remi/Perplexica
1
0
Fork 0
mirror of https://github.com/ItzCrazyKns/Perplexica.git synced 2025-09-22 01:01:33 +00:00
Code Issues Packages Projects Releases Wiki Activity

feat(app): lint

Browse Source
This commit is contained in:
ItzCrazyKns
2024-07-31 20:17:57 +05:30
parent 96f67c7028
commit c4932c659a
3 changed files with 41 additions and 30 deletions
Download Patch File Download Diff File Expand all files Collapse all files

47
src/agents/webSearchAgent.ts
View File

@@ -157,35 +157,43 @@ const createBasicWebSearchRetrieverChain = (llm: BaseChatModel) => {
question = 'Summarize';
}
let docs = []
let docs = [];
const linkDocs = await getDocumentsFromLinks({ links });
const docGroups: Document[] = [];
linkDocs.map((doc) => {
const URLDocExists = docGroups.find((d) => d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10);
const URLDocExists = docGroups.find(
(d) =>
d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
);
if (!URLDocExists) {
docGroups.push({
...doc,
metadata: {
...doc.metadata,
totalDocs: 1
}
totalDocs: 1,
},
});
}
const docIndex = docGroups.findIndex((d) => d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10);
const docIndex = docGroups.findIndex(
(d) =>
d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
);
if (docIndex !== -1) {
docGroups[docIndex].pageContent = docGroups[docIndex].pageContent + `\n\n` + doc.pageContent;
docGroups[docIndex].pageContent =
docGroups[docIndex].pageContent + `\n\n` + doc.pageContent;
docGroups[docIndex].metadata.totalDocs += 1;
}
})
});
await Promise.all(docGroups.map(async (doc) => {
const res = await llm.invoke(`
await Promise.all(
docGroups.map(async (doc) => {
const res = await llm.invoke(`
You are a text summarizer. You need to summarize the text provided inside the \`text\` XML block.
You need to summarize the text into 1 or 2 sentences capturing the main idea of the text.
You need to make sure that you don't miss any point while summarizing the text.
@@ -204,16 +212,17 @@ const createBasicWebSearchRetrieverChain = (llm: BaseChatModel) => {
Make sure to answer the query in the summary.
`);
const document = new Document({
pageContent: res.content as string,
metadata: {
title: doc.metadata.title,
url: doc.metadata.url,
},
})
docs.push(document)
}))
const document = new Document({
pageContent: res.content as string,
metadata: {
title: doc.metadata.title,
url: doc.metadata.url,
},
});
docs.push(document);
}),
);
return { query: question, docs: docs };
} else {