lg:text-base text-black dark:text-white font-medium">
{modelProvider.name}
</p>
<div className="flex items-center gap-4">
<div className="flex flex-row items-center">
<UpdateProvider
fields={fields}
modelProvider={modelProvider}
setProviders={setProviders}
/>
<DeleteProvider
modelProvider={modelProvider}
setProviders={setProviders}
/>
<div className="px-5 py-3.5 flex flex-row justify-between w-full items-center border-b border-light-200 dark:border-dark-200 bg-light-secondary/30 dark:bg-dark-secondary/30">
<div className="flex items-center gap-2.5">
<div className="p-1.5 rounded-md bg-sky-500/10 dark:bg-sky-500/10">
<Plug2 size={14} className="text-sky-500" />
</div>
<ChevronDown
size={16}
className={cn(
open ? 'rotate-180' : '',
'transition duration-200 text-black/70 dark:text-white/70 group-hover:text-sky-500',
<div className="flex flex-col">
<p className="text-sm lg:text-sm text-black dark:text-white font-medium">
{modelProvider.name}
</p>
{modelCount > 0 && (
<p className="text-[10px] lg:text-[11px] text-black/50 dark:text-white/50">
{modelCount} model{modelCount !== 1 ? 's' : ''} configured
</p>
)}
</div>
</div>
<div className="flex flex-row items-center gap-1">
<UpdateProvider
fields={fields}
modelProvider={modelProvider}
setProviders={setProviders}
/>
<DeleteProvider
modelProvider={modelProvider}
setProviders={setProviders}
/>
</div>
</div>
<AnimatePresence>
{open && (
<motion.div
initial={{ height: 0, opacity: 0 }}
animate={{ height: 'auto', opacity: 1 }}
exit={{ height: 0, opacity: 0 }}
transition={{ duration: 0.1 }}
>
<div className="border-t border-light-200 dark:border-dark-200" />
<div className="flex flex-col gap-y-4 px-5 py-4">
{modelProvider.chatModels.length > 0 && (
<div className="flex flex-col gap-y-2">
<div className="flex flex-row w-full justify-between items-center">
<p className="text-[11px] lg:text-xs text-black/70 dark:text-white/70">
Chat models
</p>
<AddModel
providerId={modelProvider.id}
setProviders={setProviders}
type="chat"
/>
<div className="flex flex-col gap-y-4 px-5 py-4">
<div className="flex flex-col gap-y-2">
<div className="flex flex-row w-full justify-between items-center">
<p className="text-[11px] lg:text-[11px] font-medium text-black/70 dark:text-white/70 uppercase tracking-wide">
Chat Models
</p>
{!modelProvider.chatModels.some((m) => m.key === 'error') && (
<AddModel
providerId={modelProvider.id}
setProviders={setProviders}
type="chat"
/>
)}
</div>
<div className="flex flex-col gap-2">
{modelProvider.chatModels.some((m) => m.key === 'error') ? (
<div className="flex flex-row items-center gap-2 text-xs lg:text-xs text-red-500 dark:text-red-400 rounded-lg bg-red-50 dark:bg-red-950/20 px-3 py-2 border border-red-200 dark:border-red-900/30">
<AlertCircle size={16} className="shrink-0" />
<span className="break-words">
{
modelProvider.chatModels.find((m) => m.key === 'error')
?.name
}
</span>
</div>
) : modelProvider.chatModels.filter((m) => m.key !== 'error')
.length === 0 && !hasError ? (
<div className="flex flex-col items-center justify-center py-4 px-4 rounded-lg border-2 border-dashed border-light-200 dark:border-dark-200 bg-light-secondary/20 dark:bg-dark-secondary/20">
<p className="text-xs text-black/50 dark:text-white/50 text-center">
No chat models configured
</p>
</div>
) : modelProvider.chatModels.filter((m) => m.key !== 'error')
.length > 0 ? (
<div className="flex flex-row flex-wrap gap-2">
{modelProvider.chatModels.map((model, index) => (
<div
key={`${modelProvider.id}-chat-${model.key}-${index}`}
className="flex flex-row items-center space-x-1.5 text-xs lg:text-xs text-black/70 dark:text-white/70 rounded-lg bg-light-secondary dark:bg-dark-secondary px-3 py-1.5 border border-light-200 dark:border-dark-200"
>
<span>{model.name}</span>
<button
onClick={() => {
handleModelDelete('chat', model.key);
}}
className="hover:text-red-500 dark:hover:text-red-400 transition-colors"
>
<X size={12} />
</button>
</div>
<div className="flex flex-col gap-2">
{modelProvider.chatModels.some((m) => m.key === 'error') ? (
<div className="flex flex-row items-center gap-2 text-xs lg:text-sm text-red-500 dark:text-red-400 rounded-lg bg-red-50 dark:bg-red-950/20 px-3 py-2 border border-red-200 dark:border-red-900/30">
<AlertCircle size={16} className="shrink-0" />
<span className="break-words">
{
modelProvider.chatModels.find(
(m) => m.key === 'error',
)?.name
}
</span>
</div>
) : (
<div className="flex flex-row flex-wrap gap-2">
{modelProvider.chatModels.map((model, index) => (
<div
key={`${modelProvider.id}-chat-${model.key}-${index}`}
className="flex flex-row items-center space-x-1 text-xs lg:text-sm text-black/70 dark:text-white/70 rounded-lg bg-light-secondary dark:bg-dark-secondary px-3 py-1.5"
>
<span>{model.name}</span>
<button
onClick={() => {
handleModelDelete('chat', model.key);
}}
>
<X size={12} />
</button>
</div>
))}
</div>
)}
))}
</div>
) : null}
</div>
</div>
<div className="flex flex-col gap-y-2">
<div className="flex flex-row w-full justify-between items-center">
<p className="text-[11px] lg:text-[11px] font-medium text-black/70 dark:text-white/70 uppercase tracking-wide">
Embedding Models
</p>
{!modelProvider.embeddingModels.some((m) => m.key === 'error') && (
<AddModel
providerId={modelProvider.id}
setProviders={setProviders}
type="embedding"
/>
)}
</div>
<div className="flex flex-col gap-2">
{modelProvider.embeddingModels.some((m) => m.key === 'error') ? (
<div className="flex flex-row items-center gap-2 text-xs lg:text-xs text-red-500 dark:text-red-400 rounded-lg bg-red-50 dark:bg-red-950/20 px-3 py-2 border border-red-200 dark:border-red-900/30">
<AlertCircle size={16} className="shrink-0" />
<span className="break-words">
{
modelProvider.embeddingModels.find((m) => m.key === 'error')
?.name
}
</span>
</div>
) : modelProvider.embeddingModels.filter((m) => m.key !== 'error')
.length === 0 && !hasError ? (
<div className="flex flex-col items-center justify-center py-4 px-4 rounded-lg border-2 border-dashed border-light-200 dark:border-dark-200 bg-light-secondary/20 dark:bg-dark-secondary/20">
<p className="text-xs text-black/50 dark:text-white/50 text-center">
No embedding models configured
</p>
</div>
) : modelProvider.embeddingModels.filter((m) => m.key !== 'error')
.length > 0 ? (
<div className="flex flex-row flex-wrap gap-2">
{modelProvider.embeddingModels.map((model, index) => (
<div
key={`${modelProvider.id}-embedding-${model.key}-${index}`}
className="flex flex-row items-center space-x-1.5 text-xs lg:text-xs text-black/70 dark:text-white/70 rounded-lg bg-light-secondary dark:bg-dark-secondary px-3 py-1.5 border border-light-200 dark:border-dark-200"
>
<span>{model.name}</span>
<button
onClick={() => {
handleModelDelete('embedding', model.key);
}}
className="hover:text-red-500 dark:hover:text-red-400 transition-colors"
>
<X size={12} />
</button>
</div>
</div>
)}
{modelProvider.embeddingModels.length > 0 && (
<div className="flex flex-col gap-y-2">
<div className="flex flex-row w-full justify-between items-center">
<p className="text-[11px] lg:text-xs text-black/70 dark:text-white/70">
Embedding models
</p>
<AddModel
providerId={modelProvider.id}
setProviders={setProviders}
type="embedding"
/>
</div>
<div className="flex flex-col gap-2">
{modelProvider.embeddingModels.some(
(m) => m.key === 'error',
) ? (
<div className="flex flex-row items-center gap-2 text-xs lg:text-sm text-red-500 dark:text-red-400 rounded-lg bg-red-50 dark:bg-red-950/20 px-3 py-2 border border-red-200 dark:border-red-900/30">
<AlertCircle size={16} className="shrink-0" />
<span className="break-words">
{
modelProvider.embeddingModels.find(
(m) => m.key === 'error',
)?.name
}
</span>
</div>
) : (
<div className="flex flex-row flex-wrap gap-2">
{modelProvider.embeddingModels.map((model, index) => (
<div
key={`${modelProvider.id}-embedding-${model.key}-${index}`}
className="flex flex-row items-center space-x-1 text-xs lg:text-sm text-black/70 dark:text-white/70 rounded-lg bg-light-secondary dark:bg-dark-secondary px-3 py-1.5"
>
<span>{model.name}</span>
<button
onClick={() => {
handleModelDelete('embedding', model.key);
}}
>
<X size={12} />
</button>
</div>
))}
</div>
)}
</div>
</div>
)}
</div>
</motion.div>
)}
</AnimatePresence>
))}
</div>
) : null}
</div>
</div>
</div>
</div>
);
};

View File

@@ -1,5 +1,6 @@
import Select from '@/components/ui/Select';
import { ConfigModelProvider } from '@/lib/config/types';
import { useChat } from '@/lib/hooks/useChat';
import { useState } from 'react';
import { toast } from 'sonner';
@@ -11,30 +12,40 @@ const ModelSelect = ({
type: 'chat' | 'embedding';
}) => {
const [selectedModel, setSelectedModel] = useState<string>(
`${providers[0]?.id}/${providers[0].embeddingModels[0]?.key}`,
type === 'chat'
? `${localStorage.getItem('chatModelProviderId')}/${localStorage.getItem('chatModelKey')}`
: `${localStorage.getItem('embeddingModelProviderId')}/${localStorage.getItem('embeddingModelKey')}`,
);
const [loading, setLoading] = useState(false);
const { setChatModelProvider, setEmbeddingModelProvider } = useChat();
const handleSave = async (newValue: string) => {
setLoading(true);
setSelectedModel(newValue);
console.log(newValue);
try {
if (type === 'chat') {
localStorage.setItem('chatModelProviderId', newValue.split('/')[0]);
localStorage.setItem(
'chatModelKey',
newValue.split('/').slice(1).join('/'),
);
const providerId = newValue.split('/')[0];
const modelKey = newValue.split('/').slice(1).join('/');
localStorage.setItem('chatModelProviderId', providerId);
localStorage.setItem('chatModelKey', modelKey);
setChatModelProvider({
providerId: providerId,
key: modelKey,
});
} else {
localStorage.setItem(
'embeddingModelProviderId',
newValue.split('/')[0],
);
localStorage.setItem(
'embeddingModelKey',
newValue.split('/').slice(1).join('/'),
);
const providerId = newValue.split('/')[0];
const modelKey = newValue.split('/').slice(1).join('/');
localStorage.setItem('embeddingModelProviderId', providerId);
localStorage.setItem('embeddingModelKey', modelKey);
setEmbeddingModelProvider({
providerId: providerId,
key: modelKey,
});
}
} catch (error) {
console.error('Error saving config:', error);
@@ -48,13 +59,13 @@ const ModelSelect = ({
<section className="rounded-xl border border-light-200 bg-light-primary/80 p-4 lg:p-6 transition-colors dark:border-dark-200 dark:bg-dark-primary/80">
<div className="space-y-3 lg:space-y-5">
<div>
<h4 className="text-sm lg:text-base text-black dark:text-white">
<h4 className="text-sm lg:text-sm text-black dark:text-white">
Select {type === 'chat' ? 'Chat Model' : 'Embedding Model'}
</h4>
<p className="text-[11px] lg:text-xs text-black/50 dark:text-white/50">
{type === 'chat'
? 'Select the model to use for chat responses'
: 'Select the model to use for embeddings'}
? 'Choose which model to use for generating responses'
: 'Choose which model to use for generating embeddings'}
</p>
</div>
<Select
@@ -75,7 +86,7 @@ const ModelSelect = ({
})),
)
}
className="!text-xs lg:!text-sm"
className="!text-xs lg:!text-[13px]"
loading={loading}
disabled={loading}
/>

View File

@@ -20,7 +20,7 @@ const Models = ({
return (
<div className="flex-1 space-y-6 overflow-y-auto py-6">
<div className="flex flex-col px-6 gap-y-4">
<h3 className="text-xs lg:text-sm text-black/70 dark:text-white/70">
<h3 className="text-xs lg:text-xs text-black/70 dark:text-white/70">
Select models
</h3>
<ModelSelect
@@ -38,23 +38,51 @@ const Models = ({
</div>
<div className="border-t border-light-200 dark:border-dark-200" />
<div className="flex flex-row justify-between items-center px-6 ">
<p className="text-xs lg:text-sm text-black/70 dark:text-white/70">
Manage model provider
<p className="text-xs lg:text-xs text-black/70 dark:text-white/70">
Manage connections
</p>
<AddProvider modelProviders={fields} setProviders={setProviders} />
</div>
<div className="flex flex-col px-6 gap-y-4">
{providers.map((provider) => (
<ModelProvider
key={`provider-${provider.id}`}
fields={
(fields.find((f) => f.key === provider.type)?.fields ??
[]) as UIConfigField[]
}
modelProvider={provider}
setProviders={setProviders}
/>
))}
{providers.length === 0 ? (
<div className="flex flex-col items-center justify-center py-12 px-4 rounded-lg border-2 border-dashed border-light-200 dark:border-dark-200 bg-light-secondary/10 dark:bg-dark-secondary/10">
<div className="p-3 rounded-full bg-sky-500/10 dark:bg-sky-500/10 mb-3">
<svg
xmlns="http://www.w3.org/2000/svg"
className="w-8 h-8 text-sky-500"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
>
<path
strokeLinecap="round"
strokeLinejoin="round"
strokeWidth={2}
d="M13 10V3L4 14h7v7l9-11h-7z"
/>
</svg>
</div>
<p className="text-sm font-medium text-black/70 dark:text-white/70 mb-1">
No connections yet
</p>
<p className="text-xs text-black/50 dark:text-white/50 text-center max-w-sm mb-4">
Add your first connection to start using AI models. Connect to
OpenAI, Anthropic, Ollama, and more.
</p>
</div>
) : (
providers.map((provider) => (
<ModelProvider
key={`provider-${provider.id}`}
fields={
(fields.find((f) => f.key === provider.type)?.fields ??
[]) as UIConfigField[]
}
modelProvider={provider}
setProviders={setProviders}
/>
))
)}
</div>
</div>
);

View File

@@ -67,10 +67,10 @@ const UpdateProvider = ({
});
});
toast.success('Provider updated successfully.');
toast.success('Connection updated successfully.');
} catch (error) {
console.error('Error updating provider:', error);
toast.error('Failed to update provider.');
toast.error('Failed to update connection.');
} finally {
setLoading(false);
setOpen(false);
@@ -109,8 +109,8 @@ const UpdateProvider = ({
<DialogPanel className="w-full mx-4 lg:w-[600px] max-h-[85vh] flex flex-col border bg-light-primary dark:bg-dark-primary border-light-secondary dark:border-dark-secondary rounded-lg">
<form onSubmit={handleSubmit} className="flex flex-col flex-1">
<div className="px-6 pt-6 pb-4">
<h3 className="text-black/90 dark:text-white/90 font-medium">
Update provider
<h3 className="text-black/90 dark:text-white/90 font-medium text-sm">
Update connection
</h3>
</div>
<div className="border-t border-light-200 dark:border-dark-200" />
@@ -121,13 +121,13 @@ const UpdateProvider = ({
className="flex flex-col items-start space-y-2"
>
<label className="text-xs text-black/70 dark:text-white/70">
Name*
Connection Name*
</label>
<input
value={name}
onChange={(event) => setName(event.target.value)}
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-4 py-3 pr-10 text-sm text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
placeholder={'Provider Name'}
placeholder={'Connection Name'}
type="text"
required={true}
/>
@@ -150,7 +150,7 @@ const UpdateProvider = ({
[field.key]: event.target.value,
}))
}
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-4 py-3 pr-10 text-sm text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-4 py-3 pr-10 text-[13px] text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
placeholder={
(field as StringUIConfigField).placeholder
}
@@ -166,12 +166,12 @@ const UpdateProvider = ({
<button
type="submit"
disabled={loading}
className="px-4 py-2 rounded-lg text-sm bg-sky-500 text-white font-medium disabled:opacity-85 hover:opacity-85 active:scale-95 transition duration-200"
className="px-4 py-2 rounded-lg text-[13px] bg-sky-500 text-white font-medium disabled:opacity-85 hover:opacity-85 active:scale-95 transition duration-200"
>
{loading ? (
<Loader2 className="animate-spin" size={16} />
) : (
'Update Provider'
'Update Connection'
)}
</button>
</div>

View File

@@ -0,0 +1,29 @@
import { UIConfigField } from '@/lib/config/types';
import SettingsField from '../SettingsField';
const Personalization = ({
fields,
values,
}: {
fields: UIConfigField[];
values: Record<string, any>;
}) => {
return (
<div className="flex-1 space-y-6 overflow-y-auto px-6 py-6">
{fields.map((field) => (
<SettingsField
key={field.key}
field={field}
value={
(field.scope === 'client'
? localStorage.getItem(field.key)
: values[field.key]) ?? field.default
}
dataAdd="personalization"
/>
))}
</div>
);
};
export default Personalization;

View File

@@ -1,7 +1,7 @@
import { UIConfigField } from '@/lib/config/types';
import SettingsField from '../SettingsField';
const General = ({
const Preferences = ({
fields,
values,
}: {
@@ -19,11 +19,11 @@ const General = ({
? localStorage.getItem(field.key)
: values[field.key]) ?? field.default
}
dataAdd="general"
dataAdd="preferences"
/>
))}
</div>
);
};
export default General;
export default Preferences;

View File

@@ -9,7 +9,7 @@ const SettingsButtonMobile = () => {
return (
<>
<button className="lg:hidden" onClick={() => setIsOpen(true)}>
<Settings size={18}/>
<Settings size={18} />
</button>
<AnimatePresence>
{isOpen && <SettingsDialogue isOpen={isOpen} setIsOpen={setIsOpen} />}

View File

@@ -4,9 +4,10 @@ import {
BrainCog,
ChevronLeft,
Search,
Settings,
Sliders,
ToggleRight,
} from 'lucide-react';
import General from './Sections/General';
import Preferences from './Sections/Preferences';
import { motion } from 'framer-motion';
import { useEffect, useState } from 'react';
import { toast } from 'sonner';
@@ -15,20 +16,29 @@ import { cn } from '@/lib/utils';
import Models from './Sections/Models/Section';
import SearchSection from './Sections/Search';
import Select from '@/components/ui/Select';
import Personalization from './Sections/Personalization';
const sections = [
{
key: 'general',
name: 'General',
description: 'Adjust common settings.',
icon: Settings,
component: General,
dataAdd: 'general',
key: 'preferences',
name: 'Preferences',
description: 'Customize your application preferences.',
icon: Sliders,
component: Preferences,
dataAdd: 'preferences',
},
{
key: 'personalization',
name: 'Personalization',
description: 'Customize the behavior and tone of the model.',
icon: ToggleRight,
component: Personalization,
dataAdd: 'personalization',
},
{
key: 'models',
name: 'Models',
description: 'Configure model settings.',
description: 'Connect to AI services and manage connections.',
icon: BrainCog,
component: Models,
dataAdd: 'modelProviders',
@@ -166,7 +176,7 @@ const SettingsDialogue = ({
<div className="flex flex-1 flex-col overflow-hidden">
<div className="border-b border-light-200/60 px-6 pb-6 lg:pt-6 dark:border-dark-200/60 flex-shrink-0">
<div className="flex flex-col">
<h4 className="font-medium text-black dark:text-white text-sm lg:text-base">
<h4 className="font-medium text-black dark:text-white text-sm lg:text-sm">
{selectedSection.name}
</h4>
<p className="text-[11px] lg:text-xs text-black/50 dark:text-white/50">

View File

@@ -1,6 +1,7 @@
import {
SelectUIConfigField,
StringUIConfigField,
SwitchUIConfigField,
TextareaUIConfigField,
UIConfigField,
} from '@/lib/config/types';
@@ -9,6 +10,13 @@ import Select from '../ui/Select';
import { toast } from 'sonner';
import { useTheme } from 'next-themes';
import { Loader2 } from 'lucide-react';
import { Switch } from '@headlessui/react';
const emitClientConfigChanged = () => {
if (typeof window !== 'undefined') {
window.dispatchEvent(new Event('client-config-changed'));
}
};
const SettingsSelect = ({
field,
@@ -33,6 +41,7 @@ const SettingsSelect = ({
if (field.key === 'theme') {
setTheme(newValue);
}
emitClientConfigChanged();
} else {
const res = await fetch('/api/config', {
method: 'POST',
@@ -62,7 +71,7 @@ const SettingsSelect = ({
<section className="rounded-xl border border-light-200 bg-light-primary/80 p-4 lg:p-6 transition-colors dark:border-dark-200 dark:bg-dark-primary/80">
<div className="space-y-3 lg:space-y-5">
<div>
<h4 className="text-sm lg:text-base text-black dark:text-white">
<h4 className="text-sm lg:text-sm text-black dark:text-white">
{field.name}
</h4>
<p className="text-[11px] lg:text-xs text-black/50 dark:text-white/50">
@@ -104,6 +113,7 @@ const SettingsInput = ({
try {
if (field.scope === 'client') {
localStorage.setItem(field.key, newValue);
emitClientConfigChanged();
} else {
const res = await fetch('/api/config', {
method: 'POST',
@@ -133,7 +143,7 @@ const SettingsInput = ({
<section className="rounded-xl border border-light-200 bg-light-primary/80 p-4 lg:p-6 transition-colors dark:border-dark-200 dark:bg-dark-primary/80">
<div className="space-y-3 lg:space-y-5">
<div>
<h4 className="text-sm lg:text-base text-black dark:text-white">
<h4 className="text-sm lg:text-sm text-black dark:text-white">
{field.name}
</h4>
<p className="text-[11px] lg:text-xs text-black/50 dark:text-white/50">
@@ -145,7 +155,7 @@ const SettingsInput = ({
value={value ?? field.default ?? ''}
onChange={(event) => setValue(event.target.value)}
onBlur={(event) => handleSave(event.target.value)}
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-3 py-2 lg:px-4 lg:py-3 pr-10 !text-xs lg:!text-sm text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-3 py-2 lg:px-4 lg:py-3 pr-10 !text-xs lg:!text-[13px] text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
placeholder={field.placeholder}
type="text"
disabled={loading}
@@ -180,6 +190,7 @@ const SettingsTextarea = ({
try {
if (field.scope === 'client') {
localStorage.setItem(field.key, newValue);
emitClientConfigChanged();
} else {
const res = await fetch('/api/config', {
method: 'POST',
@@ -209,7 +220,7 @@ const SettingsTextarea = ({
<section className="rounded-xl border border-light-200 bg-light-primary/80 p-4 lg:p-6 transition-colors dark:border-dark-200 dark:bg-dark-primary/80">
<div className="space-y-3 lg:space-y-5">
<div>
<h4 className="text-sm lg:text-base text-black dark:text-white">
<h4 className="text-sm lg:text-sm text-black dark:text-white">
{field.name}
</h4>
<p className="text-[11px] lg:text-xs text-black/50 dark:text-white/50">
@@ -221,7 +232,7 @@ const SettingsTextarea = ({
value={value ?? field.default ?? ''}
onChange={(event) => setValue(event.target.value)}
onBlur={(event) => handleSave(event.target.value)}
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-3 py-2 lg:px-4 lg:py-3 pr-10 !text-xs lg:!text-sm text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
className="w-full rounded-lg border border-light-200 dark:border-dark-200 bg-light-primary dark:bg-dark-primary px-3 py-2 lg:px-4 lg:py-3 pr-10 !text-xs lg:!text-[13px] text-black/80 dark:text-white/80 placeholder:text-black/40 dark:placeholder:text-white/40 focus-visible:outline-none focus-visible:border-light-300 dark:focus-visible:border-dark-300 transition-colors disabled:cursor-not-allowed disabled:opacity-60"
placeholder={field.placeholder}
rows={4}
disabled={loading}
@@ -237,6 +248,80 @@ const SettingsTextarea = ({
);
};
const SettingsSwitch = ({
field,
value,
setValue,
dataAdd,
}: {
field: SwitchUIConfigField;
value?: any;
setValue: (value: any) => void;
dataAdd: string;
}) => {
const [loading, setLoading] = useState(false);
const handleSave = async (newValue: boolean) => {
setLoading(true);
setValue(newValue);
try {
if (field.scope === 'client') {
localStorage.setItem(field.key, String(newValue));
emitClientConfigChanged();
} else {
const res = await fetch('/api/config', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
key: `${dataAdd}.${field.key}`,
value: newValue,
}),
});
if (!res.ok) {
console.error('Failed to save config:', await res.text());
throw new Error('Failed to save configuration');
}
}
} catch (error) {
console.error('Error saving config:', error);
toast.error('Failed to save configuration.');
} finally {
setTimeout(() => setLoading(false), 150);
}
};
const isChecked = value === true || value === 'true';
return (
<section className="rounded-xl border border-light-200 bg-light-primary/80 p-4 lg:p-6 transition-colors dark:border-dark-200 dark:bg-dark-primary/80">
<div className="flex flex-row items-center space-x-3 lg:space-x-5 w-full justify-between">
<div>
<h4 className="text-sm lg:text-sm text-black dark:text-white">
{field.name}
</h4>
<p className="text-[11px] lg:text-xs text-black/50 dark:text-white/50">
{field.description}
</p>
</div>
<Switch
checked={isChecked}
onChange={handleSave}
disabled={loading}
className="group relative flex h-6 w-12 shrink-0 cursor-pointer rounded-full bg-white/10 p-1 duration-200 ease-in-out focus:outline-none transition-colors disabled:opacity-60 disabled:cursor-not-allowed data-[checked]:bg-sky-500"
>
<span
aria-hidden="true"
className="pointer-events-none inline-block size-4 translate-x-0 rounded-full bg-white shadow-lg ring-0 transition duration-200 ease-in-out group-data-[checked]:translate-x-6"
/>
</Switch>
</div>
</section>
);
};
const SettingsField = ({
field,
value,
@@ -276,6 +361,15 @@ const SettingsField = ({
dataAdd={dataAdd}
/>
);
case 'switch':
return (
<SettingsSwitch
field={field}
value={val}
setValue={setVal}
dataAdd={dataAdd}
/>
);
default:
return <div>Unsupported field type: {field.type}</div>;
}

View File

@@ -63,8 +63,11 @@ const SetupConfig = ({
}
};
const visibleProviders = providers.filter(
(p) => p.name.toLowerCase() !== 'transformers',
);
const hasProviders =
providers.filter((p) => p.chatModels.length > 0).length > 0;
visibleProviders.filter((p) => p.chatModels.length > 0).length > 0;
return (
<div className="w-[95vw] md:w-[80vw] lg:w-[65vw] mx-auto px-2 sm:px-4 md:px-6 flex flex-col space-y-6">
@@ -82,10 +85,10 @@ const SetupConfig = ({
<div className="flex flex-row justify-between items-center mb-4 md:mb-6 pb-3 md:pb-4 border-b border-light-200 dark:border-dark-200">
<div>
<p className="text-xs sm:text-sm font-medium text-black dark:text-white">
Manage Providers
Manage Connections
</p>
<p className="text-[10px] sm:text-xs text-black/50 dark:text-white/50 mt-0.5">
Add and configure your model providers
Add connections to access AI models
</p>
</div>
<AddProvider
@@ -101,14 +104,17 @@ const SetupConfig = ({
Loading providers...
</p>
</div>
) : providers.length === 0 ? (
) : visibleProviders.length === 0 ? (
<div className="flex flex-col items-center justify-center py-8 md:py-12 text-center">
<p className="text-xs sm:text-sm font-medium text-black/70 dark:text-white/70">
No providers configured
No connections configured
</p>
<p className="text-[10px] sm:text-xs text-black/50 dark:text-white/50 mt-1">
Click &quot;Add Connection&quot; above to get started
</p>
</div>
) : (
providers.map((provider) => (
visibleProviders.map((provider) => (
<ModelProvider
key={`provider-${provider.id}`}
fields={

View File

@@ -91,7 +91,7 @@ const WeatherWidget = () => {
setData({
temperature: data.temperature,
condition: data.condition,
location: location.city,
location: 'Mars',
humidity: data.humidity,
windSpeed: data.windSpeed,
icon: data.icon,

View File

@@ -0,0 +1,54 @@
'use client';
import { Calculator, Equal } from 'lucide-react';
type CalculationWidgetProps = {
expression: string;
result: number;
};
const Calculation = ({ expression, result }: CalculationWidgetProps) => {
return (
<div className="rounded-lg bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 overflow-hidden shadow-sm">
<div className="flex items-center gap-2 p-3 bg-light-100/50 dark:bg-dark-100/50 border-b border-light-200 dark:border-dark-200">
<div className="rounded-full p-1.5 bg-light-100 dark:bg-dark-100">
<Calculator className="w-4 h-4 text-black/70 dark:text-white/70" />
</div>
<span className="text-sm font-medium text-black dark:text-white">
Calculation
</span>
</div>
<div className="p-4 space-y-3">
<div>
<div className="flex items-center gap-1.5 mb-1.5">
<span className="text-xs text-black/50 dark:text-white/50 font-medium">
Expression
</span>
</div>
<div className="bg-light-100 dark:bg-dark-100 rounded-md p-2.5 border border-light-200 dark:border-dark-200">
<code className="text-sm text-black dark:text-white font-mono break-all">
{expression}
</code>
</div>
</div>
<div>
<div className="flex items-center gap-1.5 mb-1.5">
<Equal className="w-3.5 h-3.5 text-black/50 dark:text-white/50" />
<span className="text-xs text-black/50 dark:text-white/50 font-medium">
Result
</span>
</div>
<div className="bg-gradient-to-br from-light-100 to-light-secondary dark:from-dark-100 dark:to-dark-secondary rounded-md p-4 border-2 border-light-200 dark:border-dark-200">
<div className="text-4xl font-bold text-black dark:text-white font-mono tabular-nums">
{result.toLocaleString()}
</div>
</div>
</div>
</div>
</div>
);
};
export default Calculation;

View File

@@ -0,0 +1,76 @@
import React from 'react';
import { Widget } from '../ChatWindow';
import Weather from './Weather';
import Calculation from './Calculation';
import Stock from './Stock';
const Renderer = ({ widgets }: { widgets: Widget[] }) => {
return widgets.map((widget, index) => {
switch (widget.widgetType) {
case 'weather':
return (
<Weather
key={index}
location={widget.params.location}
current={widget.params.current}
daily={widget.params.daily}
timezone={widget.params.timezone}
/>
);
case 'calculation_result':
return (
<Calculation
expression={widget.params.expression}
result={widget.params.result}
key={index}
/>
);
case 'stock':
return (
<Stock
key={index}
symbol={widget.params.symbol}
shortName={widget.params.shortName}
longName={widget.params.longName}
exchange={widget.params.exchange}
currency={widget.params.currency}
marketState={widget.params.marketState}
regularMarketPrice={widget.params.regularMarketPrice}
regularMarketChange={widget.params.regularMarketChange}
regularMarketChangePercent={
widget.params.regularMarketChangePercent
}
regularMarketPreviousClose={
widget.params.regularMarketPreviousClose
}
regularMarketOpen={widget.params.regularMarketOpen}
regularMarketDayHigh={widget.params.regularMarketDayHigh}
regularMarketDayLow={widget.params.regularMarketDayLow}
regularMarketVolume={widget.params.regularMarketVolume}
averageDailyVolume3Month={widget.params.averageDailyVolume3Month}
marketCap={widget.params.marketCap}
fiftyTwoWeekLow={widget.params.fiftyTwoWeekLow}
fiftyTwoWeekHigh={widget.params.fiftyTwoWeekHigh}
trailingPE={widget.params.trailingPE}
forwardPE={widget.params.forwardPE}
dividendYield={widget.params.dividendYield}
earningsPerShare={widget.params.earningsPerShare}
website={widget.params.website}
postMarketPrice={widget.params.postMarketPrice}
postMarketChange={widget.params.postMarketChange}
postMarketChangePercent={widget.params.postMarketChangePercent}
preMarketPrice={widget.params.preMarketPrice}
preMarketChange={widget.params.preMarketChange}
preMarketChangePercent={widget.params.preMarketChangePercent}
chartData={widget.params.chartData}
comparisonData={widget.params.comparisonData}
error={widget.params.error}
/>
);
default:
return <div key={index}>Unknown widget type: {widget.widgetType}</div>;
}
});
};
export default Renderer;

View File

@@ -0,0 +1,517 @@
'use client';
import { Clock, ArrowUpRight, ArrowDownRight, Minus } from 'lucide-react';
import { useEffect, useRef, useState } from 'react';
import {
createChart,
ColorType,
LineStyle,
BaselineSeries,
LineSeries,
} from 'lightweight-charts';
type StockWidgetProps = {
symbol: string;
shortName: string;
longName?: string;
exchange?: string;
currency?: string;
marketState?: string;
regularMarketPrice?: number;
regularMarketChange?: number;
regularMarketChangePercent?: number;
regularMarketPreviousClose?: number;
regularMarketOpen?: number;
regularMarketDayHigh?: number;
regularMarketDayLow?: number;
regularMarketVolume?: number;
averageDailyVolume3Month?: number;
marketCap?: number;
fiftyTwoWeekLow?: number;
fiftyTwoWeekHigh?: number;
trailingPE?: number;
forwardPE?: number;
dividendYield?: number;
earningsPerShare?: number;
website?: string;
postMarketPrice?: number;
postMarketChange?: number;
postMarketChangePercent?: number;
preMarketPrice?: number;
preMarketChange?: number;
preMarketChangePercent?: number;
chartData?: {
'1D'?: { timestamps: number[]; prices: number[] } | null;
'5D'?: { timestamps: number[]; prices: number[] } | null;
'1M'?: { timestamps: number[]; prices: number[] } | null;
'3M'?: { timestamps: number[]; prices: number[] } | null;
'6M'?: { timestamps: number[]; prices: number[] } | null;
'1Y'?: { timestamps: number[]; prices: number[] } | null;
MAX?: { timestamps: number[]; prices: number[] } | null;
} | null;
comparisonData?: Array<{
ticker: string;
name: string;
chartData: {
'1D'?: { timestamps: number[]; prices: number[] } | null;
'5D'?: { timestamps: number[]; prices: number[] } | null;
'1M'?: { timestamps: number[]; prices: number[] } | null;
'3M'?: { timestamps: number[]; prices: number[] } | null;
'6M'?: { timestamps: number[]; prices: number[] } | null;
'1Y'?: { timestamps: number[]; prices: number[] } | null;
MAX?: { timestamps: number[]; prices: number[] } | null;
};
}> | null;
error?: string;
};
const formatNumber = (num: number | undefined, decimals = 2): string => {
if (num === undefined || num === null) return 'N/A';
return num.toLocaleString(undefined, {
minimumFractionDigits: decimals,
maximumFractionDigits: decimals,
});
};
const formatLargeNumber = (num: number | undefined): string => {
if (num === undefined || num === null) return 'N/A';
if (num >= 1e12) return `$${(num / 1e12).toFixed(2)}T`;
if (num >= 1e9) return `$${(num / 1e9).toFixed(2)}B`;
if (num >= 1e6) return `$${(num / 1e6).toFixed(2)}M`;
if (num >= 1e3) return `$${(num / 1e3).toFixed(2)}K`;
return `$${num.toFixed(2)}`;
};
const Stock = (props: StockWidgetProps) => {
const [isDarkMode, setIsDarkMode] = useState(false);
const [selectedTimeframe, setSelectedTimeframe] = useState<
'1D' | '5D' | '1M' | '3M' | '6M' | '1Y' | 'MAX'
>('1M');
const chartContainerRef = useRef<HTMLDivElement>(null);
useEffect(() => {
const checkDarkMode = () => {
setIsDarkMode(document.documentElement.classList.contains('dark'));
};
checkDarkMode();
const observer = new MutationObserver(checkDarkMode);
observer.observe(document.documentElement, {
attributes: true,
attributeFilter: ['class'],
});
return () => observer.disconnect();
}, []);
useEffect(() => {
const currentChartData = props.chartData?.[selectedTimeframe];
if (
!chartContainerRef.current ||
!currentChartData ||
currentChartData.timestamps.length === 0
) {
return;
}
const chart = createChart(chartContainerRef.current, {
width: chartContainerRef.current.clientWidth,
height: 280,
layout: {
background: { type: ColorType.Solid, color: 'transparent' },
textColor: isDarkMode ? '#6b7280' : '#9ca3af',
fontSize: 11,
attributionLogo: false,
},
grid: {
vertLines: {
color: isDarkMode ? '#21262d' : '#e8edf1',
style: LineStyle.Solid,
},
horzLines: {
color: isDarkMode ? '#21262d' : '#e8edf1',
style: LineStyle.Solid,
},
},
crosshair: {
vertLine: {
color: isDarkMode ? '#30363d' : '#d0d7de',
labelVisible: false,
},
horzLine: {
color: isDarkMode ? '#30363d' : '#d0d7de',
labelVisible: true,
},
},
rightPriceScale: {
borderVisible: false,
visible: false,
},
leftPriceScale: {
borderVisible: false,
visible: true,
},
timeScale: {
borderVisible: false,
timeVisible: false,
},
handleScroll: false,
handleScale: false,
});
const prices = currentChartData.prices;
let baselinePrice: number;
if (selectedTimeframe === '1D') {
baselinePrice = props.regularMarketPreviousClose ?? prices[0];
} else {
baselinePrice = prices[0];
}
const baselineSeries = chart.addSeries(BaselineSeries);
baselineSeries.applyOptions({
baseValue: { type: 'price', price: baselinePrice },
topLineColor: isDarkMode ? '#14b8a6' : '#0d9488',
topFillColor1: isDarkMode
? 'rgba(20, 184, 166, 0.28)'
: 'rgba(13, 148, 136, 0.24)',
topFillColor2: isDarkMode
? 'rgba(20, 184, 166, 0.05)'
: 'rgba(13, 148, 136, 0.05)',
bottomLineColor: isDarkMode ? '#f87171' : '#dc2626',
bottomFillColor1: isDarkMode
? 'rgba(248, 113, 113, 0.05)'
: 'rgba(220, 38, 38, 0.05)',
bottomFillColor2: isDarkMode
? 'rgba(248, 113, 113, 0.28)'
: 'rgba(220, 38, 38, 0.24)',
lineWidth: 2,
crosshairMarkerVisible: true,
crosshairMarkerRadius: 4,
crosshairMarkerBorderColor: '',
crosshairMarkerBackgroundColor: '',
});
const data = currentChartData.timestamps.map((timestamp, index) => {
const price = currentChartData.prices[index];
return {
time: (timestamp / 1000) as any,
value: price,
};
});
baselineSeries.setData(data);
const comparisonColors = ['#8b5cf6', '#f59e0b', '#ec4899'];
if (props.comparisonData && props.comparisonData.length > 0) {
props.comparisonData.forEach((comp, index) => {
const compChartData = comp.chartData[selectedTimeframe];
if (compChartData && compChartData.prices.length > 0) {
const compData = compChartData.timestamps.map((timestamp, i) => ({
time: (timestamp / 1000) as any,
value: compChartData.prices[i],
}));
const compSeries = chart.addSeries(LineSeries);
compSeries.applyOptions({
color: comparisonColors[index] || '#6b7280',
lineWidth: 2,
crosshairMarkerVisible: true,
crosshairMarkerRadius: 4,
priceScaleId: 'left',
});
compSeries.setData(compData);
}
});
}
chart.timeScale().fitContent();
const handleResize = () => {
if (chartContainerRef.current) {
chart.applyOptions({
width: chartContainerRef.current.clientWidth,
});
}
};
window.addEventListener('resize', handleResize);
return () => {
window.removeEventListener('resize', handleResize);
chart.remove();
};
}, [
props.chartData,
props.comparisonData,
selectedTimeframe,
isDarkMode,
props.regularMarketPreviousClose,
]);
const isPositive = (props.regularMarketChange ?? 0) >= 0;
const isMarketOpen = props.marketState === 'REGULAR';
const isPreMarket = props.marketState === 'PRE';
const isPostMarket = props.marketState === 'POST';
const displayPrice = isPostMarket
? props.postMarketPrice ?? props.regularMarketPrice
: isPreMarket
? props.preMarketPrice ?? props.regularMarketPrice
: props.regularMarketPrice;
const displayChange = isPostMarket
? props.postMarketChange ?? props.regularMarketChange
: isPreMarket
? props.preMarketChange ?? props.regularMarketChange
: props.regularMarketChange;
const displayChangePercent = isPostMarket
? props.postMarketChangePercent ?? props.regularMarketChangePercent
: isPreMarket
? props.preMarketChangePercent ?? props.regularMarketChangePercent
: props.regularMarketChangePercent;
const changeColor = isPositive
? 'text-green-600 dark:text-green-400'
: 'text-red-600 dark:text-red-400';
if (props.error) {
return (
<div className="rounded-lg bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-4">
<p className="text-sm text-black dark:text-white">
Error: {props.error}
</p>
</div>
);
}
return (
<div className="rounded-lg border border-light-200 dark:border-dark-200 overflow-hidden">
<div className="p-4 space-y-4">
<div className="flex items-start justify-between gap-4 pb-4 border-b border-light-200 dark:border-dark-200">
<div className="flex-1">
<div className="flex items-center gap-2 mb-1">
{props.website && (
<img
src={`https://logo.clearbit.com/${new URL(props.website).hostname}`}
alt={`${props.symbol} logo`}
className="w-8 h-8 rounded-lg"
onError={(e) => {
(e.target as HTMLImageElement).style.display = 'none';
}}
/>
)}
<h3 className="text-2xl font-bold text-black dark:text-white">
{props.symbol}
</h3>
{props.exchange && (
<span className="px-2 py-0.5 text-xs font-medium rounded bg-light-100 dark:bg-dark-100 text-black/60 dark:text-white/60">
{props.exchange}
</span>
)}
{isMarketOpen && (
<div className="flex items-center gap-1.5 px-2 py-0.5 rounded-full bg-green-100 dark:bg-green-950/40 border border-green-300 dark:border-green-800">
<div className="w-1.5 h-1.5 rounded-full bg-green-500 animate-pulse" />
<span className="text-xs font-medium text-green-700 dark:text-green-400">
Live
</span>
</div>
)}
{isPreMarket && (
<div className="flex items-center gap-1.5 px-2 py-0.5 rounded-full bg-blue-100 dark:bg-blue-950/40 border border-blue-300 dark:border-blue-800">
<Clock className="w-3 h-3 text-blue-600 dark:text-blue-400" />
<span className="text-xs font-medium text-blue-700 dark:text-blue-400">
Pre-Market
</span>
</div>
)}
{isPostMarket && (
<div className="flex items-center gap-1.5 px-2 py-0.5 rounded-full bg-orange-100 dark:bg-orange-950/40 border border-orange-300 dark:border-orange-800">
<Clock className="w-3 h-3 text-orange-600 dark:text-orange-400" />
<span className="text-xs font-medium text-orange-700 dark:text-orange-400">
After Hours
</span>
</div>
)}
</div>
<p className="text-sm text-black/60 dark:text-white/60">
{props.longName || props.shortName}
</p>
</div>
<div className="text-right">
<div className="flex items-baseline gap-2 mb-1">
<span className="text-3xl font-medium text-black dark:text-white">
{props.currency === 'USD' ? '$' : ''}
{formatNumber(displayPrice)}
</span>
</div>
<div
className={`flex items-center justify-end gap-1 ${changeColor}`}
>
{isPositive ? (
<ArrowUpRight className="w-4 h-4" />
) : displayChange === 0 ? (
<Minus className="w-4 h-4" />
) : (
<ArrowDownRight className="w-4 h-4" />
)}
<span className="text-lg font-normal">
{displayChange !== undefined && displayChange >= 0 ? '+' : ''}
{formatNumber(displayChange)}
</span>
<span className="text-sm font-normal">
(
{displayChangePercent !== undefined && displayChangePercent >= 0
? '+'
: ''}
{formatNumber(displayChangePercent)}%)
</span>
</div>
</div>
</div>
{props.chartData && (
<div className="bg-light-secondary dark:bg-dark-secondary rounded-lg overflow-hidden">
<div className="flex items-center justify-between p-3 border-b border-light-200 dark:border-dark-200">
<div className="flex items-center gap-1">
{(['1D', '5D', '1M', '3M', '6M', '1Y', 'MAX'] as const).map(
(timeframe) => (
<button
key={timeframe}
onClick={() => setSelectedTimeframe(timeframe)}
disabled={!props.chartData?.[timeframe]}
className={`px-3 py-1.5 text-xs font-medium rounded transition-colors ${
selectedTimeframe === timeframe
? 'bg-black/10 dark:bg-white/10 text-black dark:text-white'
: 'text-black/50 dark:text-white/50 hover:text-black/80 dark:hover:text-white/80'
} disabled:opacity-30 disabled:cursor-not-allowed`}
>
{timeframe}
</button>
),
)}
</div>
{props.comparisonData && props.comparisonData.length > 0 && (
<div className="flex items-center gap-3 ml-auto">
<span className="text-xs text-black/50 dark:text-white/50">
{props.symbol}
</span>
{props.comparisonData.map((comp, index) => {
const colors = ['#8b5cf6', '#f59e0b', '#ec4899'];
return (
<div
key={comp.ticker}
className="flex items-center gap-1.5"
>
<div
className="w-2 h-2 rounded-full"
style={{ backgroundColor: colors[index] }}
/>
<span className="text-xs text-black/70 dark:text-white/70">
{comp.ticker}
</span>
</div>
);
})}
</div>
)}
</div>
<div className="p-4">
<div ref={chartContainerRef} />
</div>
<div className="grid grid-cols-3 border-t border-light-200 dark:border-dark-200">
<div className="flex justify-between p-3 border-r border-light-200 dark:border-dark-200">
<span className="text-xs text-black/50 dark:text-white/50">
Prev Close
</span>
<span className="text-xs text-black dark:text-white font-medium">
${formatNumber(props.regularMarketPreviousClose)}
</span>
</div>
<div className="flex justify-between p-3 border-r border-light-200 dark:border-dark-200">
<span className="text-xs text-black/50 dark:text-white/50">
52W Range
</span>
<span className="text-xs text-black dark:text-white font-medium">
${formatNumber(props.fiftyTwoWeekLow, 2)}-$
{formatNumber(props.fiftyTwoWeekHigh, 2)}
</span>
</div>
<div className="flex justify-between p-3">
<span className="text-xs text-black/50 dark:text-white/50">
Market Cap
</span>
<span className="text-xs text-black dark:text-white font-medium">
{formatLargeNumber(props.marketCap)}
</span>
</div>
<div className="flex justify-between p-3 border-t border-r border-light-200 dark:border-dark-200">
<span className="text-xs text-black/50 dark:text-white/50">
Open
</span>
<span className="text-xs text-black dark:text-white font-medium">
${formatNumber(props.regularMarketOpen)}
</span>
</div>
<div className="flex justify-between p-3 border-t border-r border-light-200 dark:border-dark-200">
<span className="text-xs text-black/50 dark:text-white/50">
P/E Ratio
</span>
<span className="text-xs text-black dark:text-white font-medium">
{props.trailingPE ? formatNumber(props.trailingPE, 2) : 'N/A'}
</span>
</div>
<div className="flex justify-between p-3 border-t border-light-200 dark:border-dark-200">
<span className="text-xs text-black/50 dark:text-white/50">
Dividend Yield
</span>
<span className="text-xs text-black dark:text-white font-medium">
{props.dividendYield
? `${formatNumber(props.dividendYield * 100, 2)}%`
: 'N/A'}
</span>
</div>
<div className="flex justify-between p-3 border-t border-r border-light-200 dark:border-dark-200">
<span className="text-xs text-black/50 dark:text-white/50">
Day Range
</span>
<span className="text-xs text-black dark:text-white font-medium">
${formatNumber(props.regularMarketDayLow, 2)}-$
{formatNumber(props.regularMarketDayHigh, 2)}
</span>
</div>
<div className="flex justify-between p-3 border-t border-r border-light-200 dark:border-dark-200">
<span className="text-xs text-black/50 dark:text-white/50">
Volume
</span>
<span className="text-xs text-black dark:text-white font-medium">
{formatLargeNumber(props.regularMarketVolume)}
</span>
</div>
<div className="flex justify-between p-3 border-t border-light-200 dark:border-dark-200">
<span className="text-xs text-black/50 dark:text-white/50">
EPS
</span>
<span className="text-xs text-black dark:text-white font-medium">
$
{props.earningsPerShare
? formatNumber(props.earningsPerShare, 2)
: 'N/A'}
</span>
</div>
</div>
</div>
)}
</div>
</div>
);
};
export default Stock;

View File

@@ -0,0 +1,407 @@
'use client';
import { Wind, Droplets, Gauge } from 'lucide-react';
import { useMemo, useEffect, useState } from 'react';
type WeatherWidgetProps = {
location: string;
current: {
time: string;
temperature_2m: number;
relative_humidity_2m: number;
apparent_temperature: number;
is_day: number;
precipitation: number;
weather_code: number;
wind_speed_10m: number;
wind_direction_10m: number;
wind_gusts_10m?: number;
};
daily: {
time: string[];
weather_code: number[];
temperature_2m_max: number[];
temperature_2m_min: number[];
precipitation_probability_max: number[];
};
timezone: string;
};
const getWeatherInfo = (code: number, isDay: boolean, isDarkMode: boolean) => {
const dayNight = isDay ? 'day' : 'night';
const weatherMap: Record<
number,
{ icon: string; description: string; gradient: string }
> = {
0: {
icon: `clear-${dayNight}.svg`,
description: 'Clear',
gradient: isDarkMode
? isDay
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #E8F1FA, #7A9DBF 35%, #4A7BA8 60%, #2F5A88)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #5A6A7E, #3E4E63 40%, #2A3544 65%, #1A2230)'
: isDay
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #DBEAFE 30%, #93C5FD 60%, #60A5FA)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #7B8694, #475569 45%, #334155 70%, #1E293B)',
},
1: {
icon: `clear-${dayNight}.svg`,
description: 'Mostly Clear',
gradient: isDarkMode
? isDay
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #E8F1FA, #7A9DBF 35%, #4A7BA8 60%, #2F5A88)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #5A6A7E, #3E4E63 40%, #2A3544 65%, #1A2230)'
: isDay
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #DBEAFE 30%, #93C5FD 60%, #60A5FA)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #7B8694, #475569 45%, #334155 70%, #1E293B)',
},
2: {
icon: `cloudy-1-${dayNight}.svg`,
description: 'Partly Cloudy',
gradient: isDarkMode
? isDay
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4E1ED, #8BA3B8 35%, #617A93 60%, #426070)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #6B7583, #4A5563 40%, #3A4450 65%, #2A3340)'
: isDay
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #E0F2FE 28%, #BFDBFE 58%, #93C5FD)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #8B99AB, #64748B 45%, #475569 70%, #334155)',
},
3: {
icon: `cloudy-1-${dayNight}.svg`,
description: 'Cloudy',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #B8C3CF, #758190 38%, #546270 65%, #3D4A58)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #F5F8FA, #CBD5E1 32%, #94A3B8 65%, #64748B)',
},
45: {
icon: `fog-${dayNight}.svg`,
description: 'Foggy',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #C5CDD8, #8892A0 38%, #697380 65%, #4F5A68)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #E2E8F0 30%, #CBD5E1 62%, #94A3B8)',
},
48: {
icon: `fog-${dayNight}.svg`,
description: 'Rime Fog',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #C5CDD8, #8892A0 38%, #697380 65%, #4F5A68)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #E2E8F0 30%, #CBD5E1 62%, #94A3B8)',
},
51: {
icon: `rainy-1-${dayNight}.svg`,
description: 'Light Drizzle',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #B8D4E5, #6FA4C5 35%, #4A85AC 60%, #356A8E)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #E5FBFF, #A5F3FC 28%, #67E8F9 60%, #22D3EE)',
},
53: {
icon: `rainy-1-${dayNight}.svg`,
description: 'Drizzle',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #B8D4E5, #6FA4C5 35%, #4A85AC 60%, #356A8E)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #E5FBFF, #A5F3FC 28%, #67E8F9 60%, #22D3EE)',
},
55: {
icon: `rainy-2-${dayNight}.svg`,
description: 'Heavy Drizzle',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #A5C5D8, #5E92B0 35%, #3F789D 60%, #2A5F82)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4F3FF, #7DD3FC 30%, #38BDF8 62%, #0EA5E9)',
},
61: {
icon: `rainy-2-${dayNight}.svg`,
description: 'Light Rain',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #A5C5D8, #5E92B0 35%, #3F789D 60%, #2A5F82)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4F3FF, #7DD3FC 30%, #38BDF8 62%, #0EA5E9)',
},
63: {
icon: `rainy-2-${dayNight}.svg`,
description: 'Rain',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #8DB3C8, #4D819F 38%, #326A87 65%, #215570)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #B8E8FF, #38BDF8 32%, #0EA5E9 65%, #0284C7)',
},
65: {
icon: `rainy-3-${dayNight}.svg`,
description: 'Heavy Rain',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #7BA3B8, #3D6F8A 38%, #295973 65%, #1A455D)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #9CD9F5, #0EA5E9 32%, #0284C7 65%, #0369A1)',
},
71: {
icon: `snowy-1-${dayNight}.svg`,
description: 'Light Snow',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #E5F0FA, #9BB5CE 32%, #7496B8 58%, #527A9E)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #F0F9FF 25%, #E0F2FE 55%, #BAE6FD)',
},
73: {
icon: `snowy-2-${dayNight}.svg`,
description: 'Snow',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4E5F3, #85A1BD 35%, #6584A8 60%, #496A8E)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #FAFEFF, #E0F2FE 28%, #BAE6FD 60%, #7DD3FC)',
},
75: {
icon: `snowy-3-${dayNight}.svg`,
description: 'Heavy Snow',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #BDD8EB, #6F92AE 35%, #4F7593 60%, #365A78)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #F0FAFF, #BAE6FD 30%, #7DD3FC 62%, #38BDF8)',
},
77: {
icon: `snowy-1-${dayNight}.svg`,
description: 'Snow Grains',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #E5F0FA, #9BB5CE 32%, #7496B8 58%, #527A9E)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #F0F9FF 25%, #E0F2FE 55%, #BAE6FD)',
},
80: {
icon: `rainy-2-${dayNight}.svg`,
description: 'Light Showers',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #A5C5D8, #5E92B0 35%, #3F789D 60%, #2A5F82)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4F3FF, #7DD3FC 30%, #38BDF8 62%, #0EA5E9)',
},
81: {
icon: `rainy-2-${dayNight}.svg`,
description: 'Showers',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #8DB3C8, #4D819F 38%, #326A87 65%, #215570)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #B8E8FF, #38BDF8 32%, #0EA5E9 65%, #0284C7)',
},
82: {
icon: `rainy-3-${dayNight}.svg`,
description: 'Heavy Showers',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #7BA3B8, #3D6F8A 38%, #295973 65%, #1A455D)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #9CD9F5, #0EA5E9 32%, #0284C7 65%, #0369A1)',
},
85: {
icon: `snowy-2-${dayNight}.svg`,
description: 'Light Snow Showers',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4E5F3, #85A1BD 35%, #6584A8 60%, #496A8E)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #FAFEFF, #E0F2FE 28%, #BAE6FD 60%, #7DD3FC)',
},
86: {
icon: `snowy-3-${dayNight}.svg`,
description: 'Snow Showers',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #BDD8EB, #6F92AE 35%, #4F7593 60%, #365A78)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #F0FAFF, #BAE6FD 30%, #7DD3FC 62%, #38BDF8)',
},
95: {
icon: `scattered-thunderstorms-${dayNight}.svg`,
description: 'Thunderstorm',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #8A95A3, #5F6A7A 38%, #475260 65%, #2F3A48)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #C8D1DD, #94A3B8 32%, #64748B 65%, #475569)',
},
96: {
icon: 'severe-thunderstorm.svg',
description: 'Thunderstorm + Hail',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #7A8593, #515C6D 38%, #3A4552 65%, #242D3A)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #B0BBC8, #64748B 32%, #475569 65%, #334155)',
},
99: {
icon: 'severe-thunderstorm.svg',
description: 'Severe Thunderstorm',
gradient: isDarkMode
? 'radial-gradient(ellipse 150% 100% at 50% 100%, #6A7583, #434E5D 40%, #2F3A47 68%, #1C2530)'
: 'radial-gradient(ellipse 150% 100% at 50% 100%, #9BA8B8, #475569 35%, #334155 68%, #1E293B)',
},
};
return weatherMap[code] || weatherMap[0];
};
const Weather = ({
location,
current,
daily,
timezone,
}: WeatherWidgetProps) => {
const [isDarkMode, setIsDarkMode] = useState(false);
useEffect(() => {
const checkDarkMode = () => {
setIsDarkMode(document.documentElement.classList.contains('dark'));
};
checkDarkMode();
const observer = new MutationObserver(checkDarkMode);
observer.observe(document.documentElement, {
attributes: true,
attributeFilter: ['class'],
});
return () => observer.disconnect();
}, []);
const weatherInfo = useMemo(
() =>
getWeatherInfo(
current?.weather_code || 0,
current?.is_day === 1,
isDarkMode,
),
[current?.weather_code, current?.is_day, isDarkMode],
);
const forecast = useMemo(() => {
if (!daily?.time || daily.time.length === 0) return [];
return daily.time.slice(1, 7).map((time, idx) => {
const date = new Date(time);
const dayName = date.toLocaleDateString('en-US', { weekday: 'short' });
const isDay = true;
const weatherCode = daily.weather_code[idx + 1];
const info = getWeatherInfo(weatherCode, isDay, isDarkMode);
return {
day: dayName,
icon: info.icon,
high: Math.round(daily.temperature_2m_max[idx + 1]),
low: Math.round(daily.temperature_2m_min[idx + 1]),
highF: Math.round((daily.temperature_2m_max[idx + 1] * 9) / 5 + 32),
lowF: Math.round((daily.temperature_2m_min[idx + 1] * 9) / 5 + 32),
precipitation: daily.precipitation_probability_max[idx + 1] || 0,
};
});
}, [daily, isDarkMode]);
if (!current || !daily || !daily.time || daily.time.length === 0) {
return (
<div className="relative overflow-hidden rounded-lg shadow-md bg-gray-200 dark:bg-gray-800">
<div className="p-4 text-black dark:text-white">
<p className="text-sm">Weather data unavailable for {location}</p>
</div>
</div>
);
}
return (
<div className="relative overflow-hidden rounded-lg shadow-md">
<div
className="absolute inset-0"
style={{
background: weatherInfo.gradient,
}}
/>
<div className="relative p-4 text-gray-800 dark:text-white">
<div className="flex items-start justify-between mb-3">
<div className="flex items-center gap-3">
<img
src={`/weather-ico/${weatherInfo.icon}`}
alt={weatherInfo.description}
className="w-16 h-16 drop-shadow-lg"
/>
<div>
<div className="flex items-baseline gap-1">
<span className="text-4xl font-bold drop-shadow-md">
{current.temperature_2m}°
</span>
<span className="text-lg">F C</span>
</div>
<p className="text-sm font-medium drop-shadow mt-0.5">
{weatherInfo.description}
</p>
</div>
</div>
<div className="text-right">
<p className="text-xs font-medium opacity-90">
{daily.temperature_2m_max[0]}° {daily.temperature_2m_min[0]}°
</p>
</div>
</div>
<div className="mb-3 pb-3 border-b border-gray-800/20 dark:border-white/20">
<h3 className="text-base font-semibold drop-shadow-md">{location}</h3>
<p className="text-xs text-gray-700 dark:text-white/80 drop-shadow mt-0.5">
{new Date(current.time).toLocaleString('en-US', {
weekday: 'short',
hour: 'numeric',
minute: '2-digit',
})}
</p>
</div>
<div className="grid grid-cols-6 gap-2 mb-3 pb-3 border-b border-gray-800/20 dark:border-white/20">
{forecast.map((day, idx) => (
<div
key={idx}
className="flex flex-col items-center bg-gray-800/10 dark:bg-white/10 backdrop-blur-sm rounded-md p-2"
>
<p className="text-xs font-medium mb-1">{day.day}</p>
<img
src={`/weather-ico/${day.icon}`}
alt=""
className="w-8 h-8 mb-1"
/>
<div className="flex items-center gap-1 text-xs">
<span className="font-semibold">{day.high}°</span>
<span className="text-gray-600 dark:text-white/60">
{day.low}°
</span>
</div>
{day.precipitation > 0 && (
<div className="flex items-center gap-0.5 mt-1">
<Droplets className="w-3 h-3 text-gray-600 dark:text-white/70" />
<span className="text-[10px] text-gray-600 dark:text-white/70">
{day.precipitation}%
</span>
</div>
)}
</div>
))}
</div>
<div className="grid grid-cols-3 gap-2 text-xs">
<div className="flex items-center gap-2 bg-gray-800/10 dark:bg-white/10 backdrop-blur-sm rounded-md p-2">
<Wind className="w-4 h-4 text-gray-700 dark:text-white/80 flex-shrink-0" />
<div>
<p className="text-[10px] text-gray-600 dark:text-white/70">
Wind
</p>
<p className="font-semibold">
{Math.round(current.wind_speed_10m)} km/h
</p>
</div>
</div>
<div className="flex items-center gap-2 bg-gray-800/10 dark:bg-white/10 backdrop-blur-sm rounded-md p-2">
<Droplets className="w-4 h-4 text-gray-700 dark:text-white/80 flex-shrink-0" />
<div>
<p className="text-[10px] text-gray-600 dark:text-white/70">
Humidity
</p>
<p className="font-semibold">
{Math.round(current.relative_humidity_2m)}%
</p>
</div>
</div>
<div className="flex items-center gap-2 bg-gray-800/10 dark:bg-white/10 backdrop-blur-sm rounded-md p-2">
<Gauge className="w-4 h-4 text-gray-700 dark:text-white/80 flex-shrink-0" />
<div>
<p className="text-[10px] text-gray-600 dark:text-white/70">
Feels Like
</p>
<p className="font-semibold">
{Math.round(current.apparent_temperature)}°C
</p>
</div>
</div>
</div>
</div>
</div>
);
};
export default Weather;

View File

@@ -1,6 +1,14 @@
import { Message } from '@/components/ChatWindow';
export const getSuggestions = async (chatHistory: Message[]) => {
export const getSuggestions = async (chatHistory: [string, string][]) => {
const chatTurns = chatHistory.map(([role, content]) => {
if (role === 'human') {
return { role: 'user', content };
} else {
return { role: 'assistant', content };
}
});
const chatModel = localStorage.getItem('chatModelKey');
const chatModelProvider = localStorage.getItem('chatModelProviderId');
@@ -10,7 +18,7 @@ export const getSuggestions = async (chatHistory: Message[]) => {
'Content-Type': 'application/json',
},
body: JSON.stringify({
chatHistory: chatHistory,
chatHistory: chatTurns,
chatModel: {
providerId: chatModelProvider,
key: chatModel,

View File

@@ -0,0 +1,66 @@
/* I don't think can be classified as agents but to keep the structure consistent i guess ill keep it here */
import { searchSearxng } from '@/lib/searxng';
import {
imageSearchFewShots,
imageSearchPrompt,
} from '@/lib/prompts/media/image';
import BaseLLM from '@/lib/models/base/llm';
import z from 'zod';
import { ChatTurnMessage } from '@/lib/types';
import formatChatHistoryAsString from '@/lib/utils/formatHistory';
type ImageSearchChainInput = {
chatHistory: ChatTurnMessage[];
query: string;
};
type ImageSearchResult = {
img_src: string;
url: string;
title: string;
};
const searchImages = async (
input: ImageSearchChainInput,
llm: BaseLLM<any>,
) => {
const schema = z.object({
query: z.string().describe('The image search query.'),
});
const res = await llm.generateObject<z.infer<typeof schema>>({
messages: [
{
role: 'system',
content: imageSearchPrompt,
},
...imageSearchFewShots,
{
role: 'user',
content: `<conversation>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation>\n<follow_up>\n${input.query}\n</follow_up>`,
},
],
schema: schema,
});
const searchRes = await searchSearxng(res.query, {
engines: ['bing images', 'google images'],
});
const images: ImageSearchResult[] = [];
searchRes.results.forEach((result) => {
if (result.img_src && result.url && result.title) {
images.push({
img_src: result.img_src,
url: result.url,
title: result.title,
});
}
});
return images.slice(0, 10);
};
export default searchImages;

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import formatChatHistoryAsString from '@/lib/utils/formatHistory';
import { searchSearxng } from '@/lib/searxng';
import {
videoSearchFewShots,
videoSearchPrompt,
} from '@/lib/prompts/media/videos';
import { ChatTurnMessage } from '@/lib/types';
import BaseLLM from '@/lib/models/base/llm';
import z from 'zod';
type VideoSearchChainInput = {
chatHistory: ChatTurnMessage[];
query: string;
};
type VideoSearchResult = {
img_src: string;
url: string;
title: string;
iframe_src: string;
};
const searchVideos = async (
input: VideoSearchChainInput,
llm: BaseLLM<any>,
) => {
const schema = z.object({
query: z.string().describe('The video search query.'),
});
const res = await llm.generateObject<z.infer<typeof schema>>({
messages: [
{
role: 'system',
content: videoSearchPrompt,
},
...videoSearchFewShots,
{
role: 'user',
content: `<conversation>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation>\n<follow_up>\n${input.query}\n</follow_up>`,
},
],
schema: schema,
});
const searchRes = await searchSearxng(res.query, {
engines: ['youtube'],
});
const videos: VideoSearchResult[] = [];
searchRes.results.forEach((result) => {
if (result.thumbnail && result.url && result.title && result.iframe_src) {
videos.push({
img_src: result.thumbnail,
url: result.url,
title: result.title,
iframe_src: result.iframe_src,
});
}
});
return videos.slice(0, 10);
};
export default searchVideos;

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import z from 'zod';
import { ClassifierInput } from './types';
import { classifierPrompt } from '@/lib/prompts/search/classifier';
import formatChatHistoryAsString from '@/lib/utils/formatHistory';
const schema = z.object({
classification: z.object({
skipSearch: z
.boolean()
.describe('Indicates whether to skip the search step.'),
personalSearch: z
.boolean()
.describe('Indicates whether to perform a personal search.'),
academicSearch: z
.boolean()
.describe('Indicates whether to perform an academic search.'),
discussionSearch: z
.boolean()
.describe('Indicates whether to perform a discussion search.'),
showWeatherWidget: z
.boolean()
.describe('Indicates whether to show the weather widget.'),
showStockWidget: z
.boolean()
.describe('Indicates whether to show the stock widget.'),
showCalculationWidget: z
.boolean()
.describe('Indicates whether to show the calculation widget.'),
}),
standaloneFollowUp: z
.string()
.describe(
"A self-contained, context-independent reformulation of the user's question.",
),
});
export const classify = async (input: ClassifierInput) => {
const output = await input.llm.generateObject<typeof schema>({
messages: [
{
role: 'system',
content: classifierPrompt,
},
{
role: 'user',
content: `<conversation_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation_history>\n<user_query>\n${input.query}\n</user_query>`,
},
],
schema,
});
return output;
};

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import { ResearcherOutput, SearchAgentInput } from './types';
import SessionManager from '@/lib/session';
import { classify } from './classifier';
import Researcher from './researcher';
import { getWriterPrompt } from '@/lib/prompts/search/writer';
import { WidgetExecutor } from './widgets';
class SearchAgent {
async searchAsync(session: SessionManager, input: SearchAgentInput) {
const classification = await classify({
chatHistory: input.chatHistory,
enabledSources: input.config.sources,
query: input.followUp,
llm: input.config.llm,
});
const widgetPromise = WidgetExecutor.executeAll({
classification,
chatHistory: input.chatHistory,
followUp: input.followUp,
llm: input.config.llm,
}).then((widgetOutputs) => {
widgetOutputs.forEach((o) => {
session.emitBlock({
id: crypto.randomUUID(),
type: 'widget',
data: {
widgetType: o.type,
params: o.data,
},
});
});
return widgetOutputs;
});
let searchPromise: Promise<ResearcherOutput> | null = null;
if (!classification.classification.skipSearch) {
const researcher = new Researcher();
searchPromise = researcher.research(session, {
chatHistory: input.chatHistory,
followUp: input.followUp,
classification: classification,
config: input.config,
});
}
const [widgetOutputs, searchResults] = await Promise.all([
widgetPromise,
searchPromise,
]);
session.emit('data', {
type: 'researchComplete',
});
const finalContext =
searchResults?.findings
.filter((f) => f.type === 'search_results')
.flatMap((f) => f.results)
.map((f) => `${f.metadata.title}: ${f.content}`)
.join('\n') || '';
const widgetContext = widgetOutputs
.map((o) => {
return `${o.type}: ${o.llmContext}`;
})
.join('\n-------------\n');
const finalContextWithWidgets = `<search_results note="These are the search results and you can cite these">${finalContext}</search_results>\n<widgets_result noteForAssistant="Its output is already showed to the user, you can use this information to answer the query but do not CITE this as a souce">${widgetContext}</widgets_result>`;
const writerPrompt = getWriterPrompt(finalContextWithWidgets);
const answerStream = input.config.llm.streamText({
messages: [
{
role: 'system',
content: writerPrompt,
},
...input.chatHistory,
{
role: 'user',
content: input.followUp,
},
],
});
let accumulatedText = '';
for await (const chunk of answerStream) {
accumulatedText += chunk.contentChunk;
session.emit('data', {
type: 'response',
data: chunk.contentChunk,
});
}
session.emit('end', {});
}
}
export default SearchAgent;

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import z from 'zod';
import { ResearchAction } from '../../types';
const doneAction: ResearchAction<any> = {
name: 'done',
description:
"Indicates that the research process is complete and no further actions are needed. Use this action when you have gathered sufficient information to answer the user's query.",
enabled: (_) => true,
schema: z.object({
type: z.literal('done'),
}),
execute: async (params, additionalConfig) => {
return {
type: 'done',
};
},
};
export default doneAction;

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import doneAction from './done';
import ActionRegistry from './registry';
import webSearchAction from './webSearch';
ActionRegistry.register(webSearchAction);
ActionRegistry.register(doneAction);
export { ActionRegistry };

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import {
ActionConfig,
ActionOutput,
AdditionalConfig,
ClassifierOutput,
ResearchAction,
} from '../../types';
class ActionRegistry {
private static actions: Map<string, ResearchAction> = new Map();
static register(action: ResearchAction<any>) {
this.actions.set(action.name, action);
}
static get(name: string): ResearchAction | undefined {
return this.actions.get(name);
}
static getAvailableActions(config: {
classification: ClassifierOutput;
}): ResearchAction[] {
return Array.from(
this.actions.values().filter((action) => action.enabled(config)),
);
}
static getAvailableActionsDescriptions(config: {
classification: ClassifierOutput;
}): string {
const availableActions = this.getAvailableActions(config);
return availableActions
.map((action) => `------------\n##${action.name}\n${action.description}`)
.join('\n\n');
}
static async execute(
name: string,
params: any,
additionalConfig: AdditionalConfig,
) {
const action = this.actions.get(name);
if (!action) {
throw new Error(`Action with name ${name} not found`);
}
return action.execute(params, additionalConfig);
}
static async executeAll(
actions: ActionConfig[],
additionalConfig: AdditionalConfig,
): Promise<ActionOutput[]> {
const results: ActionOutput[] = [];
await Promise.all(
actions.map(async (actionConfig) => {
const output = await this.execute(
actionConfig.type,
actionConfig.params,
additionalConfig,
);
results.push(output);
}),
);
return results;
}
}
export default ActionRegistry;

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import z from 'zod';
import { ResearchAction } from '../../types';
import { searchSearxng } from '@/lib/searxng';
import { Chunk } from '@/lib/types';
const actionSchema = z.object({
type: z.literal('web_search'),
queries: z
.array(z.string())
.describe('An array of search queries to perform web searches for.'),
});
const actionDescription = `
You have to use this action aggressively to find relevant information from the web to answer user queries. You can combine this action with other actions to gather comprehensive data. Always ensure that you provide accurate and up-to-date information by leveraging web search results.
When this action is present, you must use it to obtain current information from the web.
### How to use:
1. For speed search mode, you can use this action once. Make sure to cover all aspects of the user's query in that single search.
2. If you're on quality mode, you'll get to use this action up to two times. Use the first search to gather general information, and the second search to fill in any gaps or get more specific details based on the initial findings.
3. If you're set on quality mode, then you will get to use this action multiple times to gather more information. Use your judgment to decide when additional searches are necessary to provide a thorough and accurate response.
Input: An array of search queries. Make sure the queries are relevant to the user's request and cover different aspects if necessary. You can include a maximum of 3 queries. Make sure the queries are SEO friendly and not sentences rather keywords which can be used to search a search engine like Google, Bing, etc.
`;
const webSearchAction: ResearchAction<typeof actionSchema> = {
name: 'web_search',
description: actionDescription,
schema: actionSchema,
enabled: (config) => true,
execute: async (input, _) => {
let results: Chunk[] = [];
const search = async (q: string) => {
const res = await searchSearxng(q);
res.results.forEach((r) => {
results.push({
content: r.content || r.title,
metadata: {
title: r.title,
url: r.url,
},
});
});
};
await Promise.all(input.queries.map(search));
return {
type: 'search_results',
results,
};
},
};
export default webSearchAction;

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import z from 'zod';
import {
ActionConfig,
ActionOutput,
ResearcherInput,
ResearcherOutput,
} from '../types';
import { ActionRegistry } from './actions';
import { getResearcherPrompt } from '@/lib/prompts/search/researcher';
import SessionManager from '@/lib/session';
import { ReasoningResearchBlock } from '@/lib/types';
import formatChatHistoryAsString from '@/lib/utils/formatHistory';
class Researcher {
async research(
session: SessionManager,
input: ResearcherInput,
): Promise<ResearcherOutput> {
let findings: string = '';
let actionOutput: ActionOutput[] = [];
let maxIteration =
input.config.mode === 'speed'
? 1
: input.config.mode === 'balanced'
? 3
: 25;
const availableActions = ActionRegistry.getAvailableActions({
classification: input.classification,
});
const schema = z.object({
reasoning: z
.string()
.describe('The reasoning behind choosing the next action.'),
action: z
.union(availableActions.map((a) => a.schema))
.describe('The action to be performed next.'),
});
const availableActionsDescription =
ActionRegistry.getAvailableActionsDescriptions({
classification: input.classification,
});
const researchBlockId = crypto.randomUUID();
session.emitBlock({
id: researchBlockId,
type: 'research',
data: {
subSteps: [],
},
});
for (let i = 0; i < maxIteration; i++) {
const researcherPrompt = getResearcherPrompt(
availableActionsDescription,
input.config.mode,
i,
maxIteration,
);
const actionStream = input.config.llm.streamObject<typeof schema>({
messages: [
{
role: 'system',
content: researcherPrompt,
},
{
role: 'user',
content: `
<conversation>
${formatChatHistoryAsString(input.chatHistory.slice(-10))}
User: ${input.followUp} (Standalone question: ${input.classification.standaloneFollowUp})
</conversation>
<previous_actions>
${findings}
</previous_actions>
`,
},
],
schema,
});
const block = session.getBlock(researchBlockId);
let reasoningEmitted = false;
let reasoningId = crypto.randomUUID();
let finalActionRes: any;
for await (const partialRes of actionStream) {
try {
if (
partialRes.reasoning &&
!reasoningEmitted &&
block &&
block.type === 'research'
) {
reasoningEmitted = true;
block.data.subSteps.push({
id: reasoningId,
type: 'reasoning',
reasoning: partialRes.reasoning,
});
session.updateBlock(researchBlockId, [
{
op: 'replace',
path: '/data/subSteps',
value: block.data.subSteps,
},
]);
} else if (
partialRes.reasoning &&
reasoningEmitted &&
block &&
block.type === 'research'
) {
const subStepIndex = block.data.subSteps.findIndex(
(step: any) => step.id === reasoningId,
);
if (subStepIndex !== -1) {
const subStep = block.data.subSteps[
subStepIndex
] as ReasoningResearchBlock;
subStep.reasoning = partialRes.reasoning;
session.updateBlock(researchBlockId, [
{
op: 'replace',
path: '/data/subSteps',
value: block.data.subSteps,
},
]);
}
}
finalActionRes = partialRes;
} catch (e) {
// nothing
}
}
if (finalActionRes.action.type === 'done') {
break;
}
const actionConfig: ActionConfig = {
type: finalActionRes.action.type as string,
params: finalActionRes.action,
};
const queries = actionConfig.params.queries || [];
if (block && block.type === 'research') {
block.data.subSteps.push({
id: crypto.randomUUID(),
type: 'searching',
searching: queries,
});
session.updateBlock(researchBlockId, [
{ op: 'replace', path: '/data/subSteps', value: block.data.subSteps },
]);
}
findings += `\n---\nIteration ${i + 1}:\n`;
findings += 'Reasoning: ' + finalActionRes.reasoning + '\n';
findings += `Executing Action: ${actionConfig.type} with params ${JSON.stringify(actionConfig.params)}\n`;
const actionResult = await ActionRegistry.execute(
actionConfig.type,
actionConfig.params,
{
llm: input.config.llm,
embedding: input.config.embedding,
session: session,
},
);
actionOutput.push(actionResult);
if (actionResult.type === 'search_results') {
if (block && block.type === 'research') {
block.data.subSteps.push({
id: crypto.randomUUID(),
type: 'reading',
reading: actionResult.results,
});
session.updateBlock(researchBlockId, [
{
op: 'replace',
path: '/data/subSteps',
value: block.data.subSteps,
},
]);
}
findings += actionResult.results
.map(
(r) =>
`Title: ${r.metadata.title}\nURL: ${r.metadata.url}\nContent: ${r.content}\n`,
)
.join('\n');
}
findings += '\n---------\n';
}
const searchResults = actionOutput.filter(
(a) => a.type === 'search_results',
);
session.emit('data', {
type: 'sources',
data: searchResults
.flatMap((a) => a.results)
.map((r) => ({
content: r.content,
metadata: r.metadata,
})),
});
return {
findings: actionOutput,
};
}
}
export default Researcher;

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import z from 'zod';
import BaseLLM from '../../models/base/llm';
import BaseEmbedding from '@/lib/models/base/embedding';
import SessionManager from '@/lib/session';
import { ChatTurnMessage, Chunk } from '@/lib/types';
export type SearchSources = 'web' | 'discussions' | 'academic';
export type SearchAgentConfig = {
sources: SearchSources[];
llm: BaseLLM<any>;
embedding: BaseEmbedding<any>;
mode: 'speed' | 'balanced' | 'quality';
};
export type SearchAgentInput = {
chatHistory: ChatTurnMessage[];
followUp: string;
config: SearchAgentConfig;
};
export type WidgetInput = {
chatHistory: ChatTurnMessage[];
followUp: string;
classification: ClassifierOutput;
llm: BaseLLM<any>;
};
export type Widget = {
type: string;
shouldExecute: (classification: ClassifierOutput) => boolean;
execute: (input: WidgetInput) => Promise<WidgetOutput | void>;
};
export type WidgetOutput = {
type: string;
llmContext: string;
data: any;
};
export type ClassifierInput = {
llm: BaseLLM<any>;
enabledSources: SearchSources[];
query: string;
chatHistory: ChatTurnMessage[];
};
export type ClassifierOutput = {
classification: {
skipSearch: boolean;
personalSearch: boolean;
academicSearch: boolean;
discussionSearch: boolean;
showWeatherWidget: boolean;
showStockWidget: boolean;
showCalculationWidget: boolean;
};
standaloneFollowUp: string;
};
export type AdditionalConfig = {
llm: BaseLLM<any>;
embedding: BaseEmbedding<any>;
session: SessionManager;
};
export type ResearcherInput = {
chatHistory: ChatTurnMessage[];
followUp: string;
classification: ClassifierOutput;
config: SearchAgentConfig;
};
export type ResearcherOutput = {
findings: ActionOutput[];
};
export type SearchActionOutput = {
type: 'search_results';
results: Chunk[];
};
export type DoneActionOutput = {
type: 'done';
};
export type ActionOutput = SearchActionOutput | DoneActionOutput;
export interface ResearchAction<
TSchema extends z.ZodObject<any> = z.ZodObject<any>,
> {
name: string;
description: string;
schema: z.ZodObject<any>;
enabled: (config: { classification: ClassifierOutput }) => boolean;
execute: (
params: z.infer<TSchema>,
additionalConfig: AdditionalConfig,
) => Promise<ActionOutput>;
}
export type ActionConfig = {
type: string;
params: Record<string, any>;
};

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import z from 'zod';
import { Widget } from '../types';
import formatChatHistoryAsString from '@/lib/utils/formatHistory';
import { exp, evaluate as mathEval } from 'mathjs';
const schema = z.object({
expression: z
.string()
.describe('Mathematical expression to calculate or evaluate.'),
notPresent: z
.boolean()
.describe('Whether there is any need for the calculation widget.'),
});
const system = `
<role>
Assistant is a calculation expression extractor. You will recieve a user follow up and a conversation history.
Your task is to determine if there is a mathematical expression that needs to be calculated or evaluated. If there is, extract the expression and return it. If there is no need for any calculation, set notPresent to true.
</role>
<instructions>
Make sure that the extracted expression is valid and can be used to calculate the result with Math JS library (https://mathjs.org/). If the expression is not valid, set notPresent to true.
If you feel like you cannot extract a valid expression, set notPresent to true.
</instructions>
<output_format>
You must respond in the following JSON format without any extra text, explanations or filler sentences:
{
"expression": string,
"notPresent": boolean
}
</output_format>
`;
const calculationWidget: Widget = {
type: 'calculationWidget',
shouldExecute: (classification) =>
classification.classification.showCalculationWidget,
execute: async (input) => {
const output = await input.llm.generateObject<typeof schema>({
messages: [
{
role: 'system',
content: system,
},
{
role: 'user',
content: `<conversation_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation_history>\n<user_follow_up>\n${input.followUp}\n</user_follow_up>`,
},
],
schema,
});
const result = mathEval(output.expression);
return {
type: 'calculation_result',
llmContext: `The result of the calculation for the expression "${output.expression}" is: ${result}`,
data: {
expression: output.expression,
result,
},
};
},
};
export default calculationWidget;

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import { Widget, WidgetInput, WidgetOutput } from '../types';
class WidgetExecutor {
static widgets = new Map<string, Widget>();
static register(widget: Widget) {
this.widgets.set(widget.type, widget);
}
static getWidget(type: string): Widget | undefined {
return this.widgets.get(type);
}
static async executeAll(input: WidgetInput): Promise<WidgetOutput[]> {
const results: WidgetOutput[] = [];
await Promise.all(
Array.from(this.widgets.values()).map(async (widget) => {
try {
if (widget.shouldExecute(input.classification)) {
const output = await widget.execute(input);
if (output) {
results.push(output);
}
}
} catch (e) {
console.log(`Error executing widget ${widget.type}:`, e);
}
}),
);
return results;
}
}
export default WidgetExecutor;

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import calculationWidget from './calculationWidget';
import WidgetExecutor from './executor';
import weatherWidget from './weatherWidget';
import stockWidget from './stockWidget';
WidgetExecutor.register(weatherWidget);
WidgetExecutor.register(calculationWidget);
WidgetExecutor.register(stockWidget);
export { WidgetExecutor };

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import z from 'zod';
import { Widget } from '../types';
import YahooFinance from 'yahoo-finance2';
import formatChatHistoryAsString from '@/lib/utils/formatHistory';
const yf = new YahooFinance({
suppressNotices: ['yahooSurvey'],
});
const schema = z.object({
name: z
.string()
.describe(
"The stock name for example Nvidia, Google, Apple, Microsoft etc. You can also return ticker if you're aware of it otherwise just use the name.",
),
comparisonNames: z
.array(z.string())
.max(3)
.describe(
"Optional array of up to 3 stock names to compare against the base name (e.g., ['Microsoft', 'GOOGL', 'Meta']). Charts will show percentage change comparison.",
),
notPresent: z
.boolean()
.describe('Whether there is no need for the stock widget.'),
});
const systemPrompt = `
<role>
You are a stock ticker/name extractor. You will receive a user follow up and a conversation history.
Your task is to determine if the user is asking about stock information and extract the stock name(s) they want data for.
</role>
<instructions>
- If the user is asking about a stock, extract the primary stock name or ticker.
- If the user wants to compare stocks, extract up to 3 comparison stock names in comparisonNames.
- You can use either stock names (e.g., "Nvidia", "Apple") or tickers (e.g., "NVDA", "AAPL").
- If you cannot determine a valid stock or the query is not stock-related, set notPresent to true.
- If no comparison is needed, set comparisonNames to an empty array.
</instructions>
<output_format>
You must respond in the following JSON format without any extra text, explanations or filler sentences:
{
"name": string,
"comparisonNames": string[],
"notPresent": boolean
}
</output_format>
`;
const stockWidget: Widget = {
type: 'stockWidget',
shouldExecute: (classification) =>
classification.classification.showStockWidget,
execute: async (input) => {
const output = await input.llm.generateObject<typeof schema>({
messages: [
{
role: 'system',
content: systemPrompt,
},
{
role: 'user',
content: `<conversation_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation_history>\n<user_follow_up>\n${input.followUp}\n</user_follow_up>`,
},
],
schema,
});
if (output.notPresent) {
return;
}
const params = output;
try {
const name = params.name;
const findings = await yf.search(name);
if (findings.quotes.length === 0)
throw new Error(`Failed to find quote for name/symbol: ${name}`);
const ticker = findings.quotes[0].symbol as string;
const quote: any = await yf.quote(ticker);
const chartPromises = {
'1D': yf
.chart(ticker, {
period1: new Date(Date.now() - 2 * 24 * 60 * 60 * 1000),
period2: new Date(),
interval: '5m',
})
.catch(() => null),
'5D': yf
.chart(ticker, {
period1: new Date(Date.now() - 6 * 24 * 60 * 60 * 1000),
period2: new Date(),
interval: '15m',
})
.catch(() => null),
'1M': yf
.chart(ticker, {
period1: new Date(Date.now() - 30 * 24 * 60 * 60 * 1000),
interval: '1d',
})
.catch(() => null),
'3M': yf
.chart(ticker, {
period1: new Date(Date.now() - 90 * 24 * 60 * 60 * 1000),
interval: '1d',
})
.catch(() => null),
'6M': yf
.chart(ticker, {
period1: new Date(Date.now() - 180 * 24 * 60 * 60 * 1000),
interval: '1d',
})
.catch(() => null),
'1Y': yf
.chart(ticker, {
period1: new Date(Date.now() - 365 * 24 * 60 * 60 * 1000),
interval: '1d',
})
.catch(() => null),
MAX: yf
.chart(ticker, {
period1: new Date(Date.now() - 10 * 365 * 24 * 60 * 60 * 1000),
interval: '1wk',
})
.catch(() => null),
};
const charts = await Promise.all([
chartPromises['1D'],
chartPromises['5D'],
chartPromises['1M'],
chartPromises['3M'],
chartPromises['6M'],
chartPromises['1Y'],
chartPromises['MAX'],
]);
const [chart1D, chart5D, chart1M, chart3M, chart6M, chart1Y, chartMAX] =
charts;
if (!quote) {
throw new Error(`No data found for ticker: ${ticker}`);
}
let comparisonData: any = null;
if (params.comparisonNames.length > 0) {
const comparisonPromises = params.comparisonNames
.slice(0, 3)
.map(async (compName) => {
try {
const compFindings = await yf.search(compName);
if (compFindings.quotes.length === 0) return null;
const compTicker = compFindings.quotes[0].symbol as string;
const compQuote = await yf.quote(compTicker);
const compCharts = await Promise.all([
yf
.chart(compTicker, {
period1: new Date(Date.now() - 2 * 24 * 60 * 60 * 1000),
period2: new Date(),
interval: '5m',
})
.catch(() => null),
yf
.chart(compTicker, {
period1: new Date(Date.now() - 6 * 24 * 60 * 60 * 1000),
period2: new Date(),
interval: '15m',
})
.catch(() => null),
yf
.chart(compTicker, {
period1: new Date(Date.now() - 30 * 24 * 60 * 60 * 1000),
interval: '1d',
})
.catch(() => null),
yf
.chart(compTicker, {
period1: new Date(Date.now() - 90 * 24 * 60 * 60 * 1000),
interval: '1d',
})
.catch(() => null),
yf
.chart(compTicker, {
period1: new Date(Date.now() - 180 * 24 * 60 * 60 * 1000),
interval: '1d',
})
.catch(() => null),
yf
.chart(compTicker, {
period1: new Date(Date.now() - 365 * 24 * 60 * 60 * 1000),
interval: '1d',
})
.catch(() => null),
yf
.chart(compTicker, {
period1: new Date(
Date.now() - 10 * 365 * 24 * 60 * 60 * 1000,
),
interval: '1wk',
})
.catch(() => null),
]);
return {
ticker: compTicker,
name: compQuote.shortName || compTicker,
charts: compCharts,
};
} catch (error) {
console.error(
`Failed to fetch comparison ticker ${compName}:`,
error,
);
return null;
}
});
const compResults = await Promise.all(comparisonPromises);
comparisonData = compResults.filter((r) => r !== null);
}
const stockData = {
symbol: quote.symbol,
shortName: quote.shortName || quote.longName || ticker,
longName: quote.longName,
exchange: quote.fullExchangeName || quote.exchange,
currency: quote.currency,
quoteType: quote.quoteType,
marketState: quote.marketState,
regularMarketTime: quote.regularMarketTime,
postMarketTime: quote.postMarketTime,
preMarketTime: quote.preMarketTime,
regularMarketPrice: quote.regularMarketPrice,
regularMarketChange: quote.regularMarketChange,
regularMarketChangePercent: quote.regularMarketChangePercent,
regularMarketPreviousClose: quote.regularMarketPreviousClose,
regularMarketOpen: quote.regularMarketOpen,
regularMarketDayHigh: quote.regularMarketDayHigh,
regularMarketDayLow: quote.regularMarketDayLow,
postMarketPrice: quote.postMarketPrice,
postMarketChange: quote.postMarketChange,
postMarketChangePercent: quote.postMarketChangePercent,
preMarketPrice: quote.preMarketPrice,
preMarketChange: quote.preMarketChange,
preMarketChangePercent: quote.preMarketChangePercent,
regularMarketVolume: quote.regularMarketVolume,
averageDailyVolume3Month: quote.averageDailyVolume3Month,
averageDailyVolume10Day: quote.averageDailyVolume10Day,
bid: quote.bid,
bidSize: quote.bidSize,
ask: quote.ask,
askSize: quote.askSize,
fiftyTwoWeekLow: quote.fiftyTwoWeekLow,
fiftyTwoWeekHigh: quote.fiftyTwoWeekHigh,
fiftyTwoWeekChange: quote.fiftyTwoWeekChange,
fiftyTwoWeekChangePercent: quote.fiftyTwoWeekChangePercent,
marketCap: quote.marketCap,
trailingPE: quote.trailingPE,
forwardPE: quote.forwardPE,
priceToBook: quote.priceToBook,
bookValue: quote.bookValue,
earningsPerShare: quote.epsTrailingTwelveMonths,
epsForward: quote.epsForward,
dividendRate: quote.dividendRate,
dividendYield: quote.dividendYield,
exDividendDate: quote.exDividendDate,
trailingAnnualDividendRate: quote.trailingAnnualDividendRate,
trailingAnnualDividendYield: quote.trailingAnnualDividendYield,
beta: quote.beta,
fiftyDayAverage: quote.fiftyDayAverage,
fiftyDayAverageChange: quote.fiftyDayAverageChange,
fiftyDayAverageChangePercent: quote.fiftyDayAverageChangePercent,
twoHundredDayAverage: quote.twoHundredDayAverage,
twoHundredDayAverageChange: quote.twoHundredDayAverageChange,
twoHundredDayAverageChangePercent:
quote.twoHundredDayAverageChangePercent,
sector: quote.sector,
industry: quote.industry,
website: quote.website,
chartData: {
'1D': chart1D
? {
timestamps: chart1D.quotes.map((q: any) => q.date.getTime()),
prices: chart1D.quotes.map((q: any) => q.close),
}
: null,
'5D': chart5D
? {
timestamps: chart5D.quotes.map((q: any) => q.date.getTime()),
prices: chart5D.quotes.map((q: any) => q.close),
}
: null,
'1M': chart1M
? {
timestamps: chart1M.quotes.map((q: any) => q.date.getTime()),
prices: chart1M.quotes.map((q: any) => q.close),
}
: null,
'3M': chart3M
? {
timestamps: chart3M.quotes.map((q: any) => q.date.getTime()),
prices: chart3M.quotes.map((q: any) => q.close),
}
: null,
'6M': chart6M
? {
timestamps: chart6M.quotes.map((q: any) => q.date.getTime()),
prices: chart6M.quotes.map((q: any) => q.close),
}
: null,
'1Y': chart1Y
? {
timestamps: chart1Y.quotes.map((q: any) => q.date.getTime()),
prices: chart1Y.quotes.map((q: any) => q.close),
}
: null,
MAX: chartMAX
? {
timestamps: chartMAX.quotes.map((q: any) => q.date.getTime()),
prices: chartMAX.quotes.map((q: any) => q.close),
}
: null,
},
comparisonData: comparisonData
? comparisonData.map((comp: any) => ({
ticker: comp.ticker,
name: comp.name,
chartData: {
'1D': comp.charts[0]
? {
timestamps: comp.charts[0].quotes.map((q: any) =>
q.date.getTime(),
),
prices: comp.charts[0].quotes.map((q: any) => q.close),
}
: null,
'5D': comp.charts[1]
? {
timestamps: comp.charts[1].quotes.map((q: any) =>
q.date.getTime(),
),
prices: comp.charts[1].quotes.map((q: any) => q.close),
}
: null,
'1M': comp.charts[2]
? {
timestamps: comp.charts[2].quotes.map((q: any) =>
q.date.getTime(),
),
prices: comp.charts[2].quotes.map((q: any) => q.close),
}
: null,
'3M': comp.charts[3]
? {
timestamps: comp.charts[3].quotes.map((q: any) =>
q.date.getTime(),
),
prices: comp.charts[3].quotes.map((q: any) => q.close),
}
: null,
'6M': comp.charts[4]
? {
timestamps: comp.charts[4].quotes.map((q: any) =>
q.date.getTime(),
),
prices: comp.charts[4].quotes.map((q: any) => q.close),
}
: null,
'1Y': comp.charts[5]
? {
timestamps: comp.charts[5].quotes.map((q: any) =>
q.date.getTime(),
),
prices: comp.charts[5].quotes.map((q: any) => q.close),
}
: null,
MAX: comp.charts[6]
? {
timestamps: comp.charts[6].quotes.map((q: any) =>
q.date.getTime(),
),
prices: comp.charts[6].quotes.map((q: any) => q.close),
}
: null,
},
}))
: null,
};
return {
type: 'stock',
llmContext: `Current price of ${stockData.shortName} (${stockData.symbol}) is ${stockData.regularMarketPrice} ${stockData.currency}. Other details: ${JSON.stringify(
{
marketState: stockData.marketState,
regularMarketChange: stockData.regularMarketChange,
regularMarketChangePercent: stockData.regularMarketChangePercent,
marketCap: stockData.marketCap,
peRatio: stockData.trailingPE,
dividendYield: stockData.dividendYield,
},
)}`,
data: stockData,
};
} catch (error: any) {
return {
type: 'stock',
llmContext: 'Failed to fetch stock data.',
data: {
error: `Error fetching stock data: ${error.message || error}`,
ticker: params.name,
},
};
}
},
};
export default stockWidget;

View File

@@ -0,0 +1,203 @@
import z from 'zod';
import { Widget } from '../types';
import formatChatHistoryAsString from '@/lib/utils/formatHistory';
const schema = z.object({
location: z
.string()
.describe(
'Human-readable location name (e.g., "New York, NY, USA", "London, UK"). Use this OR lat/lon coordinates, never both. Leave empty string if providing coordinates.',
),
lat: z
.number()
.describe(
'Latitude coordinate in decimal degrees (e.g., 40.7128). Only use when location name is empty.',
),
lon: z
.number()
.describe(
'Longitude coordinate in decimal degrees (e.g., -74.0060). Only use when location name is empty.',
),
notPresent: z
.boolean()
.describe('Whether there is no need for the weather widget.'),
});
const systemPrompt = `
<role>
You are a location extractor for weather queries. You will receive a user follow up and a conversation history.
Your task is to determine if the user is asking about weather and extract the location they want weather for.
</role>
<instructions>
- If the user is asking about weather, extract the location name OR coordinates (never both).
- If using location name, set lat and lon to 0.
- If using coordinates, set location to empty string.
- If you cannot determine a valid location or the query is not weather-related, set notPresent to true.
- Location should be specific (city, state/region, country) for best results.
- You have to give the location so that it can be used to fetch weather data, it cannot be left empty unless notPresent is true.
- Make sure to infer short forms of location names (e.g., "NYC" -> "New York City", "LA" -> "Los Angeles").
</instructions>
<output_format>
You must respond in the following JSON format without any extra text, explanations or filler sentences:
{
"location": string,
"lat": number,
"lon": number,
"notPresent": boolean
}
</output_format>
`;
const weatherWidget: Widget = {
type: 'weatherWidget',
shouldExecute: (classification) =>
classification.classification.showWeatherWidget,
execute: async (input) => {
const output = await input.llm.generateObject<typeof schema>({
messages: [
{
role: 'system',
content: systemPrompt,
},
{
role: 'user',
content: `<conversation_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation_history>\n<user_follow_up>\n${input.followUp}\n</user_follow_up>`,
},
],
schema,
});
if (output.notPresent) {
return;
}
const params = output;
try {
if (
params.location === '' &&
(params.lat === undefined || params.lon === undefined)
) {
throw new Error(
'Either location name or both latitude and longitude must be provided.',
);
}
if (params.location !== '') {
const openStreetMapUrl = `https://nominatim.openstreetmap.org/search?q=${encodeURIComponent(params.location)}&format=json&limit=1`;
const locationRes = await fetch(openStreetMapUrl, {
headers: {
'User-Agent': 'Perplexica',
'Content-Type': 'application/json',
},
});
const data = await locationRes.json();
const location = data[0];
if (!location) {
throw new Error(
`Could not find coordinates for location: ${params.location}`,
);
}
const weatherRes = await fetch(
`https://api.open-meteo.com/v1/forecast?latitude=${location.lat}&longitude=${location.lon}&current=temperature_2m,relative_humidity_2m,apparent_temperature,is_day,precipitation,rain,showers,snowfall,weather_code,cloud_cover,pressure_msl,surface_pressure,wind_speed_10m,wind_direction_10m,wind_gusts_10m&hourly=temperature_2m,precipitation_probability,precipitation,weather_code&daily=weather_code,temperature_2m_max,temperature_2m_min,precipitation_sum,precipitation_probability_max&timezone=auto&forecast_days=7`,
{
headers: {
'User-Agent': 'Perplexica',
'Content-Type': 'application/json',
},
},
);
const weatherData = await weatherRes.json();
return {
type: 'weather',
llmContext: `Weather in ${params.location} is ${JSON.stringify(weatherData.current)}`,
data: {
location: params.location,
latitude: location.lat,
longitude: location.lon,
current: weatherData.current,
hourly: {
time: weatherData.hourly.time.slice(0, 24),
temperature_2m: weatherData.hourly.temperature_2m.slice(0, 24),
precipitation_probability:
weatherData.hourly.precipitation_probability.slice(0, 24),
precipitation: weatherData.hourly.precipitation.slice(0, 24),
weather_code: weatherData.hourly.weather_code.slice(0, 24),
},
daily: weatherData.daily,
timezone: weatherData.timezone,
},
};
} else if (params.lat !== undefined && params.lon !== undefined) {
const [weatherRes, locationRes] = await Promise.all([
fetch(
`https://api.open-meteo.com/v1/forecast?latitude=${params.lat}&longitude=${params.lon}&current=temperature_2m,relative_humidity_2m,apparent_temperature,is_day,precipitation,rain,showers,snowfall,weather_code,cloud_cover,pressure_msl,surface_pressure,wind_speed_10m,wind_direction_10m,wind_gusts_10m&hourly=temperature_2m,precipitation_probability,precipitation,weather_code&daily=weather_code,temperature_2m_max,temperature_2m_min,precipitation_sum,precipitation_probability_max&timezone=auto&forecast_days=7`,
{
headers: {
'User-Agent': 'Perplexica',
'Content-Type': 'application/json',
},
},
),
fetch(
`https://nominatim.openstreetmap.org/reverse?lat=${params.lat}&lon=${params.lon}&format=json`,
{
headers: {
'User-Agent': 'Perplexica',
'Content-Type': 'application/json',
},
},
),
]);
const weatherData = await weatherRes.json();
const locationData = await locationRes.json();
return {
type: 'weather',
llmContext: `Weather in ${locationData.display_name} is ${JSON.stringify(weatherData.current)}`,
data: {
location: locationData.display_name,
latitude: params.lat,
longitude: params.lon,
current: weatherData.current,
hourly: {
time: weatherData.hourly.time.slice(0, 24),
temperature_2m: weatherData.hourly.temperature_2m.slice(0, 24),
precipitation_probability:
weatherData.hourly.precipitation_probability.slice(0, 24),
precipitation: weatherData.hourly.precipitation.slice(0, 24),
weather_code: weatherData.hourly.weather_code.slice(0, 24),
},
daily: weatherData.daily,
timezone: weatherData.timezone,
},
};
}
return {
type: 'weather',
llmContext: 'No valid location or coordinates provided.',
data: null,
};
} catch (err) {
return {
type: 'weather',
llmContext: 'Failed to fetch weather data.',
data: {
error: `Error fetching weather data: ${err}`,
},
};
}
},
};
export default weatherWidget;

View File

@@ -0,0 +1,39 @@
import formatChatHistoryAsString from '@/lib/utils/formatHistory';
import { suggestionGeneratorPrompt } from '@/lib/prompts/suggestions';
import { ChatTurnMessage } from '@/lib/types';
import z from 'zod';
import BaseLLM from '@/lib/models/base/llm';
import { i } from 'mathjs';
type SuggestionGeneratorInput = {
chatHistory: ChatTurnMessage[];
};
const schema = z.object({
suggestions: z
.array(z.string())
.describe('List of suggested questions or prompts'),
});
const generateSuggestions = async (
input: SuggestionGeneratorInput,
llm: BaseLLM<any>,
) => {
const res = await llm.generateObject<z.infer<typeof schema>>({
messages: [
{
role: 'system',
content: suggestionGeneratorPrompt,
},
{
role: 'user',
content: `<chat_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</chat_history>`,
},
],
schema,
});
return res.suggestions;
};
export default generateSuggestions;

View File

@@ -1,105 +0,0 @@
import {
RunnableSequence,
RunnableMap,
RunnableLambda,
} from '@langchain/core/runnables';
import { ChatPromptTemplate } from '@langchain/core/prompts';
import formatChatHistoryAsString from '../utils/formatHistory';
import { BaseMessage } from '@langchain/core/messages';
import { StringOutputParser } from '@langchain/core/output_parsers';
import { searchSearxng } from '../searxng';
import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
import LineOutputParser from '../outputParsers/lineOutputParser';
const imageSearchChainPrompt = `
You will be given a conversation below and a follow up question. You need to rephrase the follow-up question so it is a standalone question that can be used by the LLM to search the web for images.
You need to make sure the rephrased question agrees with the conversation and is relevant to the conversation.
Output only the rephrased query wrapped in an XML <query> element. Do not include any explanation or additional text.
`;
type ImageSearchChainInput = {
chat_history: BaseMessage[];
query: string;
};
interface ImageSearchResult {
img_src: string;
url: string;
title: string;
}
const strParser = new StringOutputParser();
const createImageSearchChain = (llm: BaseChatModel) => {
return RunnableSequence.from([
RunnableMap.from({
chat_history: (input: ImageSearchChainInput) => {
return formatChatHistoryAsString(input.chat_history);
},
query: (input: ImageSearchChainInput) => {
return input.query;
},
}),
ChatPromptTemplate.fromMessages([
['system', imageSearchChainPrompt],
[
'user',
'<conversation>\n</conversation>\n<follow_up>\nWhat is a cat?\n</follow_up>',
],
['assistant', '<query>A cat</query>'],
[
'user',
'<conversation>\n</conversation>\n<follow_up>\nWhat is a car? How does it work?\n</follow_up>',
],
['assistant', '<query>Car working</query>'],
[
'user',
'<conversation>\n</conversation>\n<follow_up>\nHow does an AC work?\n</follow_up>',
],
['assistant', '<query>AC working</query>'],
[
'user',
'<conversation>{chat_history}</conversation>\n<follow_up>\n{query}\n</follow_up>',
],
]),
llm,
strParser,
RunnableLambda.from(async (input: string) => {
const queryParser = new LineOutputParser({
key: 'query',
});
return await queryParser.parse(input);
}),
RunnableLambda.from(async (input: string) => {
const res = await searchSearxng(input, {
engines: ['bing images', 'google images'],
});
const images: ImageSearchResult[] = [];
res.results.forEach((result) => {
if (result.img_src && result.url && result.title) {
images.push({
img_src: result.img_src,
url: result.url,
title: result.title,
});
}
});
return images.slice(0, 10);
}),
]);
};
const handleImageSearch = (
input: ImageSearchChainInput,
llm: BaseChatModel,
) => {
const imageSearchChain = createImageSearchChain(llm);
return imageSearchChain.invoke(input);
};
export default handleImageSearch;

View File

@@ -1,55 +0,0 @@
import { RunnableSequence, RunnableMap } from '@langchain/core/runnables';
import ListLineOutputParser from '../outputParsers/listLineOutputParser';
import { PromptTemplate } from '@langchain/core/prompts';
import formatChatHistoryAsString from '../utils/formatHistory';
import { BaseMessage } from '@langchain/core/messages';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { ChatOpenAI } from '@langchain/openai';
const suggestionGeneratorPrompt = `
You are an AI suggestion generator for an AI powered search engine. You will be given a conversation below. You need to generate 4-5 suggestions based on the conversation. The suggestion should be relevant to the conversation that can be used by the user to ask the chat model for more information.
You need to make sure the suggestions are relevant to the conversation and are helpful to the user. Keep a note that the user might use these suggestions to ask a chat model for more information.
Make sure the suggestions are medium in length and are informative and relevant to the conversation.
Provide these suggestions separated by newlines between the XML tags <suggestions> and </suggestions>. For example:
<suggestions>
Tell me more about SpaceX and their recent projects
What is the latest news on SpaceX?
Who is the CEO of SpaceX?
</suggestions>
Conversation:
{chat_history}
`;
type SuggestionGeneratorInput = {
chat_history: BaseMessage[];
};
const outputParser = new ListLineOutputParser({
key: 'suggestions',
});
const createSuggestionGeneratorChain = (llm: BaseChatModel) => {
return RunnableSequence.from([
RunnableMap.from({
chat_history: (input: SuggestionGeneratorInput) =>
formatChatHistoryAsString(input.chat_history),
}),
PromptTemplate.fromTemplate(suggestionGeneratorPrompt),
llm,
outputParser,
]);
};
const generateSuggestions = (
input: SuggestionGeneratorInput,
llm: BaseChatModel,
) => {
(llm as unknown as ChatOpenAI).temperature = 0;
const suggestionGeneratorChain = createSuggestionGeneratorChain(llm);
return suggestionGeneratorChain.invoke(input);
};
export default generateSuggestions;

View File

@@ -1,110 +0,0 @@
import {
RunnableSequence,
RunnableMap,
RunnableLambda,
} from '@langchain/core/runnables';
import { ChatPromptTemplate } from '@langchain/core/prompts';
import formatChatHistoryAsString from '../utils/formatHistory';
import { BaseMessage } from '@langchain/core/messages';
import { StringOutputParser } from '@langchain/core/output_parsers';
import { searchSearxng } from '../searxng';
import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
import LineOutputParser from '../outputParsers/lineOutputParser';
const videoSearchChainPrompt = `
You will be given a conversation below and a follow up question. You need to rephrase the follow-up question so it is a standalone question that can be used by the LLM to search Youtube for videos.
You need to make sure the rephrased question agrees with the conversation and is relevant to the conversation.
Output only the rephrased query wrapped in an XML <query> element. Do not include any explanation or additional text.
`;
type VideoSearchChainInput = {
chat_history: BaseMessage[];
query: string;
};
interface VideoSearchResult {
img_src: string;
url: string;
title: string;
iframe_src: string;
}
const strParser = new StringOutputParser();
const createVideoSearchChain = (llm: BaseChatModel) => {
return RunnableSequence.from([
RunnableMap.from({
chat_history: (input: VideoSearchChainInput) => {
return formatChatHistoryAsString(input.chat_history);
},
query: (input: VideoSearchChainInput) => {
return input.query;
},
}),
ChatPromptTemplate.fromMessages([
['system', videoSearchChainPrompt],
[
'user',
'<conversation>\n</conversation>\n<follow_up>\nHow does a car work?\n</follow_up>',
],
['assistant', '<query>How does a car work?</query>'],
[
'user',
'<conversation>\n</conversation>\n<follow_up>\nWhat is the theory of relativity?\n</follow_up>',
],
['assistant', '<query>Theory of relativity</query>'],
[
'user',
'<conversation>\n</conversation>\n<follow_up>\nHow does an AC work?\n</follow_up>',
],
['assistant', '<query>AC working</query>'],
[
'user',
'<conversation>{chat_history}</conversation>\n<follow_up>\n{query}\n</follow_up>',
],
]),
llm,
strParser,
RunnableLambda.from(async (input: string) => {
const queryParser = new LineOutputParser({
key: 'query',
});
return await queryParser.parse(input);
}),
RunnableLambda.from(async (input: string) => {
const res = await searchSearxng(input, {
engines: ['youtube'],
});
const videos: VideoSearchResult[] = [];
res.results.forEach((result) => {
if (
result.thumbnail &&
result.url &&
result.title &&
result.iframe_src
) {
videos.push({
img_src: result.thumbnail,
url: result.url,
title: result.title,
iframe_src: result.iframe_src,
});
}
});
return videos.slice(0, 10);
}),
]);
};
const handleVideoSearch = (
input: VideoSearchChainInput,
llm: BaseChatModel,
) => {
const videoSearchChain = createVideoSearchChain(llm);
return videoSearchChain.invoke(input);
};
export default handleVideoSearch;

View File

@@ -6,11 +6,14 @@ const getClientConfig = (key: string, defaultVal?: any) => {
export const getTheme = () => getClientConfig('theme', 'dark');
export const getAutoImageSearch = () =>
Boolean(getClientConfig('autoImageSearch', 'true'));
export const getAutoVideoSearch = () =>
Boolean(getClientConfig('autoVideoSearch', 'true'));
export const getAutoMediaSearch = () =>
getClientConfig('autoMediaSearch', 'true') === 'true';
export const getSystemInstructions = () =>
getClientConfig('systemInstructions', '');
export const getShowWeatherWidget = () =>
getClientConfig('showWeatherWidget', 'true') === 'true';
export const getShowNewsWidget = () =>
getClientConfig('showNewsWidget', 'true') === 'true';

View File

@@ -13,14 +13,15 @@ class ConfigManager {
currentConfig: Config = {
version: this.configVersion,
setupComplete: false,
general: {},
preferences: {},
personalization: {},
modelProviders: [],
search: {
searxngURL: '',
},
};
uiConfigSections: UIConfigSections = {
general: [
preferences: [
{
name: 'Theme',
key: 'theme',
@@ -40,6 +41,54 @@ class ConfigManager {
default: 'dark',
scope: 'client',
},
{
name: 'Measurement Unit',
key: 'measureUnit',
type: 'select',
options: [
{
name: 'Imperial',
value: 'Imperial',
},
{
name: 'Metric',
value: 'Metric',
},
],
required: false,
description: 'Choose between Metric and Imperial measurement unit.',
default: 'Metric',
scope: 'client',
},
{
name: 'Auto video & image search',
key: 'autoMediaSearch',
type: 'switch',
required: false,
description: 'Automatically search for relevant images and videos.',
default: true,
scope: 'client',
},
{
name: 'Show weather widget',
key: 'showWeatherWidget',
type: 'switch',
required: false,
description: 'Display the weather card on the home screen.',
default: true,
scope: 'client',
},
{
name: 'Show news widget',
key: 'showNewsWidget',
type: 'switch',
required: false,
description: 'Display the recent news card on the home screen.',
default: true,
scope: 'client',
},
],
personalization: [
{
name: 'System Instructions',
key: 'systemInstructions',

View File

@@ -38,11 +38,17 @@ type TextareaUIConfigField = BaseUIConfigField & {
default?: string;
};
type SwitchUIConfigField = BaseUIConfigField & {
type: 'switch';
default?: boolean;
};
type UIConfigField =
| StringUIConfigField
| SelectUIConfigField
| PasswordUIConfigField
| TextareaUIConfigField;
| TextareaUIConfigField
| SwitchUIConfigField;
type ConfigModelProvider = {
id: string;
@@ -57,7 +63,10 @@ type ConfigModelProvider = {
type Config = {
version: number;
setupComplete: boolean;
general: {
preferences: {
[key: string]: any;
};
personalization: {
[key: string]: any;
};
modelProviders: ConfigModelProvider[];
@@ -80,7 +89,8 @@ type ModelProviderUISection = {
};
type UIConfigSections = {
general: UIConfigField[];
preferences: UIConfigField[];
personalization: UIConfigField[];
modelProviders: ModelProviderUISection[];
search: UIConfigField[];
};
@@ -95,4 +105,5 @@ export type {
ModelProviderUISection,
ConfigModelProvider,
TextareaUIConfigField,
SwitchUIConfigField,
};

View File

@@ -18,12 +18,18 @@ db.exec(`
`);
function sanitizeSql(content: string) {
return content
.split(/\r?\n/)
.filter(
(l) => !l.trim().startsWith('-->') && !l.includes('statement-breakpoint'),
const statements = content
.split(/--> statement-breakpoint/g)
.map((stmt) =>
stmt
.split(/\r?\n/)
.filter((l) => !l.trim().startsWith('-->'))
.join('\n')
.trim(),
)
.join('\n');
.filter((stmt) => stmt.length > 0);
return statements;
}
fs.readdirSync(migrationsFolder)
@@ -32,7 +38,7 @@ fs.readdirSync(migrationsFolder)
.forEach((file) => {
const filePath = path.join(migrationsFolder, file);
let content = fs.readFileSync(filePath, 'utf-8');
content = sanitizeSql(content);
const statements = sanitizeSql(content);
const migrationName = file.split('_')[0] || file;
@@ -108,7 +114,12 @@ fs.readdirSync(migrationsFolder)
db.exec('DROP TABLE messages;');
db.exec('ALTER TABLE messages_with_sources RENAME TO messages;');
} else {
db.exec(content);
// Execute each statement separately
statements.forEach((stmt) => {
if (stmt.trim()) {
db.exec(stmt);
}
});
}
db.prepare('INSERT OR IGNORE INTO ran_migrations (name) VALUES (?)').run(

View File

@@ -1,26 +1,23 @@
import { sql } from 'drizzle-orm';
import { text, integer, sqliteTable } from 'drizzle-orm/sqlite-core';
import { Document } from '@langchain/core/documents';
import { Block } from '../types';
export const messages = sqliteTable('messages', {
id: integer('id').primaryKey(),
role: text('type', { enum: ['assistant', 'user', 'source'] }).notNull(),
chatId: text('chatId').notNull(),
createdAt: text('createdAt')
.notNull()
.default(sql`CURRENT_TIMESTAMP`),
messageId: text('messageId').notNull(),
content: text('content'),
sources: text('sources', {
mode: 'json',
})
.$type<Document[]>()
chatId: text('chatId').notNull(),
backendId: text('backendId').notNull(),
query: text('query').notNull(),
createdAt: text('createdAt').notNull(),
responseBlocks: text('responseBlocks', { mode: 'json' })
.$type<Block[]>()
.default(sql`'[]'`),
status: text({ enum: ['answering', 'completed', 'error'] }).default(
'answering',
),
});
interface File {
interface DBFile {
name: string;
fileId: string;
}
@@ -31,6 +28,6 @@ export const chats = sqliteTable('chats', {
createdAt: text('createdAt').notNull(),
focusMode: text('focusMode').notNull(),
files: text('files', { mode: 'json' })
.$type<File[]>()
.$type<DBFile[]>()
.default(sql`'[]'`),
});

View File

@@ -1,13 +1,7 @@
'use client';
import {
AssistantMessage,
ChatTurn,
Message,
SourceMessage,
SuggestionMessage,
UserMessage,
} from '@/components/ChatWindow';
import { Message } from '@/components/ChatWindow';
import { Block } from '@/lib/types';
import {
createContext,
useContext,
@@ -17,24 +11,25 @@ import {
useState,
} from 'react';
import crypto from 'crypto';
import { useSearchParams } from 'next/navigation';
import { useParams, useSearchParams } from 'next/navigation';
import { toast } from 'sonner';
import { getSuggestions } from '../actions';
import { MinimalProvider } from '../models/types';
import { getAutoMediaSearch } from '../config/clientRegistry';
import { applyPatch } from 'rfc6902';
import { Widget } from '@/components/ChatWindow';
export type Section = {
userMessage: UserMessage;
assistantMessage: AssistantMessage | undefined;
parsedAssistantMessage: string | undefined;
speechMessage: string | undefined;
sourceMessage: SourceMessage | undefined;
message: Message;
widgets: Widget[];
parsedTextBlocks: string[];
speechMessage: string;
thinkingEnded: boolean;
suggestions?: string[];
};
type ChatContext = {
messages: Message[];
chatTurns: ChatTurn[];
sections: Section[];
chatHistory: [string, string][];
files: File[];
@@ -48,6 +43,10 @@ type ChatContext = {
messageAppeared: boolean;
isReady: boolean;
hasError: boolean;
chatModelProvider: ChatModelProvider;
embeddingModelProvider: EmbeddingModelProvider;
researchEnded: boolean;
setResearchEnded: (ended: boolean) => void;
setOptimizationMode: (mode: string) => void;
setFocusMode: (mode: string) => void;
setFiles: (files: File[]) => void;
@@ -58,6 +57,8 @@ type ChatContext = {
rewrite?: boolean,
) => Promise<void>;
rewrite: (messageId: string) => void;
setChatModelProvider: (provider: ChatModelProvider) => void;
setEmbeddingModelProvider: (provider: EmbeddingModelProvider) => void;
};
export interface File {
@@ -90,17 +91,6 @@ const checkConfig = async (
'embeddingModelProviderId',
);
const autoImageSearch = localStorage.getItem('autoImageSearch');
const autoVideoSearch = localStorage.getItem('autoVideoSearch');
if (!autoImageSearch) {
localStorage.setItem('autoImageSearch', 'true');
}
if (!autoVideoSearch) {
localStorage.setItem('autoVideoSearch', 'false');
}
const res = await fetch(`/api/providers`, {
headers: {
'Content-Type': 'application/json',
@@ -210,18 +200,26 @@ const loadMessages = async (
setMessages(messages);
const chatTurns = messages.filter(
(msg): msg is ChatTurn => msg.role === 'user' || msg.role === 'assistant',
);
const history: [string, string][] = [];
messages.forEach((msg) => {
history.push(['human', msg.query]);
const history = chatTurns.map((msg) => {
return [msg.role, msg.content];
}) as [string, string][];
const textBlocks = msg.responseBlocks
.filter(
(block): block is Block & { type: 'text' } => block.type === 'text',
)
.map((block) => block.data)
.join('\n');
if (textBlocks) {
history.push(['assistant', textBlocks]);
}
});
console.debug(new Date(), 'app:messages_loaded');
if (chatTurns.length > 0) {
document.title = chatTurns[0].content;
if (messages.length > 0) {
document.title = messages[0].query;
}
const files = data.chat.files.map((file: any) => {
@@ -252,34 +250,36 @@ export const chatContext = createContext<ChatContext>({
loading: false,
messageAppeared: false,
messages: [],
chatTurns: [],
sections: [],
notFound: false,
optimizationMode: '',
chatModelProvider: { key: '', providerId: '' },
embeddingModelProvider: { key: '', providerId: '' },
researchEnded: false,
rewrite: () => {},
sendMessage: async () => {},
setFileIds: () => {},
setFiles: () => {},
setFocusMode: () => {},
setOptimizationMode: () => {},
setChatModelProvider: () => {},
setEmbeddingModelProvider: () => {},
setResearchEnded: () => {},
});
export const ChatProvider = ({
children,
id,
}: {
children: React.ReactNode;
id?: string;
}) => {
export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
const params: { chatId: string } = useParams();
const searchParams = useSearchParams();
const initialMessage = searchParams.get('q');
const [chatId, setChatId] = useState<string | undefined>(id);
const [chatId, setChatId] = useState<string | undefined>(params.chatId);
const [newChatCreated, setNewChatCreated] = useState(false);
const [loading, setLoading] = useState(false);
const [messageAppeared, setMessageAppeared] = useState(false);
const [researchEnded, setResearchEnded] = useState(false);
const [chatHistory, setChatHistory] = useState<[string, string][]>([]);
const [messages, setMessages] = useState<Message[]>([]);
@@ -312,66 +312,44 @@ export const ChatProvider = ({
const messagesRef = useRef<Message[]>([]);
const chatTurns = useMemo((): ChatTurn[] => {
return messages.filter(
(msg): msg is ChatTurn => msg.role === 'user' || msg.role === 'assistant',
);
}, [messages]);
const sections = useMemo<Section[]>(() => {
const sections: Section[] = [];
return messages.map((msg) => {
const textBlocks: string[] = [];
let speechMessage = '';
let thinkingEnded = false;
let suggestions: string[] = [];
messages.forEach((msg, i) => {
if (msg.role === 'user') {
const nextUserMessageIndex = messages.findIndex(
(m, j) => j > i && m.role === 'user',
);
const sourceBlocks = msg.responseBlocks.filter(
(block): block is Block & { type: 'source' } => block.type === 'source',
);
const sources = sourceBlocks.flatMap((block) => block.data);
const aiMessage = messages.find(
(m, j) =>
j > i &&
m.role === 'assistant' &&
(nextUserMessageIndex === -1 || j < nextUserMessageIndex),
) as AssistantMessage | undefined;
const widgetBlocks = msg.responseBlocks
.filter((b) => b.type === 'widget')
.map((b) => b.data) as Widget[];
const sourceMessage = messages.find(
(m, j) =>
j > i &&
m.role === 'source' &&
m.sources &&
(nextUserMessageIndex === -1 || j < nextUserMessageIndex),
) as SourceMessage | undefined;
let thinkingEnded = false;
let processedMessage = aiMessage?.content ?? '';
let speechMessage = aiMessage?.content ?? '';
let suggestions: string[] = [];
if (aiMessage) {
msg.responseBlocks.forEach((block) => {
if (block.type === 'text') {
let processedText = block.data;
const citationRegex = /\[([^\]]+)\]/g;
const regex = /\[(\d+)\]/g;
if (processedMessage.includes('<think>')) {
const openThinkTag =
processedMessage.match(/<think>/g)?.length || 0;
if (processedText.includes('<think>')) {
const openThinkTag = processedText.match(/<think>/g)?.length || 0;
const closeThinkTag =
processedMessage.match(/<\/think>/g)?.length || 0;
processedText.match(/<\/think>/g)?.length || 0;
if (openThinkTag && !closeThinkTag) {
processedMessage += '</think> <a> </a>';
processedText += '</think> <a> </a>';
}
}
if (aiMessage.content.includes('</think>')) {
if (block.data.includes('</think>')) {
thinkingEnded = true;
}
if (
sourceMessage &&
sourceMessage.sources &&
sourceMessage.sources.length > 0
) {
processedMessage = processedMessage.replace(
if (sources.length > 0) {
processedText = processedText.replace(
citationRegex,
(_, capturedContent: string) => {
const numbers = capturedContent
@@ -386,7 +364,7 @@ export const ChatProvider = ({
return `[${numStr}]`;
}
const source = sourceMessage.sources?.[number - 1];
const source = sources[number - 1];
const url = source?.metadata?.url;
if (url) {
@@ -400,37 +378,27 @@ export const ChatProvider = ({
return linksHtml;
},
);
speechMessage = aiMessage.content.replace(regex, '');
speechMessage += block.data.replace(regex, '');
} else {
processedMessage = processedMessage.replace(regex, '');
speechMessage = aiMessage.content.replace(regex, '');
processedText = processedText.replace(regex, '');
speechMessage += block.data.replace(regex, '');
}
const suggestionMessage = messages.find(
(m, j) =>
j > i &&
m.role === 'suggestion' &&
(nextUserMessageIndex === -1 || j < nextUserMessageIndex),
) as SuggestionMessage | undefined;
if (suggestionMessage && suggestionMessage.suggestions.length > 0) {
suggestions = suggestionMessage.suggestions;
}
textBlocks.push(processedText);
} else if (block.type === 'suggestion') {
suggestions = block.data;
}
});
sections.push({
userMessage: msg,
assistantMessage: aiMessage,
sourceMessage: sourceMessage,
parsedAssistantMessage: processedMessage,
speechMessage,
thinkingEnded,
suggestions: suggestions,
});
}
return {
message: msg,
parsedTextBlocks: textBlocks,
speechMessage,
thinkingEnded,
suggestions,
widgets: widgetBlocks,
};
});
return sections;
}, [messages]);
useEffect(() => {
@@ -443,6 +411,19 @@ export const ChatProvider = ({
// eslint-disable-next-line react-hooks/exhaustive-deps
}, []);
useEffect(() => {
if (params.chatId && params.chatId !== chatId) {
setChatId(params.chatId);
setMessages([]);
setChatHistory([]);
setFiles([]);
setFileIds([]);
setIsMessagesLoaded(false);
setNotFound(false);
setNewChatCreated(false);
}
}, [params.chatId, chatId]);
useEffect(() => {
if (
chatId &&
@@ -466,7 +447,7 @@ export const ChatProvider = ({
setChatId(crypto.randomBytes(20).toString('hex'));
}
// eslint-disable-next-line react-hooks/exhaustive-deps
}, []);
}, [chatId, isMessagesLoaded, newChatCreated, messages.length]);
useEffect(() => {
messagesRef.current = messages;
@@ -483,24 +464,17 @@ export const ChatProvider = ({
const rewrite = (messageId: string) => {
const index = messages.findIndex((msg) => msg.messageId === messageId);
const chatTurnsIndex = chatTurns.findIndex(
(msg) => msg.messageId === messageId,
);
if (index === -1) return;
const message = chatTurns[chatTurnsIndex - 1];
setMessages((prev) => prev.slice(0, index));
setMessages((prev) => {
return [
...prev.slice(0, messages.length > 2 ? messages.indexOf(message) : 0),
];
});
setChatHistory((prev) => {
return [...prev.slice(0, chatTurns.length > 2 ? chatTurnsIndex - 1 : 0)];
return prev.slice(0, index * 2);
});
sendMessage(message.content, message.messageId, true);
const messageToRewrite = messages[index];
sendMessage(messageToRewrite.query, messageToRewrite.messageId, true);
};
useEffect(() => {
@@ -519,142 +493,215 @@ export const ChatProvider = ({
messageId,
rewrite = false,
) => {
if (loading) return;
if (loading || !message) return;
setLoading(true);
setResearchEnded(false);
setMessageAppeared(false);
if (messages.length <= 1) {
window.history.replaceState(null, '', `/c/${chatId}`);
}
let recievedMessage = '';
let added = false;
messageId = messageId ?? crypto.randomBytes(7).toString('hex');
const backendId = crypto.randomBytes(20).toString('hex');
setMessages((prevMessages) => [
...prevMessages,
{
content: message,
messageId: messageId,
chatId: chatId!,
role: 'user',
createdAt: new Date(),
},
]);
const newMessage: Message = {
messageId,
chatId: chatId!,
backendId,
query: message,
responseBlocks: [],
status: 'answering',
createdAt: new Date(),
};
setMessages((prevMessages) => [...prevMessages, newMessage]);
const receivedTextRef = { current: '' };
const messageHandler = async (data: any) => {
if (data.type === 'error') {
toast.error(data.data);
setLoading(false);
setMessages((prev) =>
prev.map((msg) =>
msg.messageId === messageId
? { ...msg, status: 'error' as const }
: msg,
),
);
return;
}
if (data.type === 'researchComplete') {
setResearchEnded(true);
if (
newMessage.responseBlocks.find(
(b) => b.type === 'source' && b.data.length > 0,
)
) {
setMessageAppeared(true);
}
}
if (data.type === 'block') {
setMessages((prev) =>
prev.map((msg) => {
if (msg.messageId === messageId) {
return {
...msg,
responseBlocks: [...msg.responseBlocks, data.block],
};
}
return msg;
}),
);
}
if (data.type === 'updateBlock') {
setMessages((prev) =>
prev.map((msg) => {
if (msg.messageId === messageId) {
const updatedBlocks = msg.responseBlocks.map((block) => {
if (block.id === data.blockId) {
const updatedBlock = { ...block };
applyPatch(updatedBlock, data.patch);
return updatedBlock;
}
return block;
});
return { ...msg, responseBlocks: updatedBlocks };
}
return msg;
}),
);
}
if (data.type === 'sources') {
setMessages((prevMessages) => [
...prevMessages,
{
messageId: data.messageId,
chatId: chatId!,
role: 'source',
sources: data.data,
createdAt: new Date(),
},
]);
const sourceBlock: Block = {
id: crypto.randomBytes(7).toString('hex'),
type: 'source',
data: data.data,
};
setMessages((prev) =>
prev.map((msg) => {
if (msg.messageId === messageId) {
return {
...msg,
responseBlocks: [...msg.responseBlocks, sourceBlock],
};
}
return msg;
}),
);
if (data.data.length > 0) {
setMessageAppeared(true);
}
}
if (data.type === 'message') {
if (!added) {
setMessages((prevMessages) => [
...prevMessages,
{
content: data.data,
messageId: data.messageId,
chatId: chatId!,
role: 'assistant',
createdAt: new Date(),
},
]);
added = true;
setMessageAppeared(true);
} else {
setMessages((prev) =>
prev.map((message) => {
if (
message.messageId === data.messageId &&
message.role === 'assistant'
) {
return { ...message, content: message.content + data.data };
}
receivedTextRef.current += data.data;
return message;
}),
);
}
recievedMessage += data.data;
setMessages((prev) =>
prev.map((msg) => {
if (msg.messageId === messageId) {
const existingTextBlockIndex = msg.responseBlocks.findIndex(
(b) => b.type === 'text',
);
if (existingTextBlockIndex >= 0) {
const updatedBlocks = [...msg.responseBlocks];
const existingBlock = updatedBlocks[
existingTextBlockIndex
] as Block & { type: 'text' };
updatedBlocks[existingTextBlockIndex] = {
...existingBlock,
data: existingBlock.data + data.data,
};
return { ...msg, responseBlocks: updatedBlocks };
} else {
const textBlock: Block = {
id: crypto.randomBytes(7).toString('hex'),
type: 'text',
data: data.data,
};
return {
...msg,
responseBlocks: [...msg.responseBlocks, textBlock],
};
}
}
return msg;
}),
);
setMessageAppeared(true);
}
if (data.type === 'messageEnd') {
setChatHistory((prevHistory) => [
...prevHistory,
const newHistory: [string, string][] = [
...chatHistory,
['human', message],
['assistant', recievedMessage],
]);
['assistant', receivedTextRef.current],
];
setChatHistory(newHistory);
setMessages((prev) =>
prev.map((msg) =>
msg.messageId === messageId
? { ...msg, status: 'completed' as const }
: msg,
),
);
setLoading(false);
const lastMsg = messagesRef.current[messagesRef.current.length - 1];
const autoImageSearch = localStorage.getItem('autoImageSearch');
const autoVideoSearch = localStorage.getItem('autoVideoSearch');
const autoMediaSearch = getAutoMediaSearch();
if (autoImageSearch === 'true') {
if (autoMediaSearch) {
document
.getElementById(`search-images-${lastMsg.messageId}`)
?.click();
}
if (autoVideoSearch === 'true') {
document
.getElementById(`search-videos-${lastMsg.messageId}`)
?.click();
}
/* Check if there are sources after message id's index and no suggestions */
const userMessageIndex = messagesRef.current.findIndex(
(msg) => msg.messageId === messageId && msg.role === 'user',
// Check if there are sources and no suggestions
const currentMsg = messagesRef.current.find(
(msg) => msg.messageId === messageId,
);
const sourceMessage = messagesRef.current.find(
(msg, i) => i > userMessageIndex && msg.role === 'source',
) as SourceMessage | undefined;
const suggestionMessageIndex = messagesRef.current.findIndex(
(msg, i) => i > userMessageIndex && msg.role === 'suggestion',
const hasSourceBlocks = currentMsg?.responseBlocks.some(
(block) => block.type === 'source' && block.data.length > 0,
);
const hasSuggestions = currentMsg?.responseBlocks.some(
(block) => block.type === 'suggestion',
);
if (
sourceMessage &&
sourceMessage.sources.length > 0 &&
suggestionMessageIndex == -1
) {
const suggestions = await getSuggestions(messagesRef.current);
setMessages((prev) => {
return [
...prev,
{
role: 'suggestion',
suggestions: suggestions,
chatId: chatId!,
createdAt: new Date(),
messageId: crypto.randomBytes(7).toString('hex'),
},
];
});
if (hasSourceBlocks && !hasSuggestions) {
const suggestions = await getSuggestions(newHistory);
const suggestionBlock: Block = {
id: crypto.randomBytes(7).toString('hex'),
type: 'suggestion',
data: suggestions,
};
setMessages((prev) =>
prev.map((msg) => {
if (msg.messageId === messageId) {
return {
...msg,
responseBlocks: [...msg.responseBlocks, suggestionBlock],
};
}
return msg;
}),
);
}
}
};
@@ -723,7 +770,6 @@ export const ChatProvider = ({
<chatContext.Provider
value={{
messages,
chatTurns,
sections,
chatHistory,
files,
@@ -743,6 +789,12 @@ export const ChatProvider = ({
setOptimizationMode,
rewrite,
sendMessage,
setChatModelProvider,
chatModelProvider,
embeddingModelProvider,
setEmbeddingModelProvider,
researchEnded,
setResearchEnded,
}}
>
{children}

View File

@@ -1,76 +0,0 @@
import { Embeddings, type EmbeddingsParams } from '@langchain/core/embeddings';
import { chunkArray } from '@langchain/core/utils/chunk_array';
export interface HuggingFaceTransformersEmbeddingsParams
extends EmbeddingsParams {
modelName: string;
model: string;
timeout?: number;
batchSize?: number;
stripNewLines?: boolean;
}
export class HuggingFaceTransformersEmbeddings
extends Embeddings
implements HuggingFaceTransformersEmbeddingsParams
{
modelName = 'Xenova/all-MiniLM-L6-v2';
model = 'Xenova/all-MiniLM-L6-v2';
batchSize = 512;
stripNewLines = true;
timeout?: number;
constructor(fields?: Partial<HuggingFaceTransformersEmbeddingsParams>) {
super(fields ?? {});
this.modelName = fields?.model ?? fields?.modelName ?? this.model;
this.model = this.modelName;
this.stripNewLines = fields?.stripNewLines ?? this.stripNewLines;
this.timeout = fields?.timeout;
}
async embedDocuments(texts: string[]): Promise<number[][]> {
const batches = chunkArray(
this.stripNewLines ? texts.map((t) => t.replace(/\n/g, ' ')) : texts,
this.batchSize,
);
const batchRequests = batches.map((batch) => this.runEmbedding(batch));
const batchResponses = await Promise.all(batchRequests);
const embeddings: number[][] = [];
for (let i = 0; i < batchResponses.length; i += 1) {
const batchResponse = batchResponses[i];
for (let j = 0; j < batchResponse.length; j += 1) {
embeddings.push(batchResponse[j]);
}
}
return embeddings;
}
async embedQuery(text: string): Promise<number[]> {
const data = await this.runEmbedding([
this.stripNewLines ? text.replace(/\n/g, ' ') : text,
]);
return data[0];
}
private async runEmbedding(texts: string[]) {
const { pipeline } = await import('@huggingface/transformers');
const pipe = await pipeline('feature-extraction', this.model);
return this.caller.call(async () => {
const output = await pipe(texts, { pooling: 'mean', normalize: true });
return output.tolist();
});
}
}

View File

@@ -0,0 +1,9 @@
import { Chunk } from '@/lib/types';
abstract class BaseEmbedding<CONFIG> {
constructor(protected config: CONFIG) {}
abstract embedText(texts: string[]): Promise<number[][]>;
abstract embedChunks(chunks: Chunk[]): Promise<number[][]>;
}
export default BaseEmbedding;

View File

@@ -0,0 +1,22 @@
import z from 'zod';
import {
GenerateObjectInput,
GenerateOptions,
GenerateTextInput,
GenerateTextOutput,
StreamTextOutput,
} from '../types';
abstract class BaseLLM<CONFIG> {
constructor(protected config: CONFIG) {}
abstract generateText(input: GenerateTextInput): Promise<GenerateTextOutput>;
abstract streamText(
input: GenerateTextInput,
): AsyncGenerator<StreamTextOutput>;
abstract generateObject<T>(input: GenerateObjectInput): Promise<z.infer<T>>;
abstract streamObject<T>(
input: GenerateObjectInput,
): AsyncGenerator<Partial<z.infer<T>>>;
}
export default BaseLLM;

View File

@@ -1,7 +1,7 @@
import { Embeddings } from '@langchain/core/embeddings';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import { ModelList, ProviderMetadata } from '../types';
import { UIConfigField } from '@/lib/config/types';
import BaseLLM from './llm';
import BaseEmbedding from './embedding';
abstract class BaseModelProvider<CONFIG> {
constructor(
@@ -11,8 +11,8 @@ abstract class BaseModelProvider<CONFIG> {
) {}
abstract getDefaultModels(): Promise<ModelList>;
abstract getModelList(): Promise<ModelList>;
abstract loadChatModel(modelName: string): Promise<BaseChatModel>;
abstract loadEmbeddingModel(modelName: string): Promise<Embeddings>;
abstract loadChatModel(modelName: string): Promise<BaseLLM<any>>;
abstract loadEmbeddingModel(modelName: string): Promise<BaseEmbedding<any>>;
static getProviderConfigFields(): UIConfigField[] {
throw new Error('Method not implemented.');
}

View File

@@ -1,152 +0,0 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import BaseModelProvider from './baseProvider';
import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
import { Embeddings } from '@langchain/core/embeddings';
import { UIConfigField } from '@/lib/config/types';
import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
interface AimlConfig {
apiKey: string;
}
const providerConfigFields: UIConfigField[] = [
{
type: 'password',
name: 'API Key',
key: 'apiKey',
description: 'Your AI/ML API key',
required: true,
placeholder: 'AI/ML API Key',
env: 'AIML_API_KEY',
scope: 'server',
},
];
class AimlProvider extends BaseModelProvider<AimlConfig> {
constructor(id: string, name: string, config: AimlConfig) {
super(id, name, config);
}
async getDefaultModels(): Promise<ModelList> {
try {
const res = await fetch('https://api.aimlapi.com/models', {
method: 'GET',
headers: {
'Content-Type': 'application/json',
Authorization: `Bearer ${this.config.apiKey}`,
},
});
const data = await res.json();
const chatModels: Model[] = data.data
.filter((m: any) => m.type === 'chat-completion')
.map((m: any) => {
return {
name: m.id,
key: m.id,
};
});
const embeddingModels: Model[] = data.data
.filter((m: any) => m.type === 'embedding')
.map((m: any) => {
return {
name: m.id,
key: m.id,
};
});
return {
embedding: embeddingModels,
chat: chatModels,
};
} catch (err) {
if (err instanceof TypeError) {
throw new Error(
'Error connecting to AI/ML API. Please ensure your API key is correct and the service is available.',
);
}
throw err;
}
}
async getModelList(): Promise<ModelList> {
const defaultModels = await this.getDefaultModels();
const configProvider = getConfiguredModelProviderById(this.id)!;
return {
embedding: [
...defaultModels.embedding,
...configProvider.embeddingModels,
],
chat: [...defaultModels.chat, ...configProvider.chatModels],
};
}
async loadChatModel(key: string): Promise<BaseChatModel> {
const modelList = await this.getModelList();
const exists = modelList.chat.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading AI/ML API Chat Model. Invalid Model Selected',
);
}
return new ChatOpenAI({
apiKey: this.config.apiKey,
temperature: 0.7,
model: key,
configuration: {
baseURL: 'https://api.aimlapi.com',
},
});
}
async loadEmbeddingModel(key: string): Promise<Embeddings> {
const modelList = await this.getModelList();
const exists = modelList.embedding.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading AI/ML API Embedding Model. Invalid Model Selected.',
);
}
return new OpenAIEmbeddings({
apiKey: this.config.apiKey,
model: key,
configuration: {
baseURL: 'https://api.aimlapi.com',
},
});
}
static parseAndValidate(raw: any): AimlConfig {
if (!raw || typeof raw !== 'object')
throw new Error('Invalid config provided. Expected object');
if (!raw.apiKey)
throw new Error('Invalid config provided. API key must be provided');
return {
apiKey: String(raw.apiKey),
};
}
static getProviderConfigFields(): UIConfigField[] {
return providerConfigFields;
}
static getProviderMetadata(): ProviderMetadata {
return {
key: 'aiml',
name: 'AI/ML API',
};
}
}
export default AimlProvider;

View File

@@ -1,115 +0,0 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import BaseModelProvider from './baseProvider';
import { ChatAnthropic } from '@langchain/anthropic';
import { Embeddings } from '@langchain/core/embeddings';
import { UIConfigField } from '@/lib/config/types';
import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
interface AnthropicConfig {
apiKey: string;
}
const providerConfigFields: UIConfigField[] = [
{
type: 'password',
name: 'API Key',
key: 'apiKey',
description: 'Your Anthropic API key',
required: true,
placeholder: 'Anthropic API Key',
env: 'ANTHROPIC_API_KEY',
scope: 'server',
},
];
class AnthropicProvider extends BaseModelProvider<AnthropicConfig> {
constructor(id: string, name: string, config: AnthropicConfig) {
super(id, name, config);
}
async getDefaultModels(): Promise<ModelList> {
const res = await fetch('https://api.anthropic.com/v1/models?limit=999', {
method: 'GET',
headers: {
'x-api-key': this.config.apiKey,
'anthropic-version': '2023-06-01',
'Content-type': 'application/json',
},
});
if (!res.ok) {
throw new Error(`Failed to fetch Anthropic models: ${res.statusText}`);
}
const data = (await res.json()).data;
const models: Model[] = data.map((m: any) => {
return {
key: m.id,
name: m.display_name,
};
});
return {
embedding: [],
chat: models,
};
}
async getModelList(): Promise<ModelList> {
const defaultModels = await this.getDefaultModels();
const configProvider = getConfiguredModelProviderById(this.id)!;
return {
embedding: [],
chat: [...defaultModels.chat, ...configProvider.chatModels],
};
}
async loadChatModel(key: string): Promise<BaseChatModel> {
const modelList = await this.getModelList();
const exists = modelList.chat.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading Anthropic Chat Model. Invalid Model Selected',
);
}
return new ChatAnthropic({
apiKey: this.config.apiKey,
temperature: 0.7,
model: key,
});
}
async loadEmbeddingModel(key: string): Promise<Embeddings> {
throw new Error('Anthropic provider does not support embedding models.');
}
static parseAndValidate(raw: any): AnthropicConfig {
if (!raw || typeof raw !== 'object')
throw new Error('Invalid config provided. Expected object');
if (!raw.apiKey)
throw new Error('Invalid config provided. API key must be provided');
return {
apiKey: String(raw.apiKey),
};
}
static getProviderConfigFields(): UIConfigField[] {
return providerConfigFields;
}
static getProviderMetadata(): ProviderMetadata {
return {
key: 'anthropic',
name: 'Anthropic',
};
}
}
export default AnthropicProvider;

View File

@@ -1,107 +0,0 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import BaseModelProvider from './baseProvider';
import { ChatOpenAI } from '@langchain/openai';
import { Embeddings } from '@langchain/core/embeddings';
import { UIConfigField } from '@/lib/config/types';
import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
interface DeepSeekConfig {
apiKey: string;
}
const defaultChatModels: Model[] = [
{
name: 'Deepseek Chat / DeepSeek V3.2 Exp',
key: 'deepseek-chat',
},
{
name: 'Deepseek Reasoner / DeepSeek V3.2 Exp',
key: 'deepseek-reasoner',
},
];
const providerConfigFields: UIConfigField[] = [
{
type: 'password',
name: 'API Key',
key: 'apiKey',
description: 'Your DeepSeek API key',
required: true,
placeholder: 'DeepSeek API Key',
env: 'DEEPSEEK_API_KEY',
scope: 'server',
},
];
class DeepSeekProvider extends BaseModelProvider<DeepSeekConfig> {
constructor(id: string, name: string, config: DeepSeekConfig) {
super(id, name, config);
}
async getDefaultModels(): Promise<ModelList> {
return {
embedding: [],
chat: defaultChatModels,
};
}
async getModelList(): Promise<ModelList> {
const defaultModels = await this.getDefaultModels();
const configProvider = getConfiguredModelProviderById(this.id)!;
return {
embedding: [],
chat: [...defaultModels.chat, ...configProvider.chatModels],
};
}
async loadChatModel(key: string): Promise<BaseChatModel> {
const modelList = await this.getModelList();
const exists = modelList.chat.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading DeepSeek Chat Model. Invalid Model Selected',
);
}
return new ChatOpenAI({
apiKey: this.config.apiKey,
temperature: 0.7,
model: key,
configuration: {
baseURL: 'https://api.deepseek.com',
},
});
}
async loadEmbeddingModel(key: string): Promise<Embeddings> {
throw new Error('DeepSeek provider does not support embedding models.');
}
static parseAndValidate(raw: any): DeepSeekConfig {
if (!raw || typeof raw !== 'object')
throw new Error('Invalid config provided. Expected object');
if (!raw.apiKey)
throw new Error('Invalid config provided. API key must be provided');
return {
apiKey: String(raw.apiKey),
};
}
static getProviderConfigFields(): UIConfigField[] {
return providerConfigFields;
}
static getProviderMetadata(): ProviderMetadata {
return {
key: 'deepseek',
name: 'Deepseek AI',
};
}
}
export default DeepSeekProvider;

View File

@@ -1,140 +0,0 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import BaseModelProvider from './baseProvider';
import {
ChatGoogleGenerativeAI,
GoogleGenerativeAIEmbeddings,
} from '@langchain/google-genai';
import { Embeddings } from '@langchain/core/embeddings';
import { UIConfigField } from '@/lib/config/types';
import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
interface GeminiConfig {
apiKey: string;
}
const providerConfigFields: UIConfigField[] = [
{
type: 'password',
name: 'API Key',
key: 'apiKey',
description: 'Your Google Gemini API key',
required: true,
placeholder: 'Google Gemini API Key',
env: 'GEMINI_API_KEY',
scope: 'server',
},
];
class GeminiProvider extends BaseModelProvider<GeminiConfig> {
constructor(id: string, name: string, config: GeminiConfig) {
super(id, name, config);
}
async getDefaultModels(): Promise<ModelList> {
const res = await fetch(
`https://generativelanguage.googleapis.com/v1beta/models?key=${this.config.apiKey}`,
{
method: 'GET',
headers: {
'Content-Type': 'application/json',
},
},
);
const data = await res.json();
let defaultEmbeddingModels: Model[] = [];
let defaultChatModels: Model[] = [];
data.models.forEach((m: any) => {
if (m.supportedGenerationMethods.includes('embedText')) {
defaultEmbeddingModels.push({
key: m.name,
name: m.displayName,
});
} else if (m.supportedGenerationMethods.includes('generateContent')) {
defaultChatModels.push({
key: m.name,
name: m.displayName,
});
}
});
return {
embedding: defaultEmbeddingModels,
chat: defaultChatModels,
};
}
async getModelList(): Promise<ModelList> {
const defaultModels = await this.getDefaultModels();
const configProvider = getConfiguredModelProviderById(this.id)!;
return {
embedding: [
...defaultModels.embedding,
...configProvider.embeddingModels,
],
chat: [...defaultModels.chat, ...configProvider.chatModels],
};
}
async loadChatModel(key: string): Promise<BaseChatModel> {
const modelList = await this.getModelList();
const exists = modelList.chat.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading Gemini Chat Model. Invalid Model Selected',
);
}
return new ChatGoogleGenerativeAI({
apiKey: this.config.apiKey,
temperature: 0.7,
model: key,
});
}
async loadEmbeddingModel(key: string): Promise<Embeddings> {
const modelList = await this.getModelList();
const exists = modelList.embedding.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading Gemini Embedding Model. Invalid Model Selected.',
);
}
return new GoogleGenerativeAIEmbeddings({
apiKey: this.config.apiKey,
model: key,
});
}
static parseAndValidate(raw: any): GeminiConfig {
if (!raw || typeof raw !== 'object')
throw new Error('Invalid config provided. Expected object');
if (!raw.apiKey)
throw new Error('Invalid config provided. API key must be provided');
return {
apiKey: String(raw.apiKey),
};
}
static getProviderConfigFields(): UIConfigField[] {
return providerConfigFields;
}
static getProviderMetadata(): ProviderMetadata {
return {
key: 'gemini',
name: 'Google Gemini',
};
}
}
export default GeminiProvider;

View File

@@ -1,118 +0,0 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import BaseModelProvider from './baseProvider';
import { ChatGroq } from '@langchain/groq';
import { Embeddings } from '@langchain/core/embeddings';
import { UIConfigField } from '@/lib/config/types';
import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
interface GroqConfig {
apiKey: string;
}
const providerConfigFields: UIConfigField[] = [
{
type: 'password',
name: 'API Key',
key: 'apiKey',
description: 'Your Groq API key',
required: true,
placeholder: 'Groq API Key',
env: 'GROQ_API_KEY',
scope: 'server',
},
];
class GroqProvider extends BaseModelProvider<GroqConfig> {
constructor(id: string, name: string, config: GroqConfig) {
super(id, name, config);
}
async getDefaultModels(): Promise<ModelList> {
try {
const res = await fetch('https://api.groq.com/openai/v1/models', {
method: 'GET',
headers: {
'Content-Type': 'application/json',
Authorization: `Bearer ${this.config.apiKey}`,
},
});
const data = await res.json();
const models: Model[] = data.data.map((m: any) => {
return {
name: m.id,
key: m.id,
};
});
return {
embedding: [],
chat: models,
};
} catch (err) {
if (err instanceof TypeError) {
throw new Error(
'Error connecting to Groq API. Please ensure your API key is correct and the Groq service is available.',
);
}
throw err;
}
}
async getModelList(): Promise<ModelList> {
const defaultModels = await this.getDefaultModels();
const configProvider = getConfiguredModelProviderById(this.id)!;
return {
embedding: [],
chat: [...defaultModels.chat, ...configProvider.chatModels],
};
}
async loadChatModel(key: string): Promise<BaseChatModel> {
const modelList = await this.getModelList();
const exists = modelList.chat.find((m) => m.key === key);
if (!exists) {
throw new Error('Error Loading Groq Chat Model. Invalid Model Selected');
}
return new ChatGroq({
apiKey: this.config.apiKey,
temperature: 0.7,
model: key,
});
}
async loadEmbeddingModel(key: string): Promise<Embeddings> {
throw new Error('Groq provider does not support embedding models.');
}
static parseAndValidate(raw: any): GroqConfig {
if (!raw || typeof raw !== 'object')
throw new Error('Invalid config provided. Expected object');
if (!raw.apiKey)
throw new Error('Invalid config provided. API key must be provided');
return {
apiKey: String(raw.apiKey),
};
}
static getProviderConfigFields(): UIConfigField[] {
return providerConfigFields;
}
static getProviderMetadata(): ProviderMetadata {
return {
key: 'groq',
name: 'Groq',
};
}
}
export default GroqProvider;

View File

@@ -1,27 +1,11 @@
import { ModelProviderUISection } from '@/lib/config/types';
import { ProviderConstructor } from './baseProvider';
import { ProviderConstructor } from '../base/provider';
import OpenAIProvider from './openai';
import OllamaProvider from './ollama';
import TransformersProvider from './transformers';
import AnthropicProvider from './anthropic';
import GeminiProvider from './gemini';
import GroqProvider from './groq';
import DeepSeekProvider from './deepseek';
import LMStudioProvider from './lmstudio';
import LemonadeProvider from './lemonade';
import AimlProvider from '@/lib/models/providers/aiml';
export const providers: Record<string, ProviderConstructor<any>> = {
openai: OpenAIProvider,
ollama: OllamaProvider,
transformers: TransformersProvider,
anthropic: AnthropicProvider,
gemini: GeminiProvider,
groq: GroqProvider,
deepseek: DeepSeekProvider,
aiml: AimlProvider,
lmstudio: LMStudioProvider,
lemonade: LemonadeProvider,
};
export const getModelProvidersUIConfigSection =

View File

@@ -1,158 +0,0 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import BaseModelProvider from './baseProvider';
import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
import { Embeddings } from '@langchain/core/embeddings';
import { UIConfigField } from '@/lib/config/types';
import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
interface LemonadeConfig {
baseURL: string;
apiKey?: string;
}
const providerConfigFields: UIConfigField[] = [
{
type: 'string',
name: 'Base URL',
key: 'baseURL',
description: 'The base URL for Lemonade API',
required: true,
placeholder: 'https://api.lemonade.ai/v1',
env: 'LEMONADE_BASE_URL',
scope: 'server',
},
{
type: 'password',
name: 'API Key',
key: 'apiKey',
description: 'Your Lemonade API key (optional)',
required: false,
placeholder: 'Lemonade API Key',
env: 'LEMONADE_API_KEY',
scope: 'server',
},
];
class LemonadeProvider extends BaseModelProvider<LemonadeConfig> {
constructor(id: string, name: string, config: LemonadeConfig) {
super(id, name, config);
}
async getDefaultModels(): Promise<ModelList> {
try {
const headers: Record<string, string> = {
'Content-Type': 'application/json',
};
if (this.config.apiKey) {
headers['Authorization'] = `Bearer ${this.config.apiKey}`;
}
const res = await fetch(`${this.config.baseURL}/models`, {
method: 'GET',
headers,
});
const data = await res.json();
const models: Model[] = data.data.map((m: any) => {
return {
name: m.id,
key: m.id,
};
});
return {
embedding: models,
chat: models,
};
} catch (err) {
if (err instanceof TypeError) {
throw new Error(
'Error connecting to Lemonade API. Please ensure the base URL is correct and the service is available.',
);
}
throw err;
}
}
async getModelList(): Promise<ModelList> {
const defaultModels = await this.getDefaultModels();
const configProvider = getConfiguredModelProviderById(this.id)!;
return {
embedding: [
...defaultModels.embedding,
...configProvider.embeddingModels,
],
chat: [...defaultModels.chat, ...configProvider.chatModels],
};
}
async loadChatModel(key: string): Promise<BaseChatModel> {
const modelList = await this.getModelList();
const exists = modelList.chat.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading Lemonade Chat Model. Invalid Model Selected',
);
}
return new ChatOpenAI({
apiKey: this.config.apiKey || 'not-needed',
temperature: 0.7,
model: key,
configuration: {
baseURL: this.config.baseURL,
},
});
}
async loadEmbeddingModel(key: string): Promise<Embeddings> {
const modelList = await this.getModelList();
const exists = modelList.embedding.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading Lemonade Embedding Model. Invalid Model Selected.',
);
}
return new OpenAIEmbeddings({
apiKey: this.config.apiKey || 'not-needed',
model: key,
configuration: {
baseURL: this.config.baseURL,
},
});
}
static parseAndValidate(raw: any): LemonadeConfig {
if (!raw || typeof raw !== 'object')
throw new Error('Invalid config provided. Expected object');
if (!raw.baseURL)
throw new Error('Invalid config provided. Base URL must be provided');
return {
baseURL: String(raw.baseURL),
apiKey: raw.apiKey ? String(raw.apiKey) : undefined,
};
}
static getProviderConfigFields(): UIConfigField[] {
return providerConfigFields;
}
static getProviderMetadata(): ProviderMetadata {
return {
key: 'lemonade',
name: 'Lemonade',
};
}
}
export default LemonadeProvider;

View File

@@ -1,148 +0,0 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import BaseModelProvider from './baseProvider';
import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
import { Embeddings } from '@langchain/core/embeddings';
import { UIConfigField } from '@/lib/config/types';
import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
interface LMStudioConfig {
baseURL: string;
}
const providerConfigFields: UIConfigField[] = [
{
type: 'string',
name: 'Base URL',
key: 'baseURL',
description: 'The base URL for LM Studio server',
required: true,
placeholder: 'http://localhost:1234',
env: 'LM_STUDIO_BASE_URL',
scope: 'server',
},
];
class LMStudioProvider extends BaseModelProvider<LMStudioConfig> {
constructor(id: string, name: string, config: LMStudioConfig) {
super(id, name, config);
}
private normalizeBaseURL(url: string): string {
const trimmed = url.trim().replace(/\/+$/, '');
return trimmed.endsWith('/v1') ? trimmed : `${trimmed}/v1`;
}
async getDefaultModels(): Promise<ModelList> {
try {
const baseURL = this.normalizeBaseURL(this.config.baseURL);
const res = await fetch(`${baseURL}/models`, {
method: 'GET',
headers: {
'Content-Type': 'application/json',
},
});
const data = await res.json();
const models: Model[] = data.data.map((m: any) => {
return {
name: m.id,
key: m.id,
};
});
return {
embedding: models,
chat: models,
};
} catch (err) {
if (err instanceof TypeError) {
throw new Error(
'Error connecting to LM Studio. Please ensure the base URL is correct and the LM Studio server is running.',
);
}
throw err;
}
}
async getModelList(): Promise<ModelList> {
const defaultModels = await this.getDefaultModels();
const configProvider = getConfiguredModelProviderById(this.id)!;
return {
embedding: [
...defaultModels.embedding,
...configProvider.embeddingModels,
],
chat: [...defaultModels.chat, ...configProvider.chatModels],
};
}
async loadChatModel(key: string): Promise<BaseChatModel> {
const modelList = await this.getModelList();
const exists = modelList.chat.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading LM Studio Chat Model. Invalid Model Selected',
);
}
return new ChatOpenAI({
apiKey: 'lm-studio',
temperature: 0.7,
model: key,
streaming: true,
configuration: {
baseURL: this.normalizeBaseURL(this.config.baseURL),
},
});
}
async loadEmbeddingModel(key: string): Promise<Embeddings> {
const modelList = await this.getModelList();
const exists = modelList.embedding.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading LM Studio Embedding Model. Invalid Model Selected.',
);
}
return new OpenAIEmbeddings({
apiKey: 'lm-studio',
model: key,
configuration: {
baseURL: this.normalizeBaseURL(this.config.baseURL),
},
});
}
static parseAndValidate(raw: any): LMStudioConfig {
if (!raw || typeof raw !== 'object')
throw new Error('Invalid config provided. Expected object');
if (!raw.baseURL)
throw new Error('Invalid config provided. Base URL must be provided');
return {
baseURL: String(raw.baseURL),
};
}
static getProviderConfigFields(): UIConfigField[] {
return providerConfigFields;
}
static getProviderMetadata(): ProviderMetadata {
return {
key: 'lmstudio',
name: 'LM Studio',
};
}
}
export default LMStudioProvider;

View File

@@ -1,10 +1,11 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import BaseModelProvider from './baseProvider';
import { ChatOllama, OllamaEmbeddings } from '@langchain/ollama';
import { Embeddings } from '@langchain/core/embeddings';
import { UIConfigField } from '@/lib/config/types';
import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
import BaseModelProvider from '../../base/provider';
import { Model, ModelList, ProviderMetadata } from '../../types';
import BaseLLM from '../../base/llm';
import BaseEmbedding from '../../base/embedding';
import OllamaLLM from './ollamaLLM';
import OllamaEmbedding from './ollamaEmbedding';
interface OllamaConfig {
baseURL: string;
@@ -76,7 +77,7 @@ class OllamaProvider extends BaseModelProvider<OllamaConfig> {
};
}
async loadChatModel(key: string): Promise<BaseChatModel> {
async loadChatModel(key: string): Promise<BaseLLM<any>> {
const modelList = await this.getModelList();
const exists = modelList.chat.find((m) => m.key === key);
@@ -87,14 +88,13 @@ class OllamaProvider extends BaseModelProvider<OllamaConfig> {
);
}
return new ChatOllama({
temperature: 0.7,
return new OllamaLLM({
baseURL: this.config.baseURL,
model: key,
baseUrl: this.config.baseURL,
});
}
async loadEmbeddingModel(key: string): Promise<Embeddings> {
async loadEmbeddingModel(key: string): Promise<BaseEmbedding<any>> {
const modelList = await this.getModelList();
const exists = modelList.embedding.find((m) => m.key === key);
@@ -104,9 +104,9 @@ class OllamaProvider extends BaseModelProvider<OllamaConfig> {
);
}
return new OllamaEmbeddings({
return new OllamaEmbedding({
model: key,
baseUrl: this.config.baseURL,
baseURL: this.config.baseURL,
});
}

View File

@@ -0,0 +1,40 @@
import { Ollama } from 'ollama';
import BaseEmbedding from '../../base/embedding';
import { Chunk } from '@/lib/types';
type OllamaConfig = {
model: string;
baseURL?: string;
};
class OllamaEmbedding extends BaseEmbedding<OllamaConfig> {
ollamaClient: Ollama;
constructor(protected config: OllamaConfig) {
super(config);
this.ollamaClient = new Ollama({
host: this.config.baseURL || 'http://localhost:11434',
});
}
async embedText(texts: string[]): Promise<number[][]> {
const response = await this.ollamaClient.embed({
input: texts,
model: this.config.model,
});
return response.embeddings;
}
async embedChunks(chunks: Chunk[]): Promise<number[][]> {
const response = await this.ollamaClient.embed({
input: chunks.map((c) => c.content),
model: this.config.model,
});
return response.embeddings;
}
}
export default OllamaEmbedding;

View File

@@ -0,0 +1,173 @@
import z from 'zod';
import BaseLLM from '../../base/llm';
import {
GenerateObjectInput,
GenerateOptions,
GenerateTextInput,
GenerateTextOutput,
StreamTextOutput,
} from '../../types';
import { Ollama } from 'ollama';
import { parse } from 'partial-json';
type OllamaConfig = {
baseURL: string;
model: string;
options?: GenerateOptions;
};
const reasoningModels = [
'gpt-oss',
'deepseek-r1',
'qwen3',
'deepseek-v3.1',
'magistral',
];
class OllamaLLM extends BaseLLM<OllamaConfig> {
ollamaClient: Ollama;
constructor(protected config: OllamaConfig) {
super(config);
this.ollamaClient = new Ollama({
host: this.config.baseURL || 'http://localhost:11434',
});
}
async generateText(input: GenerateTextInput): Promise<GenerateTextOutput> {
const res = await this.ollamaClient.chat({
model: this.config.model,
messages: input.messages,
options: {
top_p: input.options?.topP ?? this.config.options?.topP,
temperature:
input.options?.temperature ?? this.config.options?.temperature ?? 0.7,
num_predict: input.options?.maxTokens ?? this.config.options?.maxTokens,
num_ctx: 32000,
frequency_penalty:
input.options?.frequencyPenalty ??
this.config.options?.frequencyPenalty,
presence_penalty:
input.options?.presencePenalty ??
this.config.options?.presencePenalty,
stop:
input.options?.stopSequences ?? this.config.options?.stopSequences,
},
});
return {
content: res.message.content,
additionalInfo: {
reasoning: res.message.thinking,
},
};
}
async *streamText(
input: GenerateTextInput,
): AsyncGenerator<StreamTextOutput> {
const stream = await this.ollamaClient.chat({
model: this.config.model,
messages: input.messages,
stream: true,
options: {
top_p: input.options?.topP ?? this.config.options?.topP,
temperature:
input.options?.temperature ?? this.config.options?.temperature ?? 0.7,
num_ctx: 32000,
num_predict: input.options?.maxTokens ?? this.config.options?.maxTokens,
frequency_penalty:
input.options?.frequencyPenalty ??
this.config.options?.frequencyPenalty,
presence_penalty:
input.options?.presencePenalty ??
this.config.options?.presencePenalty,
stop:
input.options?.stopSequences ?? this.config.options?.stopSequences,
},
});
for await (const chunk of stream) {
yield {
contentChunk: chunk.message.content,
done: chunk.done,
additionalInfo: {
reasoning: chunk.message.thinking,
},
};
}
}
async generateObject<T>(input: GenerateObjectInput): Promise<T> {
const response = await this.ollamaClient.chat({
model: this.config.model,
messages: input.messages,
format: z.toJSONSchema(input.schema),
...(reasoningModels.find((m) => this.config.model.includes(m))
? { think: false }
: {}),
options: {
top_p: input.options?.topP ?? this.config.options?.topP,
temperature:
input.options?.temperature ?? this.config.options?.temperature ?? 0.7,
num_predict: input.options?.maxTokens ?? this.config.options?.maxTokens,
frequency_penalty:
input.options?.frequencyPenalty ??
this.config.options?.frequencyPenalty,
presence_penalty:
input.options?.presencePenalty ??
this.config.options?.presencePenalty,
stop:
input.options?.stopSequences ?? this.config.options?.stopSequences,
},
});
try {
return input.schema.parse(JSON.parse(response.message.content)) as T;
} catch (err) {
throw new Error(`Error parsing response from Ollama: ${err}`);
}
}
async *streamObject<T>(input: GenerateObjectInput): AsyncGenerator<T> {
let recievedObj: string = '';
const stream = await this.ollamaClient.chat({
model: this.config.model,
messages: input.messages,
format: z.toJSONSchema(input.schema),
stream: true,
...(reasoningModels.find((m) => this.config.model.includes(m))
? { think: false }
: {}),
options: {
top_p: input.options?.topP ?? this.config.options?.topP,
temperature:
input.options?.temperature ?? this.config.options?.temperature ?? 0.7,
num_predict: input.options?.maxTokens ?? this.config.options?.maxTokens,
frequency_penalty:
input.options?.frequencyPenalty ??
this.config.options?.frequencyPenalty,
presence_penalty:
input.options?.presencePenalty ??
this.config.options?.presencePenalty,
stop:
input.options?.stopSequences ?? this.config.options?.stopSequences,
},
});
for await (const chunk of stream) {
recievedObj += chunk.message.content;
try {
yield parse(recievedObj) as T;
} catch (err) {
console.log('Error parsing partial object from Ollama:', err);
yield {} as T;
}
}
}
}
export default OllamaLLM;

View File

@@ -1,10 +1,11 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import BaseModelProvider from './baseProvider';
import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
import { Embeddings } from '@langchain/core/embeddings';
import { UIConfigField } from '@/lib/config/types';
import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
import { Model, ModelList, ProviderMetadata } from '../../types';
import OpenAIEmbedding from './openaiEmbedding';
import BaseEmbedding from '../../base/embedding';
import BaseModelProvider from '../../base/provider';
import BaseLLM from '../../base/llm';
import OpenAILLM from './openaiLLM';
interface OpenAIConfig {
apiKey: string;
@@ -145,7 +146,7 @@ class OpenAIProvider extends BaseModelProvider<OpenAIConfig> {
};
}
async loadChatModel(key: string): Promise<BaseChatModel> {
async loadChatModel(key: string): Promise<BaseLLM<any>> {
const modelList = await this.getModelList();
const exists = modelList.chat.find((m) => m.key === key);
@@ -156,17 +157,14 @@ class OpenAIProvider extends BaseModelProvider<OpenAIConfig> {
);
}
return new ChatOpenAI({
return new OpenAILLM({
apiKey: this.config.apiKey,
temperature: 0.7,
model: key,
configuration: {
baseURL: this.config.baseURL,
},
baseURL: this.config.baseURL,
});
}
async loadEmbeddingModel(key: string): Promise<Embeddings> {
async loadEmbeddingModel(key: string): Promise<BaseEmbedding<any>> {
const modelList = await this.getModelList();
const exists = modelList.embedding.find((m) => m.key === key);
@@ -176,12 +174,10 @@ class OpenAIProvider extends BaseModelProvider<OpenAIConfig> {
);
}
return new OpenAIEmbeddings({
return new OpenAIEmbedding({
apiKey: this.config.apiKey,
model: key,
configuration: {
baseURL: this.config.baseURL,
},
baseURL: this.config.baseURL,
});
}

View File

@@ -0,0 +1,42 @@
import OpenAI from 'openai';
import BaseEmbedding from '../../base/embedding';
import { Chunk } from '@/lib/types';
type OpenAIConfig = {
apiKey: string;
model: string;
baseURL?: string;
};
class OpenAIEmbedding extends BaseEmbedding<OpenAIConfig> {
openAIClient: OpenAI;
constructor(protected config: OpenAIConfig) {
super(config);
this.openAIClient = new OpenAI({
apiKey: config.apiKey,
baseURL: config.baseURL,
});
}
async embedText(texts: string[]): Promise<number[][]> {
const response = await this.openAIClient.embeddings.create({
model: this.config.model,
input: texts,
});
return response.data.map((embedding) => embedding.embedding);
}
async embedChunks(chunks: Chunk[]): Promise<number[][]> {
const response = await this.openAIClient.embeddings.create({
model: this.config.model,
input: chunks.map((c) => c.content),
});
return response.data.map((embedding) => embedding.embedding);
}
}
export default OpenAIEmbedding;

View File

@@ -0,0 +1,166 @@
import OpenAI from 'openai';
import BaseLLM from '../../base/llm';
import { zodTextFormat, zodResponseFormat } from 'openai/helpers/zod';
import {
GenerateObjectInput,
GenerateOptions,
GenerateTextInput,
GenerateTextOutput,
StreamTextOutput,
} from '../../types';
import { parse } from 'partial-json';
type OpenAIConfig = {
apiKey: string;
model: string;
baseURL?: string;
options?: GenerateOptions;
};
class OpenAILLM extends BaseLLM<OpenAIConfig> {
openAIClient: OpenAI;
constructor(protected config: OpenAIConfig) {
super(config);
this.openAIClient = new OpenAI({
apiKey: this.config.apiKey,
baseURL: this.config.baseURL || 'https://api.openai.com/v1',
});
}
async generateText(input: GenerateTextInput): Promise<GenerateTextOutput> {
const response = await this.openAIClient.chat.completions.create({
model: this.config.model,
messages: input.messages,
temperature:
input.options?.temperature ?? this.config.options?.temperature ?? 1.0,
top_p: input.options?.topP ?? this.config.options?.topP,
max_completion_tokens:
input.options?.maxTokens ?? this.config.options?.maxTokens,
stop: input.options?.stopSequences ?? this.config.options?.stopSequences,
frequency_penalty:
input.options?.frequencyPenalty ??
this.config.options?.frequencyPenalty,
presence_penalty:
input.options?.presencePenalty ?? this.config.options?.presencePenalty,
});
if (response.choices && response.choices.length > 0) {
return {
content: response.choices[0].message.content!,
additionalInfo: {
finishReason: response.choices[0].finish_reason,
},
};
}
throw new Error('No response from OpenAI');
}
async *streamText(
input: GenerateTextInput,
): AsyncGenerator<StreamTextOutput> {
const stream = await this.openAIClient.chat.completions.create({
model: this.config.model,
messages: input.messages,
temperature:
input.options?.temperature ?? this.config.options?.temperature ?? 1.0,
top_p: input.options?.topP ?? this.config.options?.topP,
max_completion_tokens:
input.options?.maxTokens ?? this.config.options?.maxTokens,
stop: input.options?.stopSequences ?? this.config.options?.stopSequences,
frequency_penalty:
input.options?.frequencyPenalty ??
this.config.options?.frequencyPenalty,
presence_penalty:
input.options?.presencePenalty ?? this.config.options?.presencePenalty,
stream: true,
});
for await (const chunk of stream) {
if (chunk.choices && chunk.choices.length > 0) {
yield {
contentChunk: chunk.choices[0].delta.content || '',
done: chunk.choices[0].finish_reason !== null,
additionalInfo: {
finishReason: chunk.choices[0].finish_reason,
},
};
}
}
}
async generateObject<T>(input: GenerateObjectInput): Promise<T> {
const response = await this.openAIClient.chat.completions.parse({
messages: input.messages,
model: this.config.model,
temperature:
input.options?.temperature ?? this.config.options?.temperature ?? 1.0,
top_p: input.options?.topP ?? this.config.options?.topP,
max_completion_tokens:
input.options?.maxTokens ?? this.config.options?.maxTokens,
stop: input.options?.stopSequences ?? this.config.options?.stopSequences,
frequency_penalty:
input.options?.frequencyPenalty ??
this.config.options?.frequencyPenalty,
presence_penalty:
input.options?.presencePenalty ?? this.config.options?.presencePenalty,
response_format: zodResponseFormat(input.schema, 'object'),
});
if (response.choices && response.choices.length > 0) {
try {
return input.schema.parse(response.choices[0].message.parsed) as T;
} catch (err) {
throw new Error(`Error parsing response from OpenAI: ${err}`);
}
}
throw new Error('No response from OpenAI');
}
async *streamObject<T>(input: GenerateObjectInput): AsyncGenerator<T> {
let recievedObj: string = '';
const stream = this.openAIClient.responses.stream({
model: this.config.model,
input: input.messages,
temperature:
input.options?.temperature ?? this.config.options?.temperature ?? 1.0,
top_p: input.options?.topP ?? this.config.options?.topP,
max_completion_tokens:
input.options?.maxTokens ?? this.config.options?.maxTokens,
stop: input.options?.stopSequences ?? this.config.options?.stopSequences,
frequency_penalty:
input.options?.frequencyPenalty ??
this.config.options?.frequencyPenalty,
presence_penalty:
input.options?.presencePenalty ?? this.config.options?.presencePenalty,
text: {
format: zodTextFormat(input.schema, 'object'),
},
});
for await (const chunk of stream) {
if (chunk.type === 'response.output_text.delta' && chunk.delta) {
recievedObj += chunk.delta;
try {
yield parse(recievedObj) as T;
} catch (err) {
console.log('Error parsing partial object from OpenAI:', err);
yield {} as T;
}
} else if (chunk.type === 'response.output_text.done' && chunk.text) {
try {
yield parse(chunk.text) as T;
} catch (err) {
throw new Error(`Error parsing response from OpenAI: ${err}`);
}
}
}
}
}
export default OpenAILLM;

View File

@@ -1,88 +0,0 @@
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Model, ModelList, ProviderMetadata } from '../types';
import BaseModelProvider from './baseProvider';
import { Embeddings } from '@langchain/core/embeddings';
import { UIConfigField } from '@/lib/config/types';
import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
import { HuggingFaceTransformersEmbeddings } from '@/lib/huggingfaceTransformer';
interface TransformersConfig {}
const defaultEmbeddingModels: Model[] = [
{
name: 'all-MiniLM-L6-v2',
key: 'Xenova/all-MiniLM-L6-v2',
},
{
name: 'mxbai-embed-large-v1',
key: 'mixedbread-ai/mxbai-embed-large-v1',
},
{
name: 'nomic-embed-text-v1',
key: 'Xenova/nomic-embed-text-v1',
},
];
const providerConfigFields: UIConfigField[] = [];
class TransformersProvider extends BaseModelProvider<TransformersConfig> {
constructor(id: string, name: string, config: TransformersConfig) {
super(id, name, config);
}
async getDefaultModels(): Promise<ModelList> {
return {
embedding: [...defaultEmbeddingModels],
chat: [],
};
}
async getModelList(): Promise<ModelList> {
const defaultModels = await this.getDefaultModels();
const configProvider = getConfiguredModelProviderById(this.id)!;
return {
embedding: [
...defaultModels.embedding,
...configProvider.embeddingModels,
],
chat: [],
};
}
async loadChatModel(key: string): Promise<BaseChatModel> {
throw new Error('Transformers Provider does not support chat models.');
}
async loadEmbeddingModel(key: string): Promise<Embeddings> {
const modelList = await this.getModelList();
const exists = modelList.embedding.find((m) => m.key === key);
if (!exists) {
throw new Error(
'Error Loading OpenAI Embedding Model. Invalid Model Selected.',
);
}
return new HuggingFaceTransformersEmbeddings({
model: key,
});
}
static parseAndValidate(raw: any): TransformersConfig {
return {};
}
static getProviderConfigFields(): UIConfigField[] {
return providerConfigFields;
}
static getProviderMetadata(): ProviderMetadata {
return {
key: 'transformers',
name: 'Transformers',
};
}
}
export default TransformersProvider;

View File

@@ -1,7 +1,5 @@
import { ConfigModelProvider } from '../config/types';
import BaseModelProvider, {
createProviderInstance,
} from './providers/baseProvider';
import BaseModelProvider, { createProviderInstance } from './base/provider';
import { getConfiguredModelProviders } from '../config/serverRegistry';
import { providers } from './providers';
import { MinimalProvider, ModelList } from './types';

View File

@@ -1,3 +1,6 @@
import z from 'zod';
import { ChatTurnMessage } from '../types';
type Model = {
name: string;
key: string;
@@ -25,10 +28,59 @@ type ModelWithProvider = {
providerId: string;
};
type GenerateOptions = {
temperature?: number;
maxTokens?: number;
topP?: number;
stopSequences?: string[];
frequencyPenalty?: number;
presencePenalty?: number;
};
type GenerateTextInput = {
messages: ChatTurnMessage[];
options?: GenerateOptions;
};
type GenerateTextOutput = {
content: string;
additionalInfo?: Record<string, any>;
};
type StreamTextOutput = {
contentChunk: string;
additionalInfo?: Record<string, any>;
done?: boolean;
};
type GenerateObjectInput = {
schema: z.ZodTypeAny;
messages: ChatTurnMessage[];
options?: GenerateOptions;
};
type GenerateObjectOutput<T> = {
object: T;
additionalInfo?: Record<string, any>;
};
type StreamObjectOutput<T> = {
objectChunk: Partial<T>;
additionalInfo?: Record<string, any>;
done?: boolean;
};
export type {
Model,
ModelList,
ProviderMetadata,
MinimalProvider,
ModelWithProvider,
GenerateOptions,
GenerateTextInput,
GenerateTextOutput,
StreamTextOutput,
GenerateObjectInput,
GenerateObjectOutput,
StreamObjectOutput,
};

View File

@@ -1,48 +0,0 @@
import { BaseOutputParser } from '@langchain/core/output_parsers';
interface LineOutputParserArgs {
key?: string;
}
class LineOutputParser extends BaseOutputParser<string | undefined> {
private key = 'questions';
constructor(args?: LineOutputParserArgs) {
super();
this.key = args?.key ?? this.key;
}
static lc_name() {
return 'LineOutputParser';
}
lc_namespace = ['langchain', 'output_parsers', 'line_output_parser'];
async parse(text: string): Promise<string | undefined> {
text = text.trim() || '';
const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
const startKeyIndex = text.indexOf(`<${this.key}>`);
const endKeyIndex = text.indexOf(`</${this.key}>`);
if (startKeyIndex === -1 || endKeyIndex === -1) {
return undefined;
}
const questionsStartIndex =
startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length;
const questionsEndIndex = endKeyIndex === -1 ? text.length : endKeyIndex;
const line = text
.slice(questionsStartIndex, questionsEndIndex)
.trim()
.replace(regex, '');
return line;
}
getFormatInstructions(): string {
throw new Error('Not implemented.');
}
}
export default LineOutputParser;

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