Use the new GPT-4 api to build a chatGPT chatbot for multiple Large PDF files.
Tech stack used includes LangChain, Chroma, Typescript, Openai, and Next.js. LangChain is a framework that makes it easier to build scalable AI/LLM apps and chatbots. Chroma is a vectorstore for storing embeddings and your PDF in text to later retrieve similar docs.
- Install packages
First run npm install yarn -g
to install yarn globally (if you haven't already).
Then run:
yarn install
After installation, you should now see a node_modules
folder.
- Set up your
.env
file
- Copy
.env.example
into.env
Your.env
file should look like this:
NODE_ENV="development"
OPENAI_API_KEY=""
OPENAI_MODEL_NAME="text-davinci-003"
CHROMA_API="http://localhost:8000"
CHROMA_COLLECTION="test"
# for chroma in cloud
CHROMA_USERNAME=
CHROMA_PASSWORD=
- Set up
ChromaDB
git clone [email protected]:chroma-core/chroma.git
cd chroma
docker-compose up -d --build
- In
utils/makechain.ts
chain change theQA_PROMPT
for your own usecase. ChangemodelName
innew OpenAI
togpt-4
, if you have access togpt-4
api. Please verify outside this repo that you have access togpt-4
api, otherwise the application will not work.
This repo can load multiple PDF files
-
Inside
docs
folder, add your pdf files or folders that contain pdf files. -
Run the script
npm run ingest
to 'ingest' and embed your docs.
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.
General errors
- Make sure you're running the latest Node version. Run
node -v
- Try a different PDF or convert your PDF to text first. It's possible your PDF is corrupted, scanned, or requires OCR to convert to text.
Console.log
theenv
variables and make sure they are exposed.- Make sure you're using the same versions of LangChain and Chroma as this repo.
- Check that you've created an
.env
file that contains your valid (and working) API keys, environment and index name. - If you change
modelName
inOpenAI
, make sure you have access to the api for the appropriate model. - Make sure you have enough OpenAI credits and a valid card on your billings account.
- Check that you don't have multiple OPENAPI keys in your global environment. If you do, the local
env
file from the project will be overwritten by systemsenv
variable. - Try to hard code your API keys into the
process.env
variables if there are still issues.