GPT4 & LangChain Chatbot for large PDF docs

GPT-4 & LangChain - Create a ChatGPT Chatbot for Your PDF Docs

Use the new GPT-4 api to build a chatGPT chatbot for Large PDF docs (56 pages used in this example).

Tech stack used includes LangChain, Pinecone, Typescript, Openai, and Next.js. LangChain is a framework that makes it easier to build scalable AI/LLM apps and chatbots. Pinecone is a vectorstore for storing embeddings and your PDF in text to later retrieve similar docs.

Tutorial video

Get in touch via twitter if you have questions

The visual guide of this repo and tutorial is in the visual guide folder.

Development

1. Clone the repo

git clone [github https url]

2. Install packages

pnpm install

3. Set up your .env file

• Copy .env.example into .env Your .env file should look like this:

OPENAI_API_KEY=

PINECONE_API_KEY=
PINECONE_ENVIRONMENT=

• Visit openai to retrieve API keys and insert into your .env file.
• Visit pinecone to create and retrieve your API keys.

4. In the config folder, replace the PINECONE_INDEX_NAME and PINECONE_NAME_SPACE with your own details from your pinecone dashboard.

5. In utils/makechain.ts chain change the QA_PROMPT for your own usecase. Change modelName in new OpenAIChat to a different api model if you don't have access to gpt-4.

Convert your PDF to embeddings

1. In docs folder replace the pdf with your own pdf doc.

2. In scripts/ingest-data.ts replace filePath with docs/{yourdocname}.pdf

3. Run the script npm run ingest to 'ingest' and embed your docs

4. Check Pinecone dashboard to verify your namespace and vectors have been added.

Run the app

Once you've verified that the embeddings and content have been successfully added to your Pinecone, you can run the app npm run dev to launch the local dev environment and then type a question in the chat interface.

Credit

Frontend of this repo is inspired by langchain-chat-nextjs