Compare commits

50 Commits

Author SHA1 Message Date
ItzCrazyKns
8e683d266a feat(package): bump version 2025-02-15 12:12:57 +05:30
ItzCrazyKns
e9ab425cee feat(sample-config): remove unused field 2025-02-15 11:34:14 +05:30
ItzCrazyKns
811c0c6fe1 Merge branch 'master' of https://github.com/ItzCrazyKns/Perplexica 2025-02-15 11:31:20 +05:30
ItzCrazyKns
cab1aa705c feat(settings): add new settings page 2025-02-15 11:31:08 +05:30
ItzCrazyKns
5cbc512322 feat(app): add auto video & image search 2025-02-15 11:29:59 +05:30
ItzCrazyKns
41d056e755 feat(handlers): use new custom openai 2025-02-15 11:29:08 +05:30
ItzCrazyKns
07dc7d7649 feat(config): update config & custom openai 2025-02-15 11:26:38 +05:30
ItzCrazyKns
7ec201d011 Merge pull request #599 from data5650/patch-1
feat: add Gemini 2.0 Flash Exp models
2025-02-07 11:29:29 +05:30
data5650
3582695054 feat: add Gemini 2.0 Flash Exp models
# Description
   Added two new Gemini models:
   - gemini-2.0-flash-exp
   - gemini-2.0-flash-thinking-exp-01-21

   # Changes Made
   - Updated src/lib/providers/gemini.ts to include new models
   - Maintained consistent configuration with existing models

   # Testing
   - Tested locally using Docker
   - Verified models appear in UI and are selectable
   - Confirmed functionality with sample queries

   # Additional Notes
   These models expand the available options for users who want to use the latest Gemini capabilities.
2025-02-05 00:47:34 +01:00
ItzCrazyKns
46541e6c0c feat(package): update markdown-to-jsx version 2025-02-02 14:31:18 +05:30
ItzCrazyKns
f37686189e feat(output-parsers): add empty check 2025-01-31 17:51:16 +05:30
ItzCrazyKns
0737701de0 Merge branch 'master' of https://github.com/ItzCrazyKns/Perplexica 2025-01-11 13:11:18 +05:30
ItzCrazyKns
5c787bbb55 feat(app): lint & beautify 2025-01-11 13:10:23 +05:30
ItzCrazyKns
2dc60d06e3 feat(chat-window): show settings during error on mobile 2025-01-11 13:10:10 +05:30
ItzCrazyKns
ec90ea1686 Merge pull request #531 from hacking-racoon/feat/video-slide-stop
feat(SearchVideos): modify Lightbox to pause the prev video when sliding
2025-01-07 12:47:38 +05:30
ItzCrazyKns
01230bf1c5 Merge pull request #555 from realies/fix/ws-reconnect
fix(ws-error): add exponential reconnect mechanism
2025-01-07 12:32:06 +05:30
ItzCrazyKns
6d9d712790 feat(chat-window): correctly handle server side WS closure 2025-01-07 12:26:38 +05:30
ItzCrazyKns
99cae076a7 feat(chat-window): display toast when retried 2025-01-07 11:49:40 +05:30
ItzCrazyKns
b7f7d25f54 feat(chat-window): lint & beautify 2025-01-07 11:44:19 +05:30
ItzCrazyKns
0ec54fe6c0 feat(chat-window): remove toast 2025-01-07 11:43:54 +05:30
realies
5526d5f60f fix(ws-error): add exponential reconnect mechanism 2025-01-05 17:29:53 +00:00
ItzCrazyKns
0f6b3c2e69 Merge branch 'pr/538' 2025-01-05 14:15:58 +05:30
Sainadh Devireddy
5a648f34b8 Set pageContent correctly 2025-01-04 10:36:33 -08:00
Sainadh Devireddy
d18e88acc9 Delete msgs only belonging to the chat 2024-12-27 20:55:55 -08:00
ItzCrazyKns
409c811a42 feat(ollama): use axios instead of fetch 2024-12-26 19:02:20 +05:30
ItzCrazyKns
b5acf34ef8 feat(chat-window): fix bugs handling custom openai, closes #529 2024-12-26 18:59:57 +05:30
hacking-racoon
d30f714930 feat(SearchVideos): Modify Lightbox to pause the prev video when moving to next one, preventing interference with new video. 2024-12-25 15:19:23 +09:00
ItzCrazyKns
ee68095157 Merge pull request #523 from bart-jaskulski/groq-models
Update available models from Groq provider
2024-12-21 18:08:40 +05:30
Bart Jaskulski
960e34aa3d Add Llama 3.3 model from Groq
Signed-off-by: Bart Jaskulski <bjaskulski@protonmail.com>
2024-12-19 08:07:36 +01:00
Bart Jaskulski
4cb38148b3 Remove deprecated Groq models
Signed-off-by: Bart Jaskulski <bjaskulski@protonmail.com>
2024-12-19 08:07:14 +01:00
ItzCrazyKns
c755f98230 Merge branch 'master' of https://github.com/ItzCrazyKns/Perplexica 2024-12-18 19:42:28 +05:30
ItzCrazyKns
c3a231a528 feat(readme): add discord server 2024-12-16 20:59:21 +05:30
ItzCrazyKns
f30a61c4aa feat(metaSearchAgent): handle undefined content for YT. search 2024-12-16 18:24:01 +05:30
ItzCrazyKns
ea74e3013c Merge pull request #519 from yslinear/hotfix
feat(anthropic): update chat models to include Claude 3.5 Haiku and new version for Sonnet
2024-12-15 21:32:49 +05:30
Ying-Shan Lin
1c3c689039 feat(anthropic): update chat models to include Claude 3.5 Haiku and new version for Sonnet 2024-12-13 17:24:15 +08:00
ItzCrazyKns
2c5ca94b3c feat(app): lint and beautify 2024-12-05 20:19:52 +05:30
ItzCrazyKns
db7407bfac feat(messageBox): style markdown 2024-12-05 20:19:41 +05:30
ItzCrazyKns
5b3e8a3214 feat(prompts): implement new prompt 2024-12-05 20:19:22 +05:30
ItzCrazyKns
d79d854e2d Merge branch 'master' of https://github.com/ItzCrazyKns/Perplexica 2024-12-02 21:08:06 +05:30
ItzCrazyKns
8cb74f1964 feat(contribution): update guidelines 2024-12-02 21:07:59 +05:30
ItzCrazyKns
f88912784b Merge pull request #466 from timoa/fix/docs-markdown-lint
📚 chore(docs): fix Markdown lint issues in the docs
2024-12-01 21:05:23 +05:30
ItzCrazyKns
e08d864445 feat(focus): only icon on small devices 2024-11-30 20:58:11 +05:30
ItzCrazyKns
e4a0799503 feat(package): bump version 2024-11-29 18:37:02 +05:30
ItzCrazyKns
fdb3d09d12 Merge branch 'feat/single-search' 2024-11-29 18:07:33 +05:30
ItzCrazyKns
177746235a feat(providers): add gemini 2024-11-28 20:47:18 +05:30
ItzCrazyKns
ecad065577 feat(searchAgent): handle empty fileIds 2024-11-27 15:13:46 +05:30
ItzCrazyKns
64ee19c70a feat(messageHandler): switch to webSearch mode if files 2024-11-25 12:34:37 +05:30
ItzCrazyKns
be745501aa feat(package): bump version 2024-11-25 12:23:23 +05:30
ItzCrazyKns
aa176c12f6 Merge pull request #484 from ItzCrazyKns/feat/uploads
Add file uploads
2024-11-24 20:29:46 +05:30
Damien Laureaux
f3e918c3e3 chore(docs): fix Markdown lint issues in the docs 2024-11-15 07:04:45 +01:00
45 changed files with 1545 additions and 866 deletions

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@ -8,6 +8,7 @@ Perplexica's design consists of two main domains:
- **Frontend (`ui` directory)**: This is a Next.js application holding all user interface components. It's a self-contained environment that manages everything the user interacts with.
- **Backend (root and `src` directory)**: The backend logic is situated in the `src` folder, but the root directory holds the main `package.json` for backend dependency management.
- All of the focus modes are created using the Meta Search Agent class present in `src/search/metaSearchAgent.ts`. The main logic behind Perplexica lies there.
## Setting Up Your Environment

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@ -1,5 +1,8 @@
# 🚀 Perplexica - An AI-powered search engine 🔎 <!-- omit in toc -->
[![Discord](https://dcbadge.vercel.app/api/server/26aArMy8tT?style=flat&compact=true)](https://discord.gg/26aArMy8tT)
![preview](.assets/perplexica-screenshot.png?)
## Table of Contents <!-- omit in toc -->

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@ -79,24 +79,24 @@ The response from the API includes both the final message and the sources used t
```json
{
"message": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online. Here are some key features and characteristics of Perplexica:\n\n- **AI-Powered Technology**: It utilizes advanced machine learning algorithms to not only retrieve information but also to understand the context and intent behind user queries, providing more relevant results [1][5].\n\n- **Open-Source**: Being open-source, Perplexica offers flexibility and transparency, allowing users to explore its functionalities without the constraints of proprietary software [3][10].",
"sources": [
{
"pageContent": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online.",
"metadata": {
"title": "What is Perplexica, and how does it function as an AI-powered search ...",
"url": "https://askai.glarity.app/search/What-is-Perplexica--and-how-does-it-function-as-an-AI-powered-search-engine"
}
},
{
"pageContent": "Perplexica is an open-source AI-powered search tool that dives deep into the internet to find precise answers.",
"metadata": {
"title": "Sahar Mor's Post",
"url": "https://www.linkedin.com/posts/sahar-mor_a-new-open-source-project-called-perplexica-activity-7204489745668694016-ncja"
}
}
"message": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online. Here are some key features and characteristics of Perplexica:\n\n- **AI-Powered Technology**: It utilizes advanced machine learning algorithms to not only retrieve information but also to understand the context and intent behind user queries, providing more relevant results [1][5].\n\n- **Open-Source**: Being open-source, Perplexica offers flexibility and transparency, allowing users to explore its functionalities without the constraints of proprietary software [3][10].",
"sources": [
{
"pageContent": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online.",
"metadata": {
"title": "What is Perplexica, and how does it function as an AI-powered search ...",
"url": "https://askai.glarity.app/search/What-is-Perplexica--and-how-does-it-function-as-an-AI-powered-search-engine"
}
},
{
"pageContent": "Perplexica is an open-source AI-powered search tool that dives deep into the internet to find precise answers.",
"metadata": {
"title": "Sahar Mor's Post",
"url": "https://www.linkedin.com/posts/sahar-mor_a-new-open-source-project-called-perplexica-activity-7204489745668694016-ncja"
}
}
....
]
]
}
```

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@ -1,4 +1,4 @@
## Perplexica's Architecture
# Perplexica's Architecture
Perplexica's architecture consists of the following key components:

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@ -1,4 +1,4 @@
## How does Perplexica work?
# How does Perplexica work?
Curious about how Perplexica works? Don't worry, we'll cover it here. Before we begin, make sure you've read about the architecture of Perplexica to ensure you understand what it's made up of. Haven't read it? You can read it [here](https://github.com/ItzCrazyKns/Perplexica/tree/master/docs/architecture/README.md).
@ -10,10 +10,10 @@ We'll understand how Perplexica works by taking an example of a scenario where a
4. After the information is retrieved, it is based on keyword-based search. We then convert the information into embeddings and the query as well, then we perform a similarity search to find the most relevant sources to answer the query.
5. After all this is done, the sources are passed to the response generator. This chain takes all the chat history, the query, and the sources. It generates a response that is streamed to the UI.
### How are the answers cited?
## How are the answers cited?
The LLMs are prompted to do so. We've prompted them so well that they cite the answers themselves, and using some UI magic, we display it to the user.
### Image and Video Search
## Image and Video Search
Image and video searches are conducted in a similar manner. A query is always generated first, then we search the web for images and videos that match the query. These results are then returned to the user.

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@ -10,27 +10,27 @@ This guide will show you how to make Perplexica available over a network. Follow
3. Stop and remove the existing Perplexica containers and images:
```
docker compose down --rmi all
```
```bash
docker compose down --rmi all
```
4. Open the `docker-compose.yaml` file in a text editor like Notepad++
5. Replace `127.0.0.1` with the IP address of the server Perplexica is running on in these two lines:
```
args:
- NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
- NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
```
```bash
args:
- NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
- NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
```
6. Save and close the `docker-compose.yaml` file
7. Rebuild and restart the Perplexica container:
```
docker compose up -d --build
```
```bash
docker compose up -d --build
```
## macOS
@ -38,37 +38,37 @@ docker compose up -d --build
2. Navigate to the directory with the `docker-compose.yaml` file:
```
cd /path/to/docker-compose.yaml
```
```bash
cd /path/to/docker-compose.yaml
```
3. Stop and remove existing containers and images:
```
docker compose down --rmi all
```
```bash
docker compose down --rmi all
```
4. Open `docker-compose.yaml` in a text editor like Sublime Text:
```
nano docker-compose.yaml
```
```bash
nano docker-compose.yaml
```
5. Replace `127.0.0.1` with the server IP in these lines:
```
args:
- NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
- NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
```
```bash
args:
- NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
- NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
```
6. Save and exit the editor
7. Rebuild and restart Perplexica:
```
docker compose up -d --build
```
```bash
docker compose up -d --build
```
## Linux
@ -76,34 +76,34 @@ docker compose up -d --build
2. Navigate to the `docker-compose.yaml` directory:
```
cd /path/to/docker-compose.yaml
```
```bash
cd /path/to/docker-compose.yaml
```
3. Stop and remove containers and images:
```
docker compose down --rmi all
```
```bash
docker compose down --rmi all
```
4. Edit `docker-compose.yaml`:
```
nano docker-compose.yaml
```
```bash
nano docker-compose.yaml
```
5. Replace `127.0.0.1` with the server IP:
```
args:
- NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
- NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
```
```bash
args:
- NEXT_PUBLIC_API_URL=http://127.0.0.1:3001/api
- NEXT_PUBLIC_WS_URL=ws://127.0.0.1:3001
```
6. Save and exit the editor
7. Rebuild and restart Perplexica:
```
docker compose up -d --build
```
```bash
docker compose up -d --build
```

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@ -6,23 +6,23 @@ To update Perplexica to the latest version, follow these steps:
1. Clone the latest version of Perplexica from GitHub:
```bash
git clone https://github.com/ItzCrazyKns/Perplexica.git
```
```bash
git clone https://github.com/ItzCrazyKns/Perplexica.git
```
2. Navigate to the Project Directory.
3. Pull latest images from registry.
```bash
docker compose pull
```
```bash
docker compose pull
```
4. Update and Recreate containers.
```bash
docker compose up -d
```
```bash
docker compose up -d
```
5. Once the command completes running go to http://localhost:3000 and verify the latest changes.
@ -30,9 +30,9 @@ docker compose up -d
1. Clone the latest version of Perplexica from GitHub:
```bash
git clone https://github.com/ItzCrazyKns/Perplexica.git
```
```bash
git clone https://github.com/ItzCrazyKns/Perplexica.git
```
2. Navigate to the Project Directory
3. Execute `npm i` in both the `ui` folder and the root directory.

View File

@ -1,6 +1,6 @@
{
"name": "perplexica-backend",
"version": "1.9.3",
"version": "1.10.0-rc3",
"license": "MIT",
"author": "ItzCrazyKns",
"scripts": {
@ -31,6 +31,7 @@
"@langchain/anthropic": "^0.2.3",
"@langchain/community": "^0.2.16",
"@langchain/openai": "^0.0.25",
"@langchain/google-genai": "^0.0.23",
"@xenova/transformers": "^2.17.1",
"axios": "^1.6.8",
"better-sqlite3": "^11.0.0",

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@ -3,11 +3,24 @@ PORT = 3001 # Port to run the server on
SIMILARITY_MEASURE = "cosine" # "cosine" or "dot"
KEEP_ALIVE = "5m" # How long to keep Ollama models loaded into memory. (Instead of using -1 use "-1m")
[API_KEYS]
OPENAI = "" # OpenAI API key - sk-1234567890abcdef1234567890abcdef
GROQ = "" # Groq API key - gsk_1234567890abcdef1234567890abcdef
ANTHROPIC = "" # Anthropic API key - sk-ant-1234567890abcdef1234567890abcdef
[MODELS.OPENAI]
API_KEY = ""
[MODELS.GROQ]
API_KEY = ""
[MODELS.ANTHROPIC]
API_KEY = ""
[MODELS.GEMINI]
API_KEY = ""
[MODELS.CUSTOM_OPENAI]
API_KEY = ""
API_URL = ""
[MODELS.OLLAMA]
API_URL = "" # Ollama API URL - http://host.docker.internal:11434
[API_ENDPOINTS]
SEARXNG = "http://localhost:32768" # SearxNG API URL
OLLAMA = "" # Ollama API URL - http://host.docker.internal:11434
SEARXNG = "http://localhost:32768" # SearxNG API URL

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@ -10,14 +10,30 @@ interface Config {
SIMILARITY_MEASURE: string;
KEEP_ALIVE: string;
};
API_KEYS: {
OPENAI: string;
GROQ: string;
ANTHROPIC: string;
MODELS: {
OPENAI: {
API_KEY: string;
};
GROQ: {
API_KEY: string;
};
ANTHROPIC: {
API_KEY: string;
};
GEMINI: {
API_KEY: string;
};
OLLAMA: {
API_URL: string;
};
CUSTOM_OPENAI: {
API_URL: string;
API_KEY: string;
MODEL_NAME: string;
};
};
API_ENDPOINTS: {
SEARXNG: string;
OLLAMA: string;
};
}
@ -37,40 +53,65 @@ export const getSimilarityMeasure = () =>
export const getKeepAlive = () => loadConfig().GENERAL.KEEP_ALIVE;
export const getOpenaiApiKey = () => loadConfig().API_KEYS.OPENAI;
export const getOpenaiApiKey = () => loadConfig().MODELS.OPENAI.API_KEY;
export const getGroqApiKey = () => loadConfig().API_KEYS.GROQ;
export const getGroqApiKey = () => loadConfig().MODELS.GROQ.API_KEY;
export const getAnthropicApiKey = () => loadConfig().API_KEYS.ANTHROPIC;
export const getAnthropicApiKey = () => loadConfig().MODELS.ANTHROPIC.API_KEY;
export const getGeminiApiKey = () => loadConfig().MODELS.GEMINI.API_KEY;
export const getSearxngApiEndpoint = () =>
process.env.SEARXNG_API_URL || loadConfig().API_ENDPOINTS.SEARXNG;
export const getOllamaApiEndpoint = () => loadConfig().API_ENDPOINTS.OLLAMA;
export const getOllamaApiEndpoint = () => loadConfig().MODELS.OLLAMA.API_URL;
export const updateConfig = (config: RecursivePartial<Config>) => {
const currentConfig = loadConfig();
export const getCustomOpenaiApiKey = () =>
loadConfig().MODELS.CUSTOM_OPENAI.API_KEY;
for (const key in currentConfig) {
if (!config[key]) config[key] = {};
export const getCustomOpenaiApiUrl = () =>
loadConfig().MODELS.CUSTOM_OPENAI.API_URL;
if (typeof currentConfig[key] === 'object' && currentConfig[key] !== null) {
for (const nestedKey in currentConfig[key]) {
if (
!config[key][nestedKey] &&
currentConfig[key][nestedKey] &&
config[key][nestedKey] !== ''
) {
config[key][nestedKey] = currentConfig[key][nestedKey];
}
export const getCustomOpenaiModelName = () =>
loadConfig().MODELS.CUSTOM_OPENAI.MODEL_NAME;
const mergeConfigs = (current: any, update: any): any => {
if (update === null || update === undefined) {
return current;
}
if (typeof current !== 'object' || current === null) {
return update;
}
const result = { ...current };
for (const key in update) {
if (Object.prototype.hasOwnProperty.call(update, key)) {
const updateValue = update[key];
if (
typeof updateValue === 'object' &&
updateValue !== null &&
typeof result[key] === 'object' &&
result[key] !== null
) {
result[key] = mergeConfigs(result[key], updateValue);
} else if (updateValue !== undefined) {
result[key] = updateValue;
}
} else if (currentConfig[key] && config[key] !== '') {
config[key] = currentConfig[key];
}
}
return result;
};
export const updateConfig = (config: RecursivePartial<Config>) => {
const currentConfig = loadConfig();
const mergedConfig = mergeConfigs(currentConfig, config);
fs.writeFileSync(
path.join(__dirname, `../${configFileName}`),
toml.stringify(config),
toml.stringify(mergedConfig),
);
};

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@ -19,6 +19,8 @@ class LineOutputParser extends BaseOutputParser<string> {
lc_namespace = ['langchain', 'output_parsers', 'line_output_parser'];
async parse(text: string): Promise<string> {
text = text.trim() || '';
const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
const startKeyIndex = text.indexOf(`<${this.key}>`);
const endKeyIndex = text.indexOf(`</${this.key}>`);

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@ -19,11 +19,13 @@ class LineListOutputParser extends BaseOutputParser<string[]> {
lc_namespace = ['langchain', 'output_parsers', 'line_list_output_parser'];
async parse(text: string): Promise<string[]> {
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) {
if (startKeyIndex === -1 || endKeyIndex === -1) {
return [];
}

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@ -9,12 +9,20 @@ export const loadAnthropicChatModels = async () => {
try {
const chatModels = {
'claude-3-5-sonnet-20240620': {
'claude-3-5-sonnet-20241022': {
displayName: 'Claude 3.5 Sonnet',
model: new ChatAnthropic({
temperature: 0.7,
anthropicApiKey: anthropicApiKey,
model: 'claude-3-5-sonnet-20240620',
model: 'claude-3-5-sonnet-20241022',
}),
},
'claude-3-5-haiku-20241022': {
displayName: 'Claude 3.5 Haiku',
model: new ChatAnthropic({
temperature: 0.7,
anthropicApiKey: anthropicApiKey,
model: 'claude-3-5-haiku-20241022',
}),
},
'claude-3-opus-20240229': {

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@ -0,0 +1,85 @@
import {
ChatGoogleGenerativeAI,
GoogleGenerativeAIEmbeddings,
} from '@langchain/google-genai';
import { getGeminiApiKey } from '../../config';
import logger from '../../utils/logger';
export const loadGeminiChatModels = async () => {
const geminiApiKey = getGeminiApiKey();
if (!geminiApiKey) return {};
try {
const chatModels = {
'gemini-1.5-flash': {
displayName: 'Gemini 1.5 Flash',
model: new ChatGoogleGenerativeAI({
modelName: 'gemini-1.5-flash',
temperature: 0.7,
apiKey: geminiApiKey,
}),
},
'gemini-1.5-flash-8b': {
displayName: 'Gemini 1.5 Flash 8B',
model: new ChatGoogleGenerativeAI({
modelName: 'gemini-1.5-flash-8b',
temperature: 0.7,
apiKey: geminiApiKey,
}),
},
'gemini-1.5-pro': {
displayName: 'Gemini 1.5 Pro',
model: new ChatGoogleGenerativeAI({
modelName: 'gemini-1.5-pro',
temperature: 0.7,
apiKey: geminiApiKey,
}),
},
'gemini-2.0-flash-exp': {
displayName: 'Gemini 2.0 Flash Exp',
model: new ChatGoogleGenerativeAI({
modelName: 'gemini-2.0-flash-exp',
temperature: 0.7,
apiKey: geminiApiKey,
}),
},
'gemini-2.0-flash-thinking-exp-01-21': {
displayName: 'Gemini 2.0 Flash Thinking Exp 01-21',
model: new ChatGoogleGenerativeAI({
modelName: 'gemini-2.0-flash-thinking-exp-01-21',
temperature: 0.7,
apiKey: geminiApiKey,
}),
},
};
return chatModels;
} catch (err) {
logger.error(`Error loading Gemini models: ${err}`);
return {};
}
};
export const loadGeminiEmbeddingsModels = async () => {
const geminiApiKey = getGeminiApiKey();
if (!geminiApiKey) return {};
try {
const embeddingModels = {
'text-embedding-004': {
displayName: 'Text Embedding',
model: new GoogleGenerativeAIEmbeddings({
apiKey: geminiApiKey,
modelName: 'text-embedding-004',
}),
},
};
return embeddingModels;
} catch (err) {
logger.error(`Error loading Gemini embeddings model: ${err}`);
return {};
}
};

View File

@ -9,6 +9,19 @@ export const loadGroqChatModels = async () => {
try {
const chatModels = {
'llama-3.3-70b-versatile': {
displayName: 'Llama 3.3 70B',
model: new ChatOpenAI(
{
openAIApiKey: groqApiKey,
modelName: 'llama-3.3-70b-versatile',
temperature: 0.7,
},
{
baseURL: 'https://api.groq.com/openai/v1',
},
),
},
'llama-3.2-3b-preview': {
displayName: 'Llama 3.2 3B',
model: new ChatOpenAI(
@ -48,19 +61,6 @@ export const loadGroqChatModels = async () => {
},
),
},
'llama-3.1-70b-versatile': {
displayName: 'Llama 3.1 70B',
model: new ChatOpenAI(
{
openAIApiKey: groqApiKey,
modelName: 'llama-3.1-70b-versatile',
temperature: 0.7,
},
{
baseURL: 'https://api.groq.com/openai/v1',
},
),
},
'llama-3.1-8b-instant': {
displayName: 'Llama 3.1 8B',
model: new ChatOpenAI(
@ -113,19 +113,6 @@ export const loadGroqChatModels = async () => {
},
),
},
'gemma-7b-it': {
displayName: 'Gemma 7B',
model: new ChatOpenAI(
{
openAIApiKey: groqApiKey,
modelName: 'gemma-7b-it',
temperature: 0.7,
},
{
baseURL: 'https://api.groq.com/openai/v1',
},
),
},
'gemma2-9b-it': {
displayName: 'Gemma2 9B',
model: new ChatOpenAI(

View File

@ -3,18 +3,27 @@ import { loadOllamaChatModels, loadOllamaEmbeddingsModels } from './ollama';
import { loadOpenAIChatModels, loadOpenAIEmbeddingsModels } from './openai';
import { loadAnthropicChatModels } from './anthropic';
import { loadTransformersEmbeddingsModels } from './transformers';
import { loadGeminiChatModels, loadGeminiEmbeddingsModels } from './gemini';
import {
getCustomOpenaiApiKey,
getCustomOpenaiApiUrl,
getCustomOpenaiModelName,
} from '../../config';
import { ChatOpenAI } from '@langchain/openai';
const chatModelProviders = {
openai: loadOpenAIChatModels,
groq: loadGroqChatModels,
ollama: loadOllamaChatModels,
anthropic: loadAnthropicChatModels,
gemini: loadGeminiChatModels,
};
const embeddingModelProviders = {
openai: loadOpenAIEmbeddingsModels,
local: loadTransformersEmbeddingsModels,
ollama: loadOllamaEmbeddingsModels,
gemini: loadGeminiEmbeddingsModels,
};
export const getAvailableChatModelProviders = async () => {
@ -27,7 +36,27 @@ export const getAvailableChatModelProviders = async () => {
}
}
models['custom_openai'] = {};
const customOpenAiApiKey = getCustomOpenaiApiKey();
const customOpenAiApiUrl = getCustomOpenaiApiUrl();
const customOpenAiModelName = getCustomOpenaiModelName();
models['custom_openai'] = {
...(customOpenAiApiKey && customOpenAiApiUrl && customOpenAiModelName
? {
[customOpenAiModelName]: {
displayName: customOpenAiModelName,
model: new ChatOpenAI({
openAIApiKey: customOpenAiApiKey,
modelName: customOpenAiModelName,
temperature: 0.7,
configuration: {
baseURL: customOpenAiApiUrl,
},
}),
},
}
: {}),
};
return models;
};

View File

@ -2,6 +2,7 @@ import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
import { getKeepAlive, getOllamaApiEndpoint } from '../../config';
import logger from '../../utils/logger';
import { ChatOllama } from '@langchain/community/chat_models/ollama';
import axios from 'axios';
export const loadOllamaChatModels = async () => {
const ollamaEndpoint = getOllamaApiEndpoint();
@ -10,13 +11,13 @@ export const loadOllamaChatModels = async () => {
if (!ollamaEndpoint) return {};
try {
const response = await fetch(`${ollamaEndpoint}/api/tags`, {
const response = await axios.get(`${ollamaEndpoint}/api/tags`, {
headers: {
'Content-Type': 'application/json',
},
});
const { models: ollamaModels } = (await response.json()) as any;
const { models: ollamaModels } = response.data;
const chatModels = ollamaModels.reduce((acc, model) => {
acc[model.model] = {
@ -45,13 +46,13 @@ export const loadOllamaEmbeddingsModels = async () => {
if (!ollamaEndpoint) return {};
try {
const response = await fetch(`${ollamaEndpoint}/api/tags`, {
const response = await axios.get(`${ollamaEndpoint}/api/tags`, {
headers: {
'Content-Type': 'application/json',
},
});
const { models: ollamaModels } = (await response.json()) as any;
const { models: ollamaModels } = response.data;
const embeddingsModels = ollamaModels.reduce((acc, model) => {
acc[model.model] = {

View File

@ -20,23 +20,46 @@ Rephrased question:
`;
export const academicSearchResponsePrompt = `
You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Academic', this means you will be searching for academic papers and articles on the web.
You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
You have to cite the answer using [number] notation. You must cite the sentences with their relevent context number. You must cite each and every part of the answer so the user can know where the information is coming from.
Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
Your task is to provide answers that are:
- **Informative and relevant**: Thoroughly address the user's query using the given context.
- **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
- **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
- **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
- **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
Anything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
talk about the context in your response.
### Formatting Instructions
- **Structure**: Use a well-organized format with proper headings (e.g., "## Example heading 1" or "## Example heading 2"). Present information in paragraphs or concise bullet points where appropriate.
- **Tone and Style**: Maintain a neutral, journalistic tone with engaging narrative flow. Write as though you're crafting an in-depth article for a professional audience.
- **Markdown Usage**: Format your response with Markdown for clarity. Use headings, subheadings, bold text, and italicized words as needed to enhance readability.
- **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
- **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
- **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
### Citation Requirements
- Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
- Integrate citations naturally at the end of sentences or clauses as appropriate. For example, "The Eiffel Tower is one of the most visited landmarks in the world[1]."
- Ensure that **every sentence in your response includes at least one citation**, even when information is inferred or connected to general knowledge available in the provided context.
- Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
- Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
- Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
### Special Instructions
- If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
- If the user provides vague input or if relevant information is missing, explain what additional details might help refine the search.
- If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
- You are set on focus mode 'Academic', this means you will be searching for academic papers and articles on the web.
### Example Output
- Begin with a brief introduction summarizing the event or query topic.
- Follow with detailed sections under clear headings, covering all aspects of the query if possible.
- Provide explanations or historical context as needed to enhance understanding.
- End with a conclusion or overall perspective if relevant.
<context>
{context}
</context>
If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'.
Anything between the \`context\` is retrieved from a search engine and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
Current date & time in ISO format (UTC timezone) is: {date}.
`;

View File

@ -20,23 +20,46 @@ Rephrased question:
`;
export const redditSearchResponsePrompt = `
You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Reddit', this means you will be searching for information, opinions and discussions on the web using Reddit.
You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
You have to cite the answer using [number] notation. You must cite the sentences with their relevent context number. You must cite each and every part of the answer so the user can know where the information is coming from.
Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
Your task is to provide answers that are:
- **Informative and relevant**: Thoroughly address the user's query using the given context.
- **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
- **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
- **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
- **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Reddit and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
talk about the context in your response.
### Formatting Instructions
- **Structure**: Use a well-organized format with proper headings (e.g., "## Example heading 1" or "## Example heading 2"). Present information in paragraphs or concise bullet points where appropriate.
- **Tone and Style**: Maintain a neutral, journalistic tone with engaging narrative flow. Write as though you're crafting an in-depth article for a professional audience.
- **Markdown Usage**: Format your response with Markdown for clarity. Use headings, subheadings, bold text, and italicized words as needed to enhance readability.
- **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
- **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
- **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
### Citation Requirements
- Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
- Integrate citations naturally at the end of sentences or clauses as appropriate. For example, "The Eiffel Tower is one of the most visited landmarks in the world[1]."
- Ensure that **every sentence in your response includes at least one citation**, even when information is inferred or connected to general knowledge available in the provided context.
- Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
- Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
- Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
### Special Instructions
- If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
- If the user provides vague input or if relevant information is missing, explain what additional details might help refine the search.
- If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
- You are set on focus mode 'Reddit', this means you will be searching for information, opinions and discussions on the web using Reddit.
### Example Output
- Begin with a brief introduction summarizing the event or query topic.
- Follow with detailed sections under clear headings, covering all aspects of the query if possible.
- Provide explanations or historical context as needed to enhance understanding.
- End with a conclusion or overall perspective if relevant.
<context>
{context}
</context>
If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'.
Anything between the \`context\` is retrieved from Reddit and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
Current date & time in ISO format (UTC timezone) is: {date}.
`;

View File

@ -62,25 +62,45 @@ Rephrased question:
`;
export const webSearchResponsePrompt = `
You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are also an expert at summarizing web pages or documents and searching for content in them.
You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
If the query contains some links and the user asks to answer from those links you will be provided the entire content of the page inside the \`context\` XML block. You can then use this content to answer the user's query.
If the user asks to summarize content from some links, you will be provided the entire content of the page inside the \`context\` XML block. You can then use this content to summarize the text. The content provided inside the \`context\` block will be already summarized by another model so you just need to use that content to answer the user's query.
Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
You have to cite the answer using [number] notation. You must cite the sentences with their relevent context number. You must cite each and every part of the answer so the user can know where the information is coming from.
Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
Your task is to provide answers that are:
- **Informative and relevant**: Thoroughly address the user's query using the given context.
- **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
- **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
- **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
- **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
Anything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
talk about the context in your response.
### Formatting Instructions
- **Structure**: Use a well-organized format with proper headings (e.g., "## Example heading 1" or "## Example heading 2"). Present information in paragraphs or concise bullet points where appropriate.
- **Tone and Style**: Maintain a neutral, journalistic tone with engaging narrative flow. Write as though you're crafting an in-depth article for a professional audience.
- **Markdown Usage**: Format your response with Markdown for clarity. Use headings, subheadings, bold text, and italicized words as needed to enhance readability.
- **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
- **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
- **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
### Citation Requirements
- Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
- Integrate citations naturally at the end of sentences or clauses as appropriate. For example, "The Eiffel Tower is one of the most visited landmarks in the world[1]."
- Ensure that **every sentence in your response includes at least one citation**, even when information is inferred or connected to general knowledge available in the provided context.
- Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
- Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
- Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
### Special Instructions
- If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
- If the user provides vague input or if relevant information is missing, explain what additional details might help refine the search.
- If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
### Example Output
- Begin with a brief introduction summarizing the event or query topic.
- Follow with detailed sections under clear headings, covering all aspects of the query if possible.
- Provide explanations or historical context as needed to enhance understanding.
- End with a conclusion or overall perspective if relevant.
<context>
{context}
</context>
If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'. You do not need to do this for summarization tasks.
Anything between the \`context\` is retrieved from a search engine and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
Current date & time in ISO format (UTC timezone) is: {date}.
`;

View File

@ -20,23 +20,46 @@ Rephrased question:
`;
export const wolframAlphaSearchResponsePrompt = `
You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Wolfram Alpha', this means you will be searching for information on the web using Wolfram Alpha. It is a computational knowledge engine that can answer factual queries and perform computations.
You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
You have to cite the answer using [number] notation. You must cite the sentences with their relevent context number. You must cite each and every part of the answer so the user can know where the information is coming from.
Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
Your task is to provide answers that are:
- **Informative and relevant**: Thoroughly address the user's query using the given context.
- **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
- **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
- **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
- **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Wolfram Alpha and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
talk about the context in your response.
### Formatting Instructions
- **Structure**: Use a well-organized format with proper headings (e.g., "## Example heading 1" or "## Example heading 2"). Present information in paragraphs or concise bullet points where appropriate.
- **Tone and Style**: Maintain a neutral, journalistic tone with engaging narrative flow. Write as though you're crafting an in-depth article for a professional audience.
- **Markdown Usage**: Format your response with Markdown for clarity. Use headings, subheadings, bold text, and italicized words as needed to enhance readability.
- **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
- **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
- **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
### Citation Requirements
- Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
- Integrate citations naturally at the end of sentences or clauses as appropriate. For example, "The Eiffel Tower is one of the most visited landmarks in the world[1]."
- Ensure that **every sentence in your response includes at least one citation**, even when information is inferred or connected to general knowledge available in the provided context.
- Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
- Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
- Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
### Special Instructions
- If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
- If the user provides vague input or if relevant information is missing, explain what additional details might help refine the search.
- If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
- You are set on focus mode 'Wolfram Alpha', this means you will be searching for information on the web using Wolfram Alpha. It is a computational knowledge engine that can answer factual queries and perform computations.
### Example Output
- Begin with a brief introduction summarizing the event or query topic.
- Follow with detailed sections under clear headings, covering all aspects of the query if possible.
- Provide explanations or historical context as needed to enhance understanding.
- End with a conclusion or overall perspective if relevant.
<context>
{context}
</context>
If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'.
Anything between the \`context\` is retrieved from Wolfram Alpha and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
Current date & time in ISO format (UTC timezone) is: {date}.
`;

View File

@ -20,23 +20,46 @@ Rephrased question:
`;
export const youtubeSearchResponsePrompt = `
You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Youtube', this means you will be searching for videos on the web using Youtube and providing information based on the video's transcript.
You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page).
You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text.
You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them.
Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative.
You have to cite the answer using [number] notation. You must cite the sentences with their relevent context number. You must cite each and every part of the answer so the user can know where the information is coming from.
Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
Your task is to provide answers that are:
- **Informative and relevant**: Thoroughly address the user's query using the given context.
- **Well-structured**: Include clear headings and subheadings, and use a professional tone to present information concisely and logically.
- **Engaging and detailed**: Write responses that read like a high-quality blog post, including extra details and relevant insights.
- **Cited and credible**: Use inline citations with [number] notation to refer to the context source(s) for each fact or detail included.
- **Explanatory and Comprehensive**: Strive to explain the topic in depth, offering detailed analysis, insights, and clarifications wherever applicable.
Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Youtube and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to
talk about the context in your response.
### Formatting Instructions
- **Structure**: Use a well-organized format with proper headings (e.g., "## Example heading 1" or "## Example heading 2"). Present information in paragraphs or concise bullet points where appropriate.
- **Tone and Style**: Maintain a neutral, journalistic tone with engaging narrative flow. Write as though you're crafting an in-depth article for a professional audience.
- **Markdown Usage**: Format your response with Markdown for clarity. Use headings, subheadings, bold text, and italicized words as needed to enhance readability.
- **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
- **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
- **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
### Citation Requirements
- Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
- Integrate citations naturally at the end of sentences or clauses as appropriate. For example, "The Eiffel Tower is one of the most visited landmarks in the world[1]."
- Ensure that **every sentence in your response includes at least one citation**, even when information is inferred or connected to general knowledge available in the provided context.
- Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
- Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
- Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
### Special Instructions
- If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
- If the user provides vague input or if relevant information is missing, explain what additional details might help refine the search.
- If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
- You are set on focus mode 'Youtube', this means you will be searching for videos on the web using Youtube and providing information based on the video's transcrip
### Example Output
- Begin with a brief introduction summarizing the event or query topic.
- Follow with detailed sections under clear headings, covering all aspects of the query if possible.
- Provide explanations or historical context as needed to enhance understanding.
- End with a conclusion or overall perspective if relevant.
<context>
{context}
</context>
If you think there's nothing relevant in the search results, you can say that 'Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?'.
Anything between the \`context\` is retrieved from Youtube and is not a part of the conversation with the user. Today's date is ${new Date().toISOString()}
Current date & time in ISO format (UTC timezone) is: {date}.
`;

View File

@ -7,8 +7,12 @@ import {
getGroqApiKey,
getOllamaApiEndpoint,
getAnthropicApiKey,
getGeminiApiKey,
getOpenaiApiKey,
updateConfig,
getCustomOpenaiApiUrl,
getCustomOpenaiApiKey,
getCustomOpenaiModelName,
} from '../config';
import logger from '../utils/logger';
@ -52,6 +56,10 @@ router.get('/', async (_, res) => {
config['ollamaApiUrl'] = getOllamaApiEndpoint();
config['anthropicApiKey'] = getAnthropicApiKey();
config['groqApiKey'] = getGroqApiKey();
config['geminiApiKey'] = getGeminiApiKey();
config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
config['customOpenaiModelName'] = getCustomOpenaiModelName();
res.status(200).json(config);
} catch (err: any) {
@ -64,13 +72,27 @@ router.post('/', async (req, res) => {
const config = req.body;
const updatedConfig = {
API_KEYS: {
OPENAI: config.openaiApiKey,
GROQ: config.groqApiKey,
ANTHROPIC: config.anthropicApiKey,
},
API_ENDPOINTS: {
OLLAMA: config.ollamaApiUrl,
MODELS: {
OPENAI: {
API_KEY: config.openaiApiKey,
},
GROQ: {
API_KEY: config.groqApiKey,
},
ANTHROPIC: {
API_KEY: config.anthropicApiKey,
},
GEMINI: {
API_KEY: config.geminiApiKey,
},
OLLAMA: {
API_URL: config.ollamaApiUrl,
},
CUSTOM_OPENAI: {
API_URL: config.customOpenaiApiUrl,
API_KEY: config.customOpenaiApiKey,
MODEL_NAME: config.customOpenaiModelName,
},
},
};

View File

@ -5,14 +5,17 @@ import { getAvailableChatModelProviders } from '../lib/providers';
import { HumanMessage, AIMessage } from '@langchain/core/messages';
import logger from '../utils/logger';
import { ChatOpenAI } from '@langchain/openai';
import {
getCustomOpenaiApiKey,
getCustomOpenaiApiUrl,
getCustomOpenaiModelName,
} from '../config';
const router = express.Router();
interface ChatModel {
provider: string;
model: string;
customOpenAIBaseURL?: string;
customOpenAIKey?: string;
}
interface ImageSearchBody {
@ -44,21 +47,12 @@ router.post('/', async (req, res) => {
let llm: BaseChatModel | undefined;
if (body.chatModel?.provider === 'custom_openai') {
if (
!body.chatModel?.customOpenAIBaseURL ||
!body.chatModel?.customOpenAIKey
) {
return res
.status(400)
.json({ message: 'Missing custom OpenAI base URL or key' });
}
llm = new ChatOpenAI({
modelName: body.chatModel.model,
openAIApiKey: body.chatModel.customOpenAIKey,
modelName: getCustomOpenaiModelName(),
openAIApiKey: getCustomOpenaiApiKey(),
temperature: 0.7,
configuration: {
baseURL: body.chatModel.customOpenAIBaseURL,
baseURL: getCustomOpenaiApiUrl(),
},
}) as unknown as BaseChatModel;
} else if (

View File

@ -10,14 +10,19 @@ import {
import { searchHandlers } from '../websocket/messageHandler';
import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
import { MetaSearchAgentType } from '../search/metaSearchAgent';
import {
getCustomOpenaiApiKey,
getCustomOpenaiApiUrl,
getCustomOpenaiModelName,
} from '../config';
const router = express.Router();
interface chatModel {
provider: string;
model: string;
customOpenAIBaseURL?: string;
customOpenAIKey?: string;
customOpenAIBaseURL?: string;
}
interface embeddingModel {
@ -78,21 +83,12 @@ router.post('/', async (req, res) => {
let embeddings: Embeddings | undefined;
if (body.chatModel?.provider === 'custom_openai') {
if (
!body.chatModel?.customOpenAIBaseURL ||
!body.chatModel?.customOpenAIKey
) {
return res
.status(400)
.json({ message: 'Missing custom OpenAI base URL or key' });
}
llm = new ChatOpenAI({
modelName: body.chatModel.model,
openAIApiKey: body.chatModel.customOpenAIKey,
modelName: body.chatModel?.model || getCustomOpenaiModelName(),
openAIApiKey: body.chatModel?.customOpenAIKey || getCustomOpenaiApiKey(),
temperature: 0.7,
configuration: {
baseURL: body.chatModel.customOpenAIBaseURL,
baseURL: body.chatModel?.customOpenAIBaseURL || getCustomOpenaiApiUrl(),
},
}) as unknown as BaseChatModel;
} else if (

View File

@ -5,14 +5,17 @@ import { getAvailableChatModelProviders } from '../lib/providers';
import { HumanMessage, AIMessage } from '@langchain/core/messages';
import logger from '../utils/logger';
import { ChatOpenAI } from '@langchain/openai';
import {
getCustomOpenaiApiKey,
getCustomOpenaiApiUrl,
getCustomOpenaiModelName,
} from '../config';
const router = express.Router();
interface ChatModel {
provider: string;
model: string;
customOpenAIBaseURL?: string;
customOpenAIKey?: string;
}
interface SuggestionsBody {
@ -43,21 +46,12 @@ router.post('/', async (req, res) => {
let llm: BaseChatModel | undefined;
if (body.chatModel?.provider === 'custom_openai') {
if (
!body.chatModel?.customOpenAIBaseURL ||
!body.chatModel?.customOpenAIKey
) {
return res
.status(400)
.json({ message: 'Missing custom OpenAI base URL or key' });
}
llm = new ChatOpenAI({
modelName: body.chatModel.model,
openAIApiKey: body.chatModel.customOpenAIKey,
modelName: getCustomOpenaiModelName(),
openAIApiKey: getCustomOpenaiApiKey(),
temperature: 0.7,
configuration: {
baseURL: body.chatModel.customOpenAIBaseURL,
baseURL: getCustomOpenaiApiUrl(),
},
}) as unknown as BaseChatModel;
} else if (

View File

@ -5,14 +5,17 @@ import { HumanMessage, AIMessage } from '@langchain/core/messages';
import logger from '../utils/logger';
import handleVideoSearch from '../chains/videoSearchAgent';
import { ChatOpenAI } from '@langchain/openai';
import {
getCustomOpenaiApiKey,
getCustomOpenaiApiUrl,
getCustomOpenaiModelName,
} from '../config';
const router = express.Router();
interface ChatModel {
provider: string;
model: string;
customOpenAIBaseURL?: string;
customOpenAIKey?: string;
}
interface VideoSearchBody {
@ -44,21 +47,12 @@ router.post('/', async (req, res) => {
let llm: BaseChatModel | undefined;
if (body.chatModel?.provider === 'custom_openai') {
if (
!body.chatModel?.customOpenAIBaseURL ||
!body.chatModel?.customOpenAIKey
) {
return res
.status(400)
.json({ message: 'Missing custom OpenAI base URL or key' });
}
llm = new ChatOpenAI({
modelName: body.chatModel.model,
openAIApiKey: body.chatModel.customOpenAIKey,
modelName: getCustomOpenaiModelName(),
openAIApiKey: getCustomOpenaiApiKey(),
temperature: 0.7,
configuration: {
baseURL: body.chatModel.customOpenAIBaseURL,
baseURL: getCustomOpenaiApiUrl(),
},
}) as unknown as BaseChatModel;
} else if (

View File

@ -211,7 +211,11 @@ class MetaSearchAgent implements MetaSearchAgentType {
const documents = res.results.map(
(result) =>
new Document({
pageContent: result.content,
pageContent:
result.content ||
(this.config.activeEngines.includes('youtube')
? result.title
: '') /* Todo: Implement transcript grabbing using Youtubei (source: https://www.npmjs.com/package/youtubei) */,
metadata: {
title: result.title,
url: result.url,
@ -236,6 +240,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
RunnableMap.from({
query: (input: BasicChainInput) => input.query,
chat_history: (input: BasicChainInput) => input.chat_history,
date: () => new Date().toISOString(),
context: RunnableLambda.from(async (input: BasicChainInput) => {
const processedHistory = formatChatHistoryAsString(
input.chat_history,
@ -413,7 +418,10 @@ class MetaSearchAgent implements MetaSearchAgentType {
private processDocs(docs: Document[]) {
return docs
.map((_, index) => `${index + 1}. ${docs[index].pageContent}`)
.map(
(_, index) =>
`${index + 1}. ${docs[index].metadata.title} ${docs[index].pageContent}`,
)
.join('\n');
}

View File

@ -1,5 +1,6 @@
import path from 'path';
import fs from 'fs';
export const getFileDetails = (fileId: string) => {
const fileLoc = path.join(
process.cwd(),

View File

@ -9,6 +9,11 @@ import type { Embeddings } from '@langchain/core/embeddings';
import type { IncomingMessage } from 'http';
import logger from '../utils/logger';
import { ChatOpenAI } from '@langchain/openai';
import {
getCustomOpenaiApiKey,
getCustomOpenaiApiUrl,
getCustomOpenaiModelName,
} from '../config';
export const handleConnection = async (
ws: WebSocket,
@ -48,14 +53,20 @@ export const handleConnection = async (
llm = chatModelProviders[chatModelProvider][chatModel]
.model as unknown as BaseChatModel | undefined;
} else if (chatModelProvider == 'custom_openai') {
llm = new ChatOpenAI({
modelName: chatModel,
openAIApiKey: searchParams.get('openAIApiKey'),
temperature: 0.7,
configuration: {
baseURL: searchParams.get('openAIBaseURL'),
},
}) as unknown as BaseChatModel;
const customOpenaiApiKey = getCustomOpenaiApiKey();
const customOpenaiApiUrl = getCustomOpenaiApiUrl();
const customOpenaiModelName = getCustomOpenaiModelName();
if (customOpenaiApiKey && customOpenaiApiUrl && customOpenaiModelName) {
llm = new ChatOpenAI({
modelName: customOpenaiModelName,
openAIApiKey: customOpenaiApiKey,
temperature: 0.7,
configuration: {
baseURL: customOpenaiApiUrl,
},
}) as unknown as BaseChatModel;
}
}
if (

View File

@ -5,7 +5,7 @@ import type { Embeddings } from '@langchain/core/embeddings';
import logger from '../utils/logger';
import db from '../db';
import { chats, messages as messagesSchema } from '../db/schema';
import { eq, asc, gt } from 'drizzle-orm';
import { eq, asc, gt, and } from 'drizzle-orm';
import crypto from 'crypto';
import { getFileDetails } from '../utils/files';
import MetaSearchAgent, {
@ -154,6 +154,11 @@ export const handleMessage = async (
const parsedWSMessage = JSON.parse(message) as WSMessage;
const parsedMessage = parsedWSMessage.message;
if (parsedWSMessage.files.length > 0) {
/* TODO: Implement uploads in other classes/single meta class system*/
parsedWSMessage.focusMode = 'webSearch';
}
const humanMessageId =
parsedMessage.messageId ?? crypto.randomBytes(7).toString('hex');
const aiMessageId = crypto.randomBytes(7).toString('hex');
@ -233,7 +238,12 @@ export const handleMessage = async (
} else {
await db
.delete(messagesSchema)
.where(gt(messagesSchema.id, messageExists.id))
.where(
and(
gt(messagesSchema.id, messageExists.id),
eq(messagesSchema.chatId, parsedMessage.chatId),
),
)
.execute();
}
} catch (err) {

664
ui/app/settings/page.tsx Normal file
View File

@ -0,0 +1,664 @@
'use client';
import { Settings as SettingsIcon, ArrowLeft, Loader2 } from 'lucide-react';
import { useEffect, useState } from 'react';
import { cn } from '@/lib/utils';
import { Switch } from '@headlessui/react';
import ThemeSwitcher from '@/components/theme/Switcher';
import { ImagesIcon, VideoIcon } from 'lucide-react';
import Link from 'next/link';
interface SettingsType {
chatModelProviders: {
[key: string]: [Record<string, any>];
};
embeddingModelProviders: {
[key: string]: [Record<string, any>];
};
openaiApiKey: string;
groqApiKey: string;
anthropicApiKey: string;
geminiApiKey: string;
ollamaApiUrl: string;
customOpenaiApiKey: string;
customOpenaiApiUrl: string;
customOpenaiModelName: string;
}
interface InputProps extends React.InputHTMLAttributes<HTMLInputElement> {
isSaving?: boolean;
onSave?: (value: string) => void;
}
const Input = ({ className, isSaving, onSave, ...restProps }: InputProps) => {
return (
<div className="relative">
<input
{...restProps}
className={cn(
'bg-light-secondary dark:bg-dark-secondary w-full px-3 py-2 flex items-center overflow-hidden border border-light-200 dark:border-dark-200 dark:text-white rounded-lg text-sm',
isSaving && 'pr-10',
className,
)}
onBlur={(e) => onSave?.(e.target.value)}
/>
{isSaving && (
<div className="absolute right-3 top-1/2 -translate-y-1/2">
<Loader2
size={16}
className="animate-spin text-black/70 dark:text-white/70"
/>
</div>
)}
</div>
);
};
const Select = ({
className,
options,
...restProps
}: React.SelectHTMLAttributes<HTMLSelectElement> & {
options: { value: string; label: string; disabled?: boolean }[];
}) => {
return (
<select
{...restProps}
className={cn(
'bg-light-secondary dark:bg-dark-secondary px-3 py-2 flex items-center overflow-hidden border border-light-200 dark:border-dark-200 dark:text-white rounded-lg text-sm',
className,
)}
>
{options.map(({ label, value, disabled }) => (
<option key={value} value={value} disabled={disabled}>
{label}
</option>
))}
</select>
);
};
const SettingsSection = ({
title,
children,
}: {
title: string;
children: React.ReactNode;
}) => (
<div className="flex flex-col space-y-4 p-4 bg-light-secondary/50 dark:bg-dark-secondary/50 rounded-xl border border-light-200 dark:border-dark-200">
<h2 className="text-black/90 dark:text-white/90 font-medium">{title}</h2>
{children}
</div>
);
const Page = () => {
const [config, setConfig] = useState<SettingsType | null>(null);
const [chatModels, setChatModels] = useState<Record<string, any>>({});
const [embeddingModels, setEmbeddingModels] = useState<Record<string, any>>(
{},
);
const [selectedChatModelProvider, setSelectedChatModelProvider] = useState<
string | null
>(null);
const [selectedChatModel, setSelectedChatModel] = useState<string | null>(
null,
);
const [selectedEmbeddingModelProvider, setSelectedEmbeddingModelProvider] =
useState<string | null>(null);
const [selectedEmbeddingModel, setSelectedEmbeddingModel] = useState<
string | null
>(null);
const [isLoading, setIsLoading] = useState(false);
const [automaticImageSearch, setAutomaticImageSearch] = useState(false);
const [automaticVideoSearch, setAutomaticVideoSearch] = useState(false);
const [savingStates, setSavingStates] = useState<Record<string, boolean>>({});
useEffect(() => {
const fetchConfig = async () => {
setIsLoading(true);
const res = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/config`, {
headers: {
'Content-Type': 'application/json',
},
});
const data = (await res.json()) as SettingsType;
setConfig(data);
const chatModelProvidersKeys = Object.keys(data.chatModelProviders || {});
const embeddingModelProvidersKeys = Object.keys(
data.embeddingModelProviders || {},
);
const defaultChatModelProvider =
chatModelProvidersKeys.length > 0 ? chatModelProvidersKeys[0] : '';
const defaultEmbeddingModelProvider =
embeddingModelProvidersKeys.length > 0
? embeddingModelProvidersKeys[0]
: '';
const chatModelProvider =
localStorage.getItem('chatModelProvider') ||
defaultChatModelProvider ||
'';
const chatModel =
localStorage.getItem('chatModel') ||
(data.chatModelProviders &&
data.chatModelProviders[chatModelProvider]?.length > 0
? data.chatModelProviders[chatModelProvider][0].name
: undefined) ||
'';
const embeddingModelProvider =
localStorage.getItem('embeddingModelProvider') ||
defaultEmbeddingModelProvider ||
'';
const embeddingModel =
localStorage.getItem('embeddingModel') ||
(data.embeddingModelProviders &&
data.embeddingModelProviders[embeddingModelProvider]?.[0].name) ||
'';
setSelectedChatModelProvider(chatModelProvider);
setSelectedChatModel(chatModel);
setSelectedEmbeddingModelProvider(embeddingModelProvider);
setSelectedEmbeddingModel(embeddingModel);
setChatModels(data.chatModelProviders || {});
setEmbeddingModels(data.embeddingModelProviders || {});
setAutomaticImageSearch(
localStorage.getItem('autoImageSearch') === 'true',
);
setAutomaticVideoSearch(
localStorage.getItem('autoVideoSearch') === 'true',
);
setIsLoading(false);
};
fetchConfig();
}, []);
const saveConfig = async (key: string, value: any) => {
setSavingStates((prev) => ({ ...prev, [key]: true }));
try {
const updatedConfig = {
...config,
[key]: value,
} as SettingsType;
const response = await fetch(
`${process.env.NEXT_PUBLIC_API_URL}/config`,
{
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify(updatedConfig),
},
);
if (!response.ok) {
throw new Error('Failed to update config');
}
setConfig(updatedConfig);
if (
key.toLowerCase().includes('api') ||
key.toLowerCase().includes('url')
) {
const res = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/config`, {
headers: {
'Content-Type': 'application/json',
},
});
if (!res.ok) {
throw new Error('Failed to fetch updated config');
}
const data = await res.json();
setChatModels(data.chatModelProviders || {});
setEmbeddingModels(data.embeddingModelProviders || {});
const currentProvider = selectedChatModelProvider;
const newProviders = Object.keys(data.chatModelProviders || {});
if (!currentProvider && newProviders.length > 0) {
const firstProvider = newProviders[0];
const firstModel = data.chatModelProviders[firstProvider]?.[0]?.name;
if (firstModel) {
setSelectedChatModelProvider(firstProvider);
setSelectedChatModel(firstModel);
localStorage.setItem('chatModelProvider', firstProvider);
localStorage.setItem('chatModel', firstModel);
}
} else if (
currentProvider &&
(!data.chatModelProviders ||
!data.chatModelProviders[currentProvider] ||
!Array.isArray(data.chatModelProviders[currentProvider]) ||
data.chatModelProviders[currentProvider].length === 0)
) {
const firstValidProvider = Object.entries(
data.chatModelProviders || {},
).find(
([_, models]) => Array.isArray(models) && models.length > 0,
)?.[0];
if (firstValidProvider) {
setSelectedChatModelProvider(firstValidProvider);
setSelectedChatModel(
data.chatModelProviders[firstValidProvider][0].name,
);
localStorage.setItem('chatModelProvider', firstValidProvider);
localStorage.setItem(
'chatModel',
data.chatModelProviders[firstValidProvider][0].name,
);
} else {
setSelectedChatModelProvider(null);
setSelectedChatModel(null);
localStorage.removeItem('chatModelProvider');
localStorage.removeItem('chatModel');
}
}
setConfig(data);
}
if (key === 'automaticImageSearch') {
localStorage.setItem('autoImageSearch', value.toString());
} else if (key === 'automaticVideoSearch') {
localStorage.setItem('autoVideoSearch', value.toString());
} else if (key === 'chatModelProvider') {
localStorage.setItem('chatModelProvider', value);
} else if (key === 'chatModel') {
localStorage.setItem('chatModel', value);
}
} catch (err) {
console.error('Failed to save:', err);
setConfig((prev) => ({ ...prev! }));
} finally {
setTimeout(() => {
setSavingStates((prev) => ({ ...prev, [key]: false }));
}, 500);
}
};
return (
<div className="max-w-3xl mx-auto">
<div className="flex flex-col pt-4">
<div className="flex items-center space-x-2">
<Link href="/" className="lg:hidden">
<ArrowLeft className="text-black/70 dark:text-white/70" />
</Link>
<div className="flex flex-row space-x-0.5 items-center">
<SettingsIcon size={23} />
<h1 className="text-3xl font-medium p-2">Settings</h1>
</div>
</div>
<hr className="border-t border-[#2B2C2C] my-4 w-full" />
</div>
{isLoading ? (
<div className="flex flex-row items-center justify-center min-h-[50vh]">
<svg
aria-hidden="true"
className="w-8 h-8 text-light-200 fill-light-secondary dark:text-[#202020] animate-spin dark:fill-[#ffffff3b]"
viewBox="0 0 100 101"
fill="none"
xmlns="http://www.w3.org/2000/svg"
>
<path
d="M100 50.5908C100.003 78.2051 78.1951 100.003 50.5908 100C22.9765 99.9972 0.997224 78.018 1 50.4037C1.00281 22.7993 22.8108 0.997224 50.4251 1C78.0395 1.00281 100.018 22.8108 100 50.4251ZM9.08164 50.594C9.06312 73.3997 27.7909 92.1272 50.5966 92.1457C73.4023 92.1642 92.1298 73.4365 92.1483 50.6308C92.1669 27.8251 73.4392 9.0973 50.6335 9.07878C27.8278 9.06026 9.10003 27.787 9.08164 50.594Z"
fill="currentColor"
/>
<path
d="M93.9676 39.0409C96.393 38.4037 97.8624 35.9116 96.9801 33.5533C95.1945 28.8227 92.871 24.3692 90.0681 20.348C85.6237 14.1775 79.4473 9.36872 72.0454 6.45794C64.6435 3.54717 56.3134 2.65431 48.3133 3.89319C45.869 4.27179 44.3768 6.77534 45.014 9.20079C45.6512 11.6262 48.1343 13.0956 50.5786 12.717C56.5073 11.8281 62.5542 12.5399 68.0406 14.7911C73.527 17.0422 78.2187 20.7487 81.5841 25.4923C83.7976 28.5886 85.4467 32.059 86.4416 35.7474C87.1273 38.1189 89.5423 39.6781 91.9676 39.0409Z"
fill="currentFill"
/>
</svg>
</div>
) : (
config && (
<div className="flex flex-col space-y-6 pb-28 lg:pb-8">
<SettingsSection title="Appearance">
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Theme
</p>
<ThemeSwitcher />
</div>
</SettingsSection>
<SettingsSection title="Automatic Search">
<div className="flex flex-col space-y-4">
<div className="flex items-center justify-between p-3 bg-light-secondary dark:bg-dark-secondary rounded-lg hover:bg-light-200 dark:hover:bg-dark-200 transition-colors">
<div className="flex items-center space-x-3">
<div className="p-2 bg-light-200 dark:bg-dark-200 rounded-lg">
<ImagesIcon
size={18}
className="text-black/70 dark:text-white/70"
/>
</div>
<div>
<p className="text-sm text-black/90 dark:text-white/90 font-medium">
Automatic Image Search
</p>
<p className="text-xs text-black/60 dark:text-white/60 mt-0.5">
Automatically search for relevant images in chat
responses
</p>
</div>
</div>
<Switch
checked={automaticImageSearch}
onChange={(checked) => {
setAutomaticImageSearch(checked);
saveConfig('automaticImageSearch', checked);
}}
className={cn(
automaticImageSearch
? 'bg-[#24A0ED]'
: 'bg-light-200 dark:bg-dark-200',
'relative inline-flex h-6 w-11 items-center rounded-full transition-colors focus:outline-none',
)}
>
<span
className={cn(
automaticImageSearch
? 'translate-x-6'
: 'translate-x-1',
'inline-block h-4 w-4 transform rounded-full bg-white transition-transform',
)}
/>
</Switch>
</div>
<div className="flex items-center justify-between p-3 bg-light-secondary dark:bg-dark-secondary rounded-lg hover:bg-light-200 dark:hover:bg-dark-200 transition-colors">
<div className="flex items-center space-x-3">
<div className="p-2 bg-light-200 dark:bg-dark-200 rounded-lg">
<VideoIcon
size={18}
className="text-black/70 dark:text-white/70"
/>
</div>
<div>
<p className="text-sm text-black/90 dark:text-white/90 font-medium">
Automatic Video Search
</p>
<p className="text-xs text-black/60 dark:text-white/60 mt-0.5">
Automatically search for relevant videos in chat
responses
</p>
</div>
</div>
<Switch
checked={automaticVideoSearch}
onChange={(checked) => {
setAutomaticVideoSearch(checked);
saveConfig('automaticVideoSearch', checked);
}}
className={cn(
automaticVideoSearch
? 'bg-[#24A0ED]'
: 'bg-light-200 dark:bg-dark-200',
'relative inline-flex h-6 w-11 items-center rounded-full transition-colors focus:outline-none',
)}
>
<span
className={cn(
automaticVideoSearch
? 'translate-x-6'
: 'translate-x-1',
'inline-block h-4 w-4 transform rounded-full bg-white transition-transform',
)}
/>
</Switch>
</div>
</div>
</SettingsSection>
<SettingsSection title="Model Settings">
{config.chatModelProviders && (
<div className="flex flex-col space-y-4">
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Chat Model Provider
</p>
<Select
value={selectedChatModelProvider ?? undefined}
onChange={(e) => {
const value = e.target.value;
setSelectedChatModelProvider(value);
saveConfig('chatModelProvider', value);
// Auto-select first model of new provider
const firstModel =
config.chatModelProviders[value]?.[0]?.name;
if (firstModel) {
setSelectedChatModel(firstModel);
saveConfig('chatModel', firstModel);
}
}}
options={Object.keys(config.chatModelProviders).map(
(provider) => ({
value: provider,
label:
provider.charAt(0).toUpperCase() +
provider.slice(1),
}),
)}
/>
</div>
{selectedChatModelProvider &&
selectedChatModelProvider != 'custom_openai' && (
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Chat Model
</p>
<Select
value={selectedChatModel ?? undefined}
onChange={(e) => {
const value = e.target.value;
setSelectedChatModel(value);
saveConfig('chatModel', value);
}}
options={(() => {
const chatModelProvider =
config.chatModelProviders[
selectedChatModelProvider
];
return chatModelProvider
? chatModelProvider.length > 0
? chatModelProvider.map((model) => ({
value: model.name,
label: model.displayName,
}))
: [
{
value: '',
label: 'No models available',
disabled: true,
},
]
: [
{
value: '',
label:
'Invalid provider, please check backend logs',
disabled: true,
},
];
})()}
/>
</div>
)}
</div>
)}
{selectedChatModelProvider &&
selectedChatModelProvider === 'custom_openai' && (
<div className="flex flex-col space-y-4">
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Model Name
</p>
<Input
type="text"
placeholder="Model name"
defaultValue={config.customOpenaiModelName}
onChange={(e) =>
setConfig({
...config,
customOpenaiModelName: e.target.value,
})
}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Custom OpenAI API Key
</p>
<Input
type="text"
placeholder="Custom OpenAI API Key"
defaultValue={config.customOpenaiApiKey}
onChange={(e) =>
setConfig({
...config,
customOpenaiApiKey: e.target.value,
})
}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Custom OpenAI Base URL
</p>
<Input
type="text"
placeholder="Custom OpenAI Base URL"
defaultValue={config.customOpenaiApiUrl}
onChange={(e) =>
setConfig({
...config,
customOpenaiApiUrl: e.target.value,
})
}
/>
</div>
</div>
)}
</SettingsSection>
<SettingsSection title="API Keys">
<div className="flex flex-col space-y-4">
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
OpenAI API Key
</p>
<Input
type="text"
placeholder="OpenAI API Key"
value={config.openaiApiKey}
isSaving={savingStates['openaiApiKey']}
onChange={(e) => {
setConfig((prev) => ({
...prev!,
openaiApiKey: e.target.value,
}));
}}
onSave={(value) => saveConfig('openaiApiKey', value)}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Ollama API URL
</p>
<Input
type="text"
placeholder="Ollama API URL"
value={config.ollamaApiUrl}
isSaving={savingStates['ollamaApiUrl']}
onChange={(e) => {
setConfig((prev) => ({
...prev!,
ollamaApiUrl: e.target.value,
}));
}}
onSave={(value) => saveConfig('ollamaApiUrl', value)}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
GROQ API Key
</p>
<Input
type="text"
placeholder="GROQ API Key"
value={config.groqApiKey}
isSaving={savingStates['groqApiKey']}
onChange={(e) => {
setConfig((prev) => ({
...prev!,
groqApiKey: e.target.value,
}));
}}
onSave={(value) => saveConfig('groqApiKey', value)}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Anthropic API Key
</p>
<Input
type="text"
placeholder="Anthropic API key"
value={config.anthropicApiKey}
isSaving={savingStates['anthropicApiKey']}
onChange={(e) => {
setConfig((prev) => ({
...prev!,
anthropicApiKey: e.target.value,
}));
}}
onSave={(value) => saveConfig('anthropicApiKey', value)}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Gemini API Key
</p>
<Input
type="text"
placeholder="Gemini API key"
value={config.geminiApiKey}
isSaving={savingStates['geminiApiKey']}
onChange={(e) => {
setConfig((prev) => ({
...prev!,
geminiApiKey: e.target.value,
}));
}}
onSave={(value) => saveConfig('geminiApiKey', value)}
/>
</div>
</div>
</SettingsSection>
</div>
)
)}
</div>
);
};
export default Page;

View File

@ -9,7 +9,9 @@ import crypto from 'crypto';
import { toast } from 'sonner';
import { useSearchParams } from 'next/navigation';
import { getSuggestions } from '@/lib/actions';
import Error from 'next/error';
import { Settings } from 'lucide-react';
import Link from 'next/link';
import NextError from 'next/error';
export type Message = {
messageId: string;
@ -32,11 +34,25 @@ const useSocket = (
setIsWSReady: (ready: boolean) => void,
setError: (error: boolean) => void,
) => {
const [ws, setWs] = useState<WebSocket | null>(null);
const wsRef = useRef<WebSocket | null>(null);
const reconnectTimeoutRef = useRef<NodeJS.Timeout>();
const retryCountRef = useRef(0);
const isCleaningUpRef = useRef(false);
const MAX_RETRIES = 3;
const INITIAL_BACKOFF = 1000; // 1 second
const isConnectionErrorRef = useRef(false);
const getBackoffDelay = (retryCount: number) => {
return Math.min(INITIAL_BACKOFF * Math.pow(2, retryCount), 10000); // Cap at 10 seconds
};
useEffect(() => {
if (!ws) {
const connectWs = async () => {
const connectWs = async () => {
if (wsRef.current?.readyState === WebSocket.OPEN) {
wsRef.current.close();
}
try {
let chatModel = localStorage.getItem('chatModel');
let chatModelProvider = localStorage.getItem('chatModelProvider');
let embeddingModel = localStorage.getItem('embeddingModel');
@ -44,6 +60,17 @@ const useSocket = (
'embeddingModelProvider',
);
const autoImageSearch = localStorage.getItem('autoImageSearch');
const autoVideoSearch = localStorage.getItem('autoVideoSearch');
if (!autoImageSearch) {
localStorage.setItem('autoImageSearch', 'true');
}
if (!autoVideoSearch) {
localStorage.setItem('autoVideoSearch', 'false');
}
const providers = await fetch(
`${process.env.NEXT_PUBLIC_API_URL}/models`,
{
@ -51,7 +78,13 @@ const useSocket = (
'Content-Type': 'application/json',
},
},
).then(async (res) => await res.json());
).then(async (res) => {
if (!res.ok)
throw new Error(
`Failed to fetch models: ${res.status} ${res.statusText}`,
);
return res.json();
});
if (
!chatModel ||
@ -62,22 +95,16 @@ const useSocket = (
if (!chatModel || !chatModelProvider) {
const chatModelProviders = providers.chatModelProviders;
chatModelProvider = Object.keys(chatModelProviders)[0];
chatModelProvider =
chatModelProvider || Object.keys(chatModelProviders)[0];
if (chatModelProvider === 'custom_openai') {
toast.error(
'Seems like you are using the custom OpenAI provider, please open the settings and configure the API key and base URL',
);
setError(true);
return;
} else {
chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
if (
!chatModelProviders ||
Object.keys(chatModelProviders).length === 0
)
return toast.error('No chat models available');
}
chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
if (
!chatModelProviders ||
Object.keys(chatModelProviders).length === 0
)
return toast.error('No chat models available');
}
if (!embeddingModel || !embeddingModelProvider) {
@ -110,16 +137,26 @@ const useSocket = (
Object.keys(chatModelProviders).length > 0 &&
!chatModelProviders[chatModelProvider]
) {
chatModelProvider = Object.keys(chatModelProviders)[0];
const chatModelProvidersKeys = Object.keys(chatModelProviders);
chatModelProvider =
chatModelProvidersKeys.find(
(key) => Object.keys(chatModelProviders[key]).length > 0,
) || chatModelProvidersKeys[0];
localStorage.setItem('chatModelProvider', chatModelProvider);
}
if (
chatModelProvider &&
chatModelProvider != 'custom_openai' &&
!chatModelProviders[chatModelProvider][chatModel]
) {
chatModel = Object.keys(chatModelProviders[chatModelProvider])[0];
chatModel = Object.keys(
chatModelProviders[
Object.keys(chatModelProviders[chatModelProvider]).length > 0
? chatModelProvider
: Object.keys(chatModelProviders)[0]
],
)[0];
localStorage.setItem('chatModel', chatModel);
}
@ -168,6 +205,7 @@ const useSocket = (
wsURL.search = searchParams.toString();
const ws = new WebSocket(wsURL.toString());
wsRef.current = ws;
const timeoutId = setTimeout(() => {
if (ws.readyState !== 1) {
@ -183,37 +221,88 @@ const useSocket = (
const interval = setInterval(() => {
if (ws.readyState === 1) {
setIsWSReady(true);
setError(false);
if (retryCountRef.current > 0) {
toast.success('Connection restored.');
}
retryCountRef.current = 0;
clearInterval(interval);
}
}, 5);
clearTimeout(timeoutId);
console.log('[DEBUG] opened');
console.debug(new Date(), 'ws:connected');
}
if (data.type === 'error') {
isConnectionErrorRef.current = true;
setError(true);
toast.error(data.data);
}
});
ws.onerror = () => {
clearTimeout(timeoutId);
setError(true);
setIsWSReady(false);
toast.error('WebSocket connection error.');
};
ws.onclose = () => {
clearTimeout(timeoutId);
setError(true);
console.log('[DEBUG] closed');
setIsWSReady(false);
console.debug(new Date(), 'ws:disconnected');
if (!isCleaningUpRef.current && !isConnectionErrorRef.current) {
toast.error('Connection lost. Attempting to reconnect...');
attemptReconnect();
}
};
} catch (error) {
console.debug(new Date(), 'ws:error', error);
setIsWSReady(false);
attemptReconnect();
}
};
setWs(ws);
};
const attemptReconnect = () => {
retryCountRef.current += 1;
connectWs();
}
}, [ws, url, setIsWSReady, setError]);
if (retryCountRef.current > MAX_RETRIES) {
console.debug(new Date(), 'ws:max_retries');
setError(true);
toast.error(
'Unable to connect to server after multiple attempts. Please refresh the page to try again.',
);
return;
}
return ws;
const backoffDelay = getBackoffDelay(retryCountRef.current);
console.debug(
new Date(),
`ws:retry attempt=${retryCountRef.current}/${MAX_RETRIES} delay=${backoffDelay}ms`,
);
if (reconnectTimeoutRef.current) {
clearTimeout(reconnectTimeoutRef.current);
}
reconnectTimeoutRef.current = setTimeout(() => {
connectWs();
}, backoffDelay);
};
connectWs();
return () => {
if (reconnectTimeoutRef.current) {
clearTimeout(reconnectTimeoutRef.current);
}
if (wsRef.current?.readyState === WebSocket.OPEN) {
wsRef.current.close();
isCleaningUpRef.current = true;
console.debug(new Date(), 'ws:cleanup');
}
};
}, [url, setIsWSReady, setError]);
return wsRef.current;
};
const loadMessages = async (
@ -257,7 +346,7 @@ const loadMessages = async (
return [msg.role, msg.content];
}) as [string, string][];
console.log('[DEBUG] messages loaded');
console.debug(new Date(), 'app:messages_loaded');
document.title = messages[0].content;
@ -310,6 +399,8 @@ const ChatWindow = ({ id }: { id?: string }) => {
const [notFound, setNotFound] = useState(false);
const [isSettingsOpen, setIsSettingsOpen] = useState(false);
useEffect(() => {
if (
chatId &&
@ -339,7 +430,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
return () => {
if (ws?.readyState === 1) {
ws.close();
console.log('[DEBUG] closed');
console.debug(new Date(), 'ws:cleanup');
}
};
// eslint-disable-next-line react-hooks/exhaustive-deps
@ -354,12 +445,18 @@ const ChatWindow = ({ id }: { id?: string }) => {
useEffect(() => {
if (isMessagesLoaded && isWSReady) {
setIsReady(true);
console.log('[DEBUG] ready');
console.debug(new Date(), 'app:ready');
} else {
setIsReady(false);
}
}, [isMessagesLoaded, isWSReady]);
const sendMessage = async (message: string, messageId?: string) => {
if (loading) return;
if (!ws || ws.readyState !== WebSocket.OPEN) {
toast.error('Cannot send message while disconnected');
return;
}
setLoading(true);
setMessageAppeared(false);
@ -370,7 +467,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
messageId = messageId ?? crypto.randomBytes(7).toString('hex');
ws?.send(
ws.send(
JSON.stringify({
type: 'message',
message: {
@ -482,6 +579,17 @@ const ChatWindow = ({ id }: { id?: string }) => {
}),
);
}
const autoImageSearch = localStorage.getItem('autoImageSearch');
const autoVideoSearch = localStorage.getItem('autoVideoSearch');
if (autoImageSearch === 'true') {
document.getElementById('search-images')?.click();
}
if (autoVideoSearch === 'true') {
document.getElementById('search-videos')?.click();
}
}
};
@ -514,17 +622,24 @@ const ChatWindow = ({ id }: { id?: string }) => {
if (hasError) {
return (
<div className="flex flex-col items-center justify-center min-h-screen">
<p className="dark:text-white/70 text-black/70 text-sm">
Failed to connect to the server. Please try again later.
</p>
<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>
</div>
<div className="flex flex-col items-center justify-center min-h-screen">
<p className="dark:text-white/70 text-black/70 text-sm">
Failed to connect to the server. Please try again later.
</p>
</div>
</div>
);
}
return isReady ? (
notFound ? (
<Error statusCode={404} />
<NextError statusCode={404} />
) : (
<div>
{messages.length > 0 ? (

View File

@ -1,8 +1,8 @@
import { Settings } from 'lucide-react';
import EmptyChatMessageInput from './EmptyChatMessageInput';
import SettingsDialog from './SettingsDialog';
import { useState } from 'react';
import { File } from './ChatWindow';
import Link from 'next/link';
const EmptyChat = ({
sendMessage,
@ -29,12 +29,10 @@ const EmptyChat = ({
return (
<div className="relative">
<SettingsDialog isOpen={isSettingsOpen} setIsOpen={setIsSettingsOpen} />
<div className="absolute w-full flex flex-row items-center justify-end mr-5 mt-5">
<Settings
className="cursor-pointer lg:hidden"
onClick={() => setIsSettingsOpen(true)}
/>
<Link href="/settings">
<Settings className="cursor-pointer lg:hidden" />
</Link>
</div>
<div className="flex flex-col items-center justify-center min-h-screen max-w-screen-sm mx-auto p-2 space-y-8">
<h2 className="text-black/70 dark:text-white/70 text-3xl font-medium -mt-8">

View File

@ -107,8 +107,8 @@ const MessageBox = ({
</div>
<Markdown
className={cn(
'prose dark:prose-invert prose-p:leading-relaxed prose-pre:p-0',
'max-w-none break-words text-black dark:text-white text-sm md:text-base font-medium',
'prose prose-h1:mb-3 prose-h2:mb-2 prose-h2:mt-6 prose-h2:font-[800] prose-h3:mt-4 prose-h3:mb-1.5 prose-h3:font-[600] dark:prose-invert prose-p:leading-relaxed prose-pre:p-0 font-[400]',
'max-w-none break-words text-black dark:text-white',
)}
>
{parsedMessage}

View File

@ -83,7 +83,7 @@ const Focus = ({
{focusMode !== 'webSearch' ? (
<div className="flex flex-row items-center space-x-1">
{focusModes.find((mode) => mode.key === focusMode)?.icon}
<p className="text-xs font-medium">
<p className="text-xs font-medium hidden lg:block">
{focusModes.find((mode) => mode.key === focusMode)?.title}
</p>
<ChevronDown size={20} className="-translate-x-1" />
@ -91,7 +91,7 @@ const Focus = ({
) : (
<div className="flex flex-row items-center space-x-1">
<ScanEye size={20} />
<p className="text-xs font-medium">Focus</p>
<p className="text-xs font-medium hidden lg:block">Focus</p>
</div>
)}
</PopoverButton>

View File

@ -27,6 +27,7 @@ const SearchImages = ({
<>
{!loading && images === null && (
<button
id="search-images"
onClick={async () => {
setLoading(true);

View File

@ -1,6 +1,6 @@
/* eslint-disable @next/next/no-img-element */
import { PlayCircle, PlayIcon, PlusIcon, VideoIcon } from 'lucide-react';
import { useState } from 'react';
import { useRef, useState } from 'react';
import Lightbox, { GenericSlide, VideoSlide } from 'yet-another-react-lightbox';
import 'yet-another-react-lightbox/styles.css';
import { Message } from './ChatWindow';
@ -35,11 +35,14 @@ const Searchvideos = ({
const [loading, setLoading] = useState(false);
const [open, setOpen] = useState(false);
const [slides, setSlides] = useState<VideoSlide[]>([]);
const [currentIndex, setCurrentIndex] = useState(0);
const videoRefs = useRef<(HTMLIFrameElement | null)[]>([]);
return (
<>
{!loading && videos === null && (
<button
id="search-videos"
onClick={async () => {
setLoading(true);
@ -182,18 +185,39 @@ const Searchvideos = ({
open={open}
close={() => setOpen(false)}
slides={slides}
index={currentIndex}
on={{
view: ({ index }) => {
const previousIframe = videoRefs.current[currentIndex];
if (previousIframe?.contentWindow) {
previousIframe.contentWindow.postMessage(
'{"event":"command","func":"pauseVideo","args":""}',
'*',
);
}
setCurrentIndex(index);
},
}}
render={{
slide: ({ slide }) =>
slide.type === 'video-slide' ? (
slide: ({ slide }) => {
const index = slides.findIndex((s) => s === slide);
return slide.type === 'video-slide' ? (
<div className="h-full w-full flex flex-row items-center justify-center">
<iframe
src={slide.iframe_src}
src={`${slide.iframe_src}${slide.iframe_src.includes('?') ? '&' : '?'}enablejsapi=1`}
ref={(el) => {
if (el) {
videoRefs.current[index] = el;
}
}}
className="aspect-video max-h-[95vh] w-[95vw] rounded-2xl md:w-[80vw]"
allowFullScreen
allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture"
/>
</div>
) : null,
) : null;
},
}}
/>
</>

View File

@ -1,511 +0,0 @@
import { cn } from '@/lib/utils';
import {
Dialog,
DialogPanel,
DialogTitle,
Transition,
TransitionChild,
} from '@headlessui/react';
import { CloudUpload, RefreshCcw, RefreshCw } from 'lucide-react';
import React, {
Fragment,
useEffect,
useState,
type SelectHTMLAttributes,
} from 'react';
import ThemeSwitcher from './theme/Switcher';
interface InputProps extends React.InputHTMLAttributes<HTMLInputElement> {}
const Input = ({ className, ...restProps }: InputProps) => {
return (
<input
{...restProps}
className={cn(
'bg-light-secondary dark:bg-dark-secondary px-3 py-2 flex items-center overflow-hidden border border-light-200 dark:border-dark-200 dark:text-white rounded-lg text-sm',
className,
)}
/>
);
};
interface SelectProps extends SelectHTMLAttributes<HTMLSelectElement> {
options: { value: string; label: string; disabled?: boolean }[];
}
export const Select = ({ className, options, ...restProps }: SelectProps) => {
return (
<select
{...restProps}
className={cn(
'bg-light-secondary dark:bg-dark-secondary px-3 py-2 flex items-center overflow-hidden border border-light-200 dark:border-dark-200 dark:text-white rounded-lg text-sm',
className,
)}
>
{options.map(({ label, value, disabled }) => {
return (
<option key={value} value={value} disabled={disabled}>
{label}
</option>
);
})}
</select>
);
};
interface SettingsType {
chatModelProviders: {
[key: string]: [Record<string, any>];
};
embeddingModelProviders: {
[key: string]: [Record<string, any>];
};
openaiApiKey: string;
groqApiKey: string;
anthropicApiKey: string;
ollamaApiUrl: string;
}
const SettingsDialog = ({
isOpen,
setIsOpen,
}: {
isOpen: boolean;
setIsOpen: (isOpen: boolean) => void;
}) => {
const [config, setConfig] = useState<SettingsType | null>(null);
const [chatModels, setChatModels] = useState<Record<string, any>>({});
const [embeddingModels, setEmbeddingModels] = useState<Record<string, any>>(
{},
);
const [selectedChatModelProvider, setSelectedChatModelProvider] = useState<
string | null
>(null);
const [selectedChatModel, setSelectedChatModel] = useState<string | null>(
null,
);
const [selectedEmbeddingModelProvider, setSelectedEmbeddingModelProvider] =
useState<string | null>(null);
const [selectedEmbeddingModel, setSelectedEmbeddingModel] = useState<
string | null
>(null);
const [customOpenAIApiKey, setCustomOpenAIApiKey] = useState<string>('');
const [customOpenAIBaseURL, setCustomOpenAIBaseURL] = useState<string>('');
const [isLoading, setIsLoading] = useState(false);
const [isUpdating, setIsUpdating] = useState(false);
useEffect(() => {
if (isOpen) {
const fetchConfig = async () => {
setIsLoading(true);
const res = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/config`, {
headers: {
'Content-Type': 'application/json',
},
});
const data = (await res.json()) as SettingsType;
setConfig(data);
const chatModelProvidersKeys = Object.keys(
data.chatModelProviders || {},
);
const embeddingModelProvidersKeys = Object.keys(
data.embeddingModelProviders || {},
);
const defaultChatModelProvider =
chatModelProvidersKeys.length > 0 ? chatModelProvidersKeys[0] : '';
const defaultEmbeddingModelProvider =
embeddingModelProvidersKeys.length > 0
? embeddingModelProvidersKeys[0]
: '';
const chatModelProvider =
localStorage.getItem('chatModelProvider') ||
defaultChatModelProvider ||
'';
const chatModel =
localStorage.getItem('chatModel') ||
(data.chatModelProviders &&
data.chatModelProviders[chatModelProvider]?.length > 0
? data.chatModelProviders[chatModelProvider][0].name
: undefined) ||
'';
const embeddingModelProvider =
localStorage.getItem('embeddingModelProvider') ||
defaultEmbeddingModelProvider ||
'';
const embeddingModel =
localStorage.getItem('embeddingModel') ||
(data.embeddingModelProviders &&
data.embeddingModelProviders[embeddingModelProvider]?.[0].name) ||
'';
setSelectedChatModelProvider(chatModelProvider);
setSelectedChatModel(chatModel);
setSelectedEmbeddingModelProvider(embeddingModelProvider);
setSelectedEmbeddingModel(embeddingModel);
setCustomOpenAIApiKey(localStorage.getItem('openAIApiKey') || '');
setCustomOpenAIBaseURL(localStorage.getItem('openAIBaseURL') || '');
setChatModels(data.chatModelProviders || {});
setEmbeddingModels(data.embeddingModelProviders || {});
setIsLoading(false);
};
fetchConfig();
}
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [isOpen]);
const handleSubmit = async () => {
setIsUpdating(true);
try {
await fetch(`${process.env.NEXT_PUBLIC_API_URL}/config`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify(config),
});
localStorage.setItem('chatModelProvider', selectedChatModelProvider!);
localStorage.setItem('chatModel', selectedChatModel!);
localStorage.setItem(
'embeddingModelProvider',
selectedEmbeddingModelProvider!,
);
localStorage.setItem('embeddingModel', selectedEmbeddingModel!);
localStorage.setItem('openAIApiKey', customOpenAIApiKey!);
localStorage.setItem('openAIBaseURL', customOpenAIBaseURL!);
} catch (err) {
console.log(err);
} finally {
setIsUpdating(false);
setIsOpen(false);
window.location.reload();
}
};
return (
<Transition appear show={isOpen} as={Fragment}>
<Dialog
as="div"
className="relative z-50"
onClose={() => setIsOpen(false)}
>
<TransitionChild
as={Fragment}
enter="ease-out duration-300"
enterFrom="opacity-0"
enterTo="opacity-100"
leave="ease-in duration-200"
leaveFrom="opacity-100"
leaveTo="opacity-0"
>
<div className="fixed inset-0 bg-white/50 dark:bg-black/50" />
</TransitionChild>
<div className="fixed inset-0 overflow-y-auto">
<div className="flex min-h-full items-center justify-center p-4 text-center">
<TransitionChild
as={Fragment}
enter="ease-out duration-200"
enterFrom="opacity-0 scale-95"
enterTo="opacity-100 scale-100"
leave="ease-in duration-100"
leaveFrom="opacity-100 scale-200"
leaveTo="opacity-0 scale-95"
>
<DialogPanel className="w-full max-w-md transform rounded-2xl bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-6 text-left align-middle shadow-xl transition-all">
<DialogTitle className="text-xl font-medium leading-6 dark:text-white">
Settings
</DialogTitle>
{config && !isLoading && (
<div className="flex flex-col space-y-4 mt-6">
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Theme
</p>
<ThemeSwitcher />
</div>
{config.chatModelProviders && (
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Chat model Provider
</p>
<Select
value={selectedChatModelProvider ?? undefined}
onChange={(e) => {
setSelectedChatModelProvider(e.target.value);
if (e.target.value === 'custom_openai') {
setSelectedChatModel('');
} else {
setSelectedChatModel(
config.chatModelProviders[e.target.value][0]
.name,
);
}
}}
options={Object.keys(config.chatModelProviders).map(
(provider) => ({
value: provider,
label:
provider.charAt(0).toUpperCase() +
provider.slice(1),
}),
)}
/>
</div>
)}
{selectedChatModelProvider &&
selectedChatModelProvider != 'custom_openai' && (
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Chat Model
</p>
<Select
value={selectedChatModel ?? undefined}
onChange={(e) =>
setSelectedChatModel(e.target.value)
}
options={(() => {
const chatModelProvider =
config.chatModelProviders[
selectedChatModelProvider
];
return chatModelProvider
? chatModelProvider.length > 0
? chatModelProvider.map((model) => ({
value: model.name,
label: model.displayName,
}))
: [
{
value: '',
label: 'No models available',
disabled: true,
},
]
: [
{
value: '',
label:
'Invalid provider, please check backend logs',
disabled: true,
},
];
})()}
/>
</div>
)}
{selectedChatModelProvider &&
selectedChatModelProvider === 'custom_openai' && (
<>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Model name
</p>
<Input
type="text"
placeholder="Model name"
defaultValue={selectedChatModel!}
onChange={(e) =>
setSelectedChatModel(e.target.value)
}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Custom OpenAI API Key
</p>
<Input
type="text"
placeholder="Custom OpenAI API Key"
defaultValue={customOpenAIApiKey!}
onChange={(e) =>
setCustomOpenAIApiKey(e.target.value)
}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Custom OpenAI Base URL
</p>
<Input
type="text"
placeholder="Custom OpenAI Base URL"
defaultValue={customOpenAIBaseURL!}
onChange={(e) =>
setCustomOpenAIBaseURL(e.target.value)
}
/>
</div>
</>
)}
{/* Embedding models */}
{config.embeddingModelProviders && (
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Embedding model Provider
</p>
<Select
value={selectedEmbeddingModelProvider ?? undefined}
onChange={(e) => {
setSelectedEmbeddingModelProvider(e.target.value);
setSelectedEmbeddingModel(
config.embeddingModelProviders[e.target.value][0]
.name,
);
}}
options={Object.keys(
config.embeddingModelProviders,
).map((provider) => ({
label:
provider.charAt(0).toUpperCase() +
provider.slice(1),
value: provider,
}))}
/>
</div>
)}
{selectedEmbeddingModelProvider && (
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Embedding Model
</p>
<Select
value={selectedEmbeddingModel ?? undefined}
onChange={(e) =>
setSelectedEmbeddingModel(e.target.value)
}
options={(() => {
const embeddingModelProvider =
config.embeddingModelProviders[
selectedEmbeddingModelProvider
];
return embeddingModelProvider
? embeddingModelProvider.length > 0
? embeddingModelProvider.map((model) => ({
label: model.displayName,
value: model.name,
}))
: [
{
label: 'No embedding models available',
value: '',
disabled: true,
},
]
: [
{
label:
'Invalid provider, please check backend logs',
value: '',
disabled: true,
},
];
})()}
/>
</div>
)}
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
OpenAI API Key
</p>
<Input
type="text"
placeholder="OpenAI API Key"
defaultValue={config.openaiApiKey}
onChange={(e) =>
setConfig({
...config,
openaiApiKey: e.target.value,
})
}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Ollama API URL
</p>
<Input
type="text"
placeholder="Ollama API URL"
defaultValue={config.ollamaApiUrl}
onChange={(e) =>
setConfig({
...config,
ollamaApiUrl: e.target.value,
})
}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
GROQ API Key
</p>
<Input
type="text"
placeholder="GROQ API Key"
defaultValue={config.groqApiKey}
onChange={(e) =>
setConfig({
...config,
groqApiKey: e.target.value,
})
}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Anthropic API Key
</p>
<Input
type="text"
placeholder="Anthropic API key"
defaultValue={config.anthropicApiKey}
onChange={(e) =>
setConfig({
...config,
anthropicApiKey: e.target.value,
})
}
/>
</div>
</div>
)}
{isLoading && (
<div className="w-full flex items-center justify-center mt-6 text-black/70 dark:text-white/70 py-6">
<RefreshCcw className="animate-spin" />
</div>
)}
<div className="w-full mt-6 space-y-2">
<p className="text-xs text-black/50 dark:text-white/50">
We&apos;ll refresh the page after updating the settings.
</p>
<button
onClick={handleSubmit}
className="bg-[#24A0ED] flex flex-row items-center space-x-2 text-white disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#ececec21] rounded-full px-4 py-2"
disabled={isLoading || isUpdating}
>
{isUpdating ? (
<RefreshCw size={20} className="animate-spin" />
) : (
<CloudUpload size={20} />
)}
</button>
</div>
</DialogPanel>
</TransitionChild>
</div>
</div>
</Dialog>
</Transition>
);
};
export default SettingsDialog;

View File

@ -6,7 +6,6 @@ import Link from 'next/link';
import { useSelectedLayoutSegments } from 'next/navigation';
import React, { useState, type ReactNode } from 'react';
import Layout from './Layout';
import SettingsDialog from './SettingsDialog';
const VerticalIconContainer = ({ children }: { children: ReactNode }) => {
return (
@ -67,15 +66,9 @@ const Sidebar = ({ children }: { children: React.ReactNode }) => {
))}
</VerticalIconContainer>
<Settings
onClick={() => setIsSettingsOpen(!isSettingsOpen)}
className="cursor-pointer"
/>
<SettingsDialog
isOpen={isSettingsOpen}
setIsOpen={setIsSettingsOpen}
/>
<Link href="/settings">
<Settings className="cursor-pointer" />
</Link>
</div>
</div>

View File

@ -1,8 +1,7 @@
'use client';
import { useTheme } from 'next-themes';
import { SunIcon, MoonIcon, MonitorIcon } from 'lucide-react';
import { useCallback, useEffect, useState } from 'react';
import { Select } from '../SettingsDialog';
import Select from '../ui/Select';
type Theme = 'dark' | 'light' | 'system';

View File

@ -0,0 +1,28 @@
import { cn } from '@/lib/utils';
import { SelectHTMLAttributes } from 'react';
interface SelectProps extends SelectHTMLAttributes<HTMLSelectElement> {
options: { value: string; label: string; disabled?: boolean }[];
}
export const Select = ({ className, options, ...restProps }: SelectProps) => {
return (
<select
{...restProps}
className={cn(
'bg-light-secondary dark:bg-dark-secondary px-3 py-2 flex items-center overflow-hidden border border-light-200 dark:border-dark-200 dark:text-white rounded-lg text-sm',
className,
)}
>
{options.map(({ label, value, disabled }) => {
return (
<option key={value} value={value} disabled={disabled}>
{label}
</option>
);
})}
</select>
);
};
export default Select;

View File

@ -1,6 +1,6 @@
{
"name": "perplexica-frontend",
"version": "1.9.3",
"version": "1.10.0-rc3",
"license": "MIT",
"author": "ItzCrazyKns",
"scripts": {
@ -18,7 +18,7 @@
"clsx": "^2.1.0",
"langchain": "^0.1.30",
"lucide-react": "^0.363.0",
"markdown-to-jsx": "^7.6.2",
"markdown-to-jsx": "^7.7.2",
"next": "14.1.4",
"next-themes": "^0.3.0",
"react": "^18",

View File

@ -2210,10 +2210,10 @@ lucide-react@^0.363.0:
resolved "https://registry.yarnpkg.com/lucide-react/-/lucide-react-0.363.0.tgz#2bb1f9d09b830dda86f5118fcd097f87247fe0e3"
integrity sha512-AlsfPCsXQyQx7wwsIgzcKOL9LwC498LIMAo+c0Es5PkHJa33xwmYAkkSoKoJWWWSYQEStqu58/jT4tL2gi32uQ==
markdown-to-jsx@^7.6.2:
version "7.6.2"
resolved "https://registry.yarnpkg.com/markdown-to-jsx/-/markdown-to-jsx-7.6.2.tgz#254cbf7d412a37073486c0a2dd52266d2191a793"
integrity sha512-gEcyiJXzBxmId2Y/kydLbD6KRNccDiUy/Src1cFGn3s2X0LZZ/hUiEc2VisFyA5kUE3SXclTCczjQiAuqKZiFQ==
markdown-to-jsx@^7.7.2:
version "7.7.2"
resolved "https://registry.yarnpkg.com/markdown-to-jsx/-/markdown-to-jsx-7.7.2.tgz#59c1dd64f48b53719311ab140be3cd51cdabccd3"
integrity sha512-N3AKfYRvxNscvcIH6HDnDKILp4S8UWbebp+s92Y8SwIq0CuSbLW4Jgmrbjku3CWKjTQO0OyIMS6AhzqrwjEa3g==
md5@^2.3.0:
version "2.3.0"

View File

@ -293,6 +293,11 @@
resolved "https://registry.yarnpkg.com/@esbuild/win32-x64/-/win32-x64-0.19.12.tgz#c57c8afbb4054a3ab8317591a0b7320360b444ae"
integrity sha512-T1QyPSDCyMXaO3pzBkF96E8xMkiRYbUEZADd29SyPGabqxMViNoii+NcK7eWJAEoU6RZyEm5lVSIjTmcdoB9HA==
"@google/generative-ai@^0.7.0":
version "0.7.1"
resolved "https://registry.yarnpkg.com/@google/generative-ai/-/generative-ai-0.7.1.tgz#eb187c75080c0706245699dbc06816c830d8c6a7"
integrity sha512-WTjMLLYL/xfA5BW6xAycRPiAX7FNHKAxrid/ayqC1QMam0KAK0NbMeS9Lubw80gVg5xFMLE+H7pw4wdNzTOlxw==
"@huggingface/jinja@^0.2.2":
version "0.2.2"
resolved "https://registry.yarnpkg.com/@huggingface/jinja/-/jinja-0.2.2.tgz#faeb205a9d6995089bef52655ddd8245d3190627"
@ -380,6 +385,23 @@
zod "^3.22.4"
zod-to-json-schema "^3.22.3"
"@langchain/core@>=0.2.16 <0.3.0":
version "0.2.36"
resolved "https://registry.yarnpkg.com/@langchain/core/-/core-0.2.36.tgz#75754c33aa5b9310dcf117047374a1ae011005a4"
integrity sha512-qHLvScqERDeH7y2cLuJaSAlMwg3f/3Oc9nayRSXRU2UuaK/SOhI42cxiPLj1FnuHJSmN0rBQFkrLx02gI4mcVg==
dependencies:
ansi-styles "^5.0.0"
camelcase "6"
decamelize "1.2.0"
js-tiktoken "^1.0.12"
langsmith "^0.1.56-rc.1"
mustache "^4.2.0"
p-queue "^6.6.2"
p-retry "4"
uuid "^10.0.0"
zod "^3.22.4"
zod-to-json-schema "^3.22.3"
"@langchain/core@>=0.2.9 <0.3.0":
version "0.2.15"
resolved "https://registry.yarnpkg.com/@langchain/core/-/core-0.2.15.tgz#1bb99ac4fffe935c7ba37edcaa91abfba3c82219"
@ -415,6 +437,15 @@
zod "^3.22.4"
zod-to-json-schema "^3.22.3"
"@langchain/google-genai@^0.0.23":
version "0.0.23"
resolved "https://registry.yarnpkg.com/@langchain/google-genai/-/google-genai-0.0.23.tgz#e73af501bc1df4c7642b531759b82dc3eb7ae459"
integrity sha512-MTSCJEoKsfU1inz0PWvAjITdNFM4s41uvBCwLpcgx3jWJIEisczFD82x86ahYqJlb2fD6tohYSaCH/4tKAdkXA==
dependencies:
"@google/generative-ai" "^0.7.0"
"@langchain/core" ">=0.2.16 <0.3.0"
zod-to-json-schema "^3.22.4"
"@langchain/openai@^0.0.25", "@langchain/openai@~0.0.19":
version "0.0.25"
resolved "https://registry.yarnpkg.com/@langchain/openai/-/openai-0.0.25.tgz#8332abea1e3acb9b1169f90636e518c0ee90622e"
@ -712,6 +743,11 @@
resolved "https://registry.yarnpkg.com/@types/triple-beam/-/triple-beam-1.3.5.tgz#74fef9ffbaa198eb8b588be029f38b00299caa2c"
integrity sha512-6WaYesThRMCl19iryMYP7/x2OVgCtbIVflDGFpWnb9irXI3UjYE4AzmYuiUKY1AJstGijoY+MgUszMgRxIYTYw==
"@types/uuid@^10.0.0":
version "10.0.0"
resolved "https://registry.yarnpkg.com/@types/uuid/-/uuid-10.0.0.tgz#e9c07fe50da0f53dc24970cca94d619ff03f6f6d"
integrity sha512-7gqG38EyHgyP1S+7+xomFtL+ZNHcKv6DwNaCZmJmo1vgMugyF3TCnXVg4t1uk89mLNwnLtnY3TpOpCOyp1/xHQ==
"@types/uuid@^9.0.1":
version "9.0.8"
resolved "https://registry.yarnpkg.com/@types/uuid/-/uuid-9.0.8.tgz#7545ba4fc3c003d6c756f651f3bf163d8f0f29ba"
@ -1900,6 +1936,18 @@ langchainhub@~0.0.8:
resolved "https://registry.yarnpkg.com/langchainhub/-/langchainhub-0.0.8.tgz#fd4b96dc795e22e36c1a20bad31b61b0c33d3110"
integrity sha512-Woyb8YDHgqqTOZvWIbm2CaFDGfZ4NTSyXV687AG4vXEfoNo7cGQp7nhl7wL3ehenKWmNEmcxCLgOZzW8jE6lOQ==
langsmith@^0.1.56-rc.1:
version "0.1.68"
resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.1.68.tgz#848332e822fe5e6734a07f1c36b6530cc1798afb"
integrity sha512-otmiysWtVAqzMx3CJ4PrtUBhWRG5Co8Z4o7hSZENPjlit9/j3/vm3TSvbaxpDYakZxtMjhkcJTqrdYFipISEiQ==
dependencies:
"@types/uuid" "^10.0.0"
commander "^10.0.1"
p-queue "^6.6.2"
p-retry "4"
semver "^7.6.3"
uuid "^10.0.0"
langsmith@~0.1.1, langsmith@~0.1.7:
version "0.1.14"
resolved "https://registry.yarnpkg.com/langsmith/-/langsmith-0.1.14.tgz#2b889dbcfb49547614df276a4a5a063092a1585d"
@ -2568,6 +2616,11 @@ semver@^7.3.5, semver@^7.5.3, semver@^7.5.4:
dependencies:
lru-cache "^6.0.0"
semver@^7.6.3:
version "7.6.3"
resolved "https://registry.yarnpkg.com/semver/-/semver-7.6.3.tgz#980f7b5550bc175fb4dc09403085627f9eb33143"
integrity sha512-oVekP1cKtI+CTDvHWYFUcMtsK/00wmAEfyqKfNdARm8u1wNVhSgaX7A8d4UuIlUI5e84iEwOhs7ZPYRmzU9U6A==
send@0.18.0:
version "0.18.0"
resolved "https://registry.yarnpkg.com/send/-/send-0.18.0.tgz#670167cc654b05f5aa4a767f9113bb371bc706be"