remi/Perplexica
1
0
Fork 0
mirror of https://github.com/ItzCrazyKns/Perplexica.git synced 2025-07-21 16:08:29 +00:00
Code Issues Packages Projects Releases Wiki Activity

feat(imageSearch): use XML parsing, implement few shot prompting

Browse Source
This commit is contained in:
ItzCrazyKns
2025-07-19 17:52:30 +05:30
parent cddc793915
commit b48b0eeb0e
1 changed files with 41 additions and 19 deletions
Download Patch File Download Diff File Expand all files Collapse all files

60
src/lib/chains/imageSearchAgent.ts
View File

@ -3,32 +3,18 @@ import {
RunnableMap,
RunnableLambda,
} from '@langchain/core/runnables';
import { PromptTemplate } from '@langchain/core/prompts';
import { ChatPromptTemplate, PromptTemplate } from '@langchain/core/prompts';
import formatChatHistoryAsString from '../utils/formatHistory';
import { BaseMessage } from '@langchain/core/messages';
import { StringOutputParser } from '@langchain/core/output_parsers';
import { searchSearxng } from '../searxng';
import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
import LineOutputParser from '../outputParsers/lineOutputParser';
const imageSearchChainPrompt = `
You will be given a conversation below and a follow up question. You need to rephrase the follow-up question so it is a standalone question that can be used by the LLM to search the web for images.
You need to make sure the rephrased question agrees with the conversation and is relevant to the conversation.
Example:
1. Follow up question: What is a cat?
Rephrased: A cat
2. Follow up question: What is a car? How does it works?
Rephrased: Car working
3. Follow up question: How does an AC work?
Rephrased: AC working
Conversation:
{chat_history}
Follow up question: {query}
Rephrased question:
Output only the rephrased query wrapped in an XML <query> element. Do not include any explanation or additional text.
`;
type ImageSearchChainInput = {
@ -54,12 +40,48 @@ const createImageSearchChain = (llm: BaseChatModel) => {
return input.query;
},
}),
PromptTemplate.fromTemplate(imageSearchChainPrompt),
ChatPromptTemplate.fromMessages([
['system', imageSearchChainPrompt],
[
"user",
"<conversation>\n</conversation>\n<follow_up>\nWhat is a cat?\n</follow_up>"
],
[
"assistant",
"<query>A cat</query>"
],
[
"user",
"<conversation>\n</conversation>\n<follow_up>\nWhat is a car? How does it work?\n</follow_up>"
],
[
"assistant",
"<query>Car working</query>"
],
[
"user",
"<conversation>\n</conversation>\n<follow_up>\nHow does an AC work?\n</follow_up>"
],
[
"assistant",
"<query>AC working</query>"
],
[
'user',
'<conversation>{chat_history}</conversation>\n<follow_up>\n{query}\n</follow_up>'
]
]),
llm,
strParser,
RunnableLambda.from(async (input: string) => {
input = input.replace(/<think>.*?<\/think>/g, '');
const queryParser = new LineOutputParser({
key: 'query'
})
return (await queryParser.parse(input))
}),
RunnableLambda.from(async (input: string) => {
const res = await searchSearxng(input, {
engines: ['bing images', 'google images'],
});