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This code is an implementation of a chatbot using LLM chat model API and Langchain.

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minhbtrc/langchain-chatbot

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Chatbot with Langchain, LangSmith.

Requirement

  • Python version >= 3.9. Because langchainhub package require it

Description

  • This is a chatbot implementation with Langchain framework.
    • Base LLM: Vertex AI or OpenAI API
    • Memory: MongoDB
    • UI:
      • Gradio
      • Langchain UI: Chat Langchain
        • Use it to leverages LangChain's streaming support.
    • Prompt versioning and tracing: LangSmith
  • User can custom bot's personality by setting bot information like gender, age, ...
  • Demo UI: Demo UI

PII for chatbot

  • Data anonymization with Microsoft Presidio
  • To protect personally identifiable information (PII), we add PresidioAnonymizer to my bot to replace PIIs before pass to LLM api. View code in Anonymizer
  • Steps when using it:
    • User message after anonymize:

      anonymized message

    • Anonymized prompt before input to LLM:

      anonymized_prompt

    • De-anonymized response to user after LLM call:

      de-anonymized_output.png

How to use

  • You need Google Cloud credentials to call Vertex API or OPENAI API KEY to call OpenAI API
  • You need create MongoDB database and collection to use as Langchain memory

Setup tracing with Langsmith

  • Langsmith docs: LangSmith
  • Configure environment to connect to LangSmith.
    export LANGCHAIN_TRACING_V2=true
    export LANGCHAIN_ENDPOINT="https://api.smith.langchain.com"
    export LANGCHAIN_API_KEY="<your-api-key>"
    export LANGCHAIN_PROJECT="chatbot-with-langchain"
    

Running

  1. Download the models for the languages to use in anonymizer. PII support.
    1. python -m spacy download en_core_web_md
  2. RUN backend
    1. Clone repo: git clone https://github.com/btrcm00/chatbot-with-langchain.git
    2. Add google-cloud-platform credential file to secure/vertexai.json
    3. cd chatbot
    4. Install required packages: pip install -r requirements.txt
    5. Create MongoDB database and config environment variables to connect Mongo.
    6. Run: python app.py
  3. RUN frontend
    1. cd chatbot_frontend
    2. Install packages: npm i
    3. Start frontend: npm start dev