Efficiently use Langchain for Complex Tasks

Prerequisites:

• Python
• Git
• OpenAI API Key

git clone https://github.com/Haste171/langchain-chatbot.git

Recommended to use a virtual environment

pip install -r requirements.txt

Reference example.env to create credentials file

OPENAI_API_KEY=
PINECONE_API_KEY=
PINECONE_ENVIRONMENT=
PINECONE_INDEX=

Run Terminal Interface

python chatbot.py

Run Chat Interface

streamlit run streamlit.py

• Conversational answers with chat history
• Compatibility for PDF documents (more soon)
• Local and external vector database compatibility

Soon:

• Externally hosted user accessible chat interface
• Compatibility with multiple files types (Llama Index)
• Compatibility with offline models (HuggingFace, Vicuna, Alpaca)

If you would like to contribute to the LangChain Chatbot, please follow these steps:

1. Fork the repository
2. Create a new branch for your feature or bug fix
3. Write tests for your changes
4. Implement your changes and ensure that all tests pass
5. Submit a pull request

The LangChain Chatbot was developed by Haste171 with much inspiration from Mayo with the GPT4 & LangChain Chatbot for large PDF docs. This project is mainly a port to Python from the Mayo chatbot.

The LangChain Chatbot is released under the MIT License.