chore: apply linters

llm-server/config/pinecone.ts

@@ -3,11 +3,11 @@
  */
 
 if (!process.env.PINECONE_INDEX_NAME) {
-  throw new Error('Missing Pinecone index name in .env file');
+    throw new Error('Missing Pinecone index name in .env file');
 }
 
 const PINECONE_INDEX_NAME = process.env.PINECONE_INDEX_NAME ?? '';
 
 const PINECONE_NAME_SPACE = 'bot-test'; //namespace is optional for your vectors
 
-export { PINECONE_INDEX_NAME, PINECONE_NAME_SPACE };
+export {PINECONE_INDEX_NAME, PINECONE_NAME_SPACE};

llm-server/data-sources/codebaseHandler.ts

@@ -9,25 +9,18 @@ import {GithubRepoLoader} from "langchain/document_loaders/web/github";
 export default async function codebaseHandler(req: NextApiRequest, res: NextApiResponse) {
     try {
         const {repo, namespace} = req.body;
-
         const loader = new GithubRepoLoader(repo, // @ts-ignore
             {
-                branch: "main",
-                recursive: true,
-                unknown: "warn",
-                // @ts-ignore
+                branch: "main", recursive: true, unknown: "warn", // @ts-ignore
                 // ignorePaths: ['node_modules', 'vendor', 'bower_components', '__pycache__', '.venv', 'target', 'build', 'bin', 'obj', 'tmp', 'dist', 'public', '.git', '.svn', 'CVS', 'out', 'logs', '.idea', '.vscode', '.gradle', '.classpath', '.project', '.settings', '.DS_Store', 'venv', 'env', 'migrations', 'db', 'log', 'logs', 'backup', 'cache', 'temp', 'tmp', 'docs', 'doc', 'test', 'tests', 'spec', 'specs']
             });
-
         const rawDocs = await loader.load();
 
         console.log('Loaded documents')
 
         const textSplitter = new RecursiveCharacterTextSplitter({
-            chunkSize: 1000,
-            chunkOverlap: 200,
+            chunkSize: 1000, chunkOverlap: 200,
         });
-
         const docs = await textSplitter.splitDocuments(rawDocs);
 
         console.log('Split documents')
@@ -36,17 +29,14 @@ export default async function codebaseHandler(req: NextApiRequest, res: NextApiR
         const index = pinecone.Index(PINECONE_INDEX_NAME);
 
         await PineconeStore.fromDocuments(docs, embeddings, {
-            pineconeIndex: index,
-            namespace: namespace,
-            textKey: 'text',
+            pineconeIndex: index, namespace: namespace, textKey: 'text',
         });
 
         console.log('Indexed documents. all done!')
-
         return res.status(200).json({message: 'Success'});
     } catch (e) {
         console.error(e);
         // @ts-ignore
-        res.status(500).json({error: e.message, line: e.lineNumber});
+        return res.status(500).json({error: e.message, line: e.lineNumber});
     }
 }

llm-server/data-sources/pdfHandler.ts

@@ -28,16 +28,14 @@ export default async function pdfHandler(req: NextApiRequest, res: NextApiRespon
         const index = pinecone.Index(PINECONE_INDEX_NAME);
 
         await PineconeStore.fromDocuments(docs, embeddings, {
-            pineconeIndex: index,
-            namespace: namespace,
-            textKey: 'text',
+            pineconeIndex: index, namespace: namespace, textKey: 'text',
         });
 
         console.log('All is done, folder deleted');
         return res.status(200).json({message: 'Success'});
     } catch (e) {
         console.error(e);
         // @ts-ignore
-        res.status(500).json({error: e.message, line: e.lineNumber});
+        return res.status(500).json({error: e.message, line: e.lineNumber});
     }
 }

llm-server/data-sources/websiteHandler.ts

@@ -19,8 +19,7 @@ export default async function websiteHandler(req: NextApiRequest, res: NextApiRe
         const rawDocs = await directoryLoader.load();
 
         const textSplitter = new RecursiveCharacterTextSplitter({
-            chunkSize: 1000,
-            chunkOverlap: 200,
+            chunkSize: 1000, chunkOverlap: 200,
         });
 
         const docs = await textSplitter.splitDocuments(rawDocs);
@@ -29,15 +28,13 @@ export default async function websiteHandler(req: NextApiRequest, res: NextApiRe
         const index = pinecone.Index(PINECONE_INDEX_NAME);
 
         await PineconeStore.fromDocuments(docs, embeddings, {
-            pineconeIndex: index,
-            namespace: namespace,
-            textKey: 'text',
+            pineconeIndex: index, namespace: namespace, textKey: 'text',
         });
         console.log('All is done, folder deleted');
         return res.status(200).json({message: 'Success'});
     } catch (e) {
         console.error(e);
         // @ts-ignore
-        res.status(500).json({error: e.message, line: e.lineNumber});
+        return res.status(500).json({error: e.message, line: e.lineNumber});
     }
 }

llm-server/declarations/pdf-parse.d.ts

@@ -1,5 +1,5 @@
 declare module 'pdf-parse/lib/pdf-parse.js' {
-  import pdf from 'pdf-parse';
+    import pdf from 'pdf-parse';
 
-  export default pdf;
+    export default pdf;
 }

llm-server/pages/api/chat.ts

@@ -1,55 +1,45 @@
-import type { NextApiRequest, NextApiResponse } from 'next';
-import { OpenAIEmbeddings } from 'langchain/embeddings/openai';
-import { PineconeStore } from 'langchain/vectorstores/pinecone';
-import { makeChain } from '@/utils/makechain';
-import { pinecone } from '@/utils/pinecone-client';
-import { PINECONE_INDEX_NAME, PINECONE_NAME_SPACE } from '@/config/pinecone';
+import type {NextApiRequest, NextApiResponse} from 'next';
+import {OpenAIEmbeddings} from 'langchain/embeddings/openai';
+import {PineconeStore} from 'langchain/vectorstores/pinecone';
+import {makeChain} from '@/utils/makechain';
+import {pinecone} from '@/utils/pinecone-client';
+import {PINECONE_INDEX_NAME, PINECONE_NAME_SPACE} from '@/config/pinecone';
 
-export default async function handler(
-    req: NextApiRequest,
-    res: NextApiResponse,
-) {
-  const { question, history, namespace, mode, initial_prompt } = req.body;
+export default async function handler(req: NextApiRequest, res: NextApiResponse,) {
+    const {question, history, namespace, mode, initial_prompt} = req.body;
 
-  console.log('req.body', req.body);
-  console.log({ question, history, namespace, mode, initial_prompt });
-  //only accept post requests
-  if (req.method !== 'POST') {
-    res.status(405).json({ error: 'Method not allowed' });
-    return;
-  }
+    console.log('req.body', req.body);
+    console.log({question, history, namespace, mode, initial_prompt});
+    //only accept post requests
+    if (req.method !== 'POST') {
+        return res.status(405).json({error: 'Method not allowed'});
+    }
 
-  if (!question) {
-    return res.status(400).json({ message: 'No question in the request' });
-  }
-  // OpenAI recommends replacing newlines with spaces for best results
-  const sanitizedQuestion = question.trim().replaceAll('\n', ' ');
+    if (!question) {
+        return res.status(400).json({message: 'No question in the request'});
+    }
+    // OpenAI recommends replacing newlines with spaces for best results
+    const sanitizedQuestion = question.trim().replaceAll('\n', ' ');
 
-  try {
-    const index = pinecone.Index(PINECONE_INDEX_NAME);
+    try {
+        const index = pinecone.Index(PINECONE_INDEX_NAME);
 
-    /* create vectorstore*/
-    const vectorStore = await PineconeStore.fromExistingIndex(
-        new OpenAIEmbeddings({}),
-        {
-          pineconeIndex: index,
-          textKey: 'text',
-          namespace: namespace, //namespace comes from your config folder
-        },
-    );
+        /* create vectorstore*/
+        const vectorStore = await PineconeStore.fromExistingIndex(new OpenAIEmbeddings({}), {
+            pineconeIndex: index, textKey: 'text', namespace: namespace, //namespace comes from your config folder
+        },);
 
-    //create chain
-    const chain = makeChain(vectorStore, mode, initial_prompt);
-    //Ask a question using chat history
-    const response = await chain.call({
-      question: sanitizedQuestion,
-      chat_history: history || [],
-    });
+        //create chain
+        const chain = makeChain(vectorStore, mode, initial_prompt);
+        //Ask a question using chat history
+        const response = await chain.call({
+            question: sanitizedQuestion, chat_history: history || [],
+        });
 
-    console.log('response', response);
-    res.status(200).json(response);
-  } catch (error: any) {
-    console.log('error', error);
-    res.status(500).json({ error: error.message || 'Something went wrong' });
-  }
+        console.log('response', response);
+        return res.status(200).json(response);
+    } catch (error: any) {
+        console.log('error', error);
+        return res.status(500).json({error: error.message || 'Something went wrong'});
+    }
 }

llm-server/pages/api/ingest.ts

@@ -29,10 +29,11 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
         } else {
             return res.status(400).json({message: 'Not supported type'});
         }
+
     } catch (e) {
         console.error(e);
         // Return error message and line number
         // @ts-ignore
-        res.status(500).json({error: e.message, line: e.lineNumber});
+        return res.status(500).json({error: e.message, line: e.lineNumber});
     }
 }

llm-server/types/chat.ts

@@ -1,8 +1,5 @@
-import { Document } from 'langchain/document';
+import {Document} from 'langchain/document';
 
 export type Message = {
-  type: 'apiMessage' | 'userMessage';
-  message: string;
-  isStreaming?: boolean;
-  sourceDocs?: Document[];
+    type: 'apiMessage' | 'userMessage'; message: string; isStreaming?: boolean; sourceDocs?: Document[];
 };

llm-server/utils/cn.ts

@@ -1,6 +1,6 @@
-import { ClassValue, clsx } from 'clsx';
-import { twMerge } from 'tailwind-merge';
+import {ClassValue, clsx} from 'clsx';
+import {twMerge} from 'tailwind-merge';
 
 export function cn(...inputs: ClassValue[]) {
-  return twMerge(clsx(inputs));
+    return twMerge(clsx(inputs));
 }

llm-server/utils/customPDFLoader.ts

@@ -1,61 +1,49 @@
-import { Document } from 'langchain/document';
-import { readFile } from 'fs/promises';
-import { BaseDocumentLoader } from 'langchain/document_loaders';
+import {Document} from 'langchain/document';
+import {readFile} from 'fs/promises';
+import {BaseDocumentLoader} from 'langchain/document_loaders';
 
 export abstract class BufferLoader extends BaseDocumentLoader {
-  constructor(public filePathOrBlob: string | Blob) {
-    super();
-  }
-
-  protected abstract parse(
-    raw: Buffer,
-    metadata: Document['metadata'],
-  ): Promise<Document[]>;
+    constructor(public filePathOrBlob: string | Blob) {
+        super();
+    }
 
-  public async load(): Promise<Document[]> {
-    let buffer: Buffer;
-    let metadata: Record<string, string>;
-    if (typeof this.filePathOrBlob === 'string') {
-      buffer = await readFile(this.filePathOrBlob);
-      metadata = { source: this.filePathOrBlob };
-    } else {
-      buffer = await this.filePathOrBlob
-        .arrayBuffer()
-        .then((ab) => Buffer.from(ab));
-      metadata = { source: 'blob', blobType: this.filePathOrBlob.type };
+    public async load(): Promise<Document[]> {
+        let buffer: Buffer;
+        let metadata: Record<string, string>;
+        if (typeof this.filePathOrBlob === 'string') {
+            buffer = await readFile(this.filePathOrBlob);
+            metadata = {source: this.filePathOrBlob};
+        } else {
+            buffer = await this.filePathOrBlob
+                .arrayBuffer()
+                .then((ab) => Buffer.from(ab));
+            metadata = {source: 'blob', blobType: this.filePathOrBlob.type};
+        }
+        return this.parse(buffer, metadata);
     }
-    return this.parse(buffer, metadata);
-  }
+
+    protected abstract parse(raw: Buffer, metadata: Document['metadata'],): Promise<Document[]>;
 }
 
 export class CustomPDFLoader extends BufferLoader {
-  public async parse(
-    raw: Buffer,
-    metadata: Document['metadata'],
-  ): Promise<Document[]> {
-    const { pdf } = await PDFLoaderImports();
-    const parsed = await pdf(raw);
-    return [
-      new Document({
-        pageContent: parsed.text,
-        metadata: {
-          ...metadata,
-          pdf_numpages: parsed.numpages,
-        },
-      }),
-    ];
-  }
+    public async parse(raw: Buffer, metadata: Document['metadata'],): Promise<Document[]> {
+        const {pdf} = await PDFLoaderImports();
+        const parsed = await pdf(raw);
+        return [new Document({
+            pageContent: parsed.text, metadata: {
+                ...metadata, pdf_numpages: parsed.numpages,
+            },
+        }),];
+    }
 }
 
 async function PDFLoaderImports() {
-  try {
-    // the main entrypoint has some debug code that we don't want to import
-    const { default: pdf } = await import('pdf-parse/lib/pdf-parse.js');
-    return { pdf };
-  } catch (e) {
-    console.error(e);
-    throw new Error(
-      'Failed to load pdf-parse. Please install it with eg. `npm install pdf-parse`.',
-    );
-  }
+    try {
+        // the main entrypoint has some debug code that we don't want to import
+        const {default: pdf} = await import('pdf-parse/lib/pdf-parse.js');
+        return {pdf};
+    } catch (e) {
+        console.error(e);
+        throw new Error('Failed to load pdf-parse. Please install it with eg. `npm install pdf-parse`.',);
+    }
 }

llm-server/utils/makechain.ts

@@ -13,11 +13,13 @@ export const makeChain = (vectorstore: PineconeStore, mode: string, initial_prom
 
     let enableSourceDocuments = false;
 
-    if(mode === 'pair_programmer') {
+    if (mode === 'pair_programmer') {
         enableSourceDocuments = true;
     }
     return ConversationalRetrievalQAChain.fromLLM(model, vectorstore.asRetriever(), {
-        qaTemplate: prompts.qa_prompt, questionGeneratorTemplate: prompts.condense_prompt, returnSourceDocuments: enableSourceDocuments, //The number of source documents returned is 4 by default
+        qaTemplate: prompts.qa_prompt,
+        questionGeneratorTemplate: prompts.condense_prompt,
+        returnSourceDocuments: enableSourceDocuments, //The number of source documents returned is 4 by default
     },);
 };