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feat(config): Use toml instead of env

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ItzCrazyKns 2024-04-20 09:32:19 +05:30
parent dd1ce4e324
commit c6a5790d33
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26 changed files with 799 additions and 596 deletions
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79
src/agents/imageSearchAgent.ts
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@ -4,16 +4,11 @@ import {
RunnableLambda,
} from '@langchain/core/runnables';
import { PromptTemplate } from '@langchain/core/prompts';
import { ChatOpenAI } from '@langchain/openai';
import formatChatHistoryAsString from '../utils/formatHistory';
import { BaseMessage } from '@langchain/core/messages';
import { StringOutputParser } from '@langchain/core/output_parsers';
import { searchSearxng } from '../core/searxng';
const llm = new ChatOpenAI({
modelName: process.env.MODEL_NAME,
temperature: 0.7,
});
import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
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.
@ -43,38 +38,48 @@ type ImageSearchChainInput = {
const strParser = new StringOutputParser();
const imageSearchChain = RunnableSequence.from([
RunnableMap.from({
chat_history: (input: ImageSearchChainInput) => {
return formatChatHistoryAsString(input.chat_history);
},
query: (input: ImageSearchChainInput) => {
return input.query;
},
}),
PromptTemplate.fromTemplate(imageSearchChainPrompt),
llm,
strParser,
RunnableLambda.from(async (input: string) => {
const res = await searchSearxng(input, {
categories: ['images'],
engines: ['bing_images', 'google_images'],
});
const createImageSearchChain = (llm: BaseChatModel) => {
return RunnableSequence.from([
RunnableMap.from({
chat_history: (input: ImageSearchChainInput) => {
return formatChatHistoryAsString(input.chat_history);
},
query: (input: ImageSearchChainInput) => {
return input.query;
},
}),
PromptTemplate.fromTemplate(imageSearchChainPrompt),
llm,
strParser,
RunnableLambda.from(async (input: string) => {
const res = await searchSearxng(input, {
categories: ['images'],
engines: ['bing_images', 'google_images'],
});
const images = [];
const images = [];
res.results.forEach((result) => {
if (result.img_src && result.url && result.title) {
images.push({
img_src: result.img_src,
url: result.url,
title: result.title,
});
}
});
res.results.forEach((result) => {
if (result.img_src && result.url && result.title) {
images.push({
img_src: result.img_src,
url: result.url,
title: result.title,
});
}
});
return images.slice(0, 10);
}),
]);
return images.slice(0, 10);
}),
]);
};
export default imageSearchChain;
const handleImageSearch = (
input: ImageSearchChainInput,
llm: BaseChatModel,
) => {
const imageSearchChain = createImageSearchChain(llm);
return imageSearchChain.invoke(input);
};
export default handleImageSearch;