https://github.com/minhbtrc/langchain-chatbot

This code is an implementation of a chatbot using LLM chat model API and Langchain.
https://github.com/minhbtrc/langchain-chatbot

chatbot gpt-4 gradio langchain langserve langsmith lcel llm mongodb openai personality-chatbot presidio runnable streaming streaming-response

Last synced: about 2 months ago
JSON representation

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

• Host: GitHub
• URL: https://github.com/minhbtrc/langchain-chatbot
• Owner: spartan-minhbui
• License: mit
• Created: 2023-10-02T09:31:33.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-12-01T02:32:33.000Z (about 1 year ago)
• Last Synced: 2024-05-20T21:27:09.047Z (7 months ago)
• Topics: chatbot, gpt-4, gradio, langchain, langserve, langsmith, lcel, llm, mongodb, openai, personality-chatbot, presidio, runnable, streaming, streaming-response
• Language: Python
• Homepage:
• Size: 663 KB
• Stars: 40
• Watchers: 6
• Forks: 8
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-langchain-zh - PersonalityChatbot - with-langchain?style=social): 采用 Langchain | LangSmith | MongoDB 的个性化聊天机器人. (开源项目 / 其他聊天机器人)

README

        
# 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](https://github.com/langchain-ai/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](/assets/demo_ui.png)

### PII for chatbot

- [Data anonymization with Microsoft Presidio](https://python.langchain.com/docs/guides/privacy/presidio_data_anonymization/)

- To protect personally identifiable information (PII), we add `PresidioAnonymizer` to my bot to replace PIIs before

  pass to LLM api. View code in [Anonymizer](//utils/anonymizer.py)

- Steps when using it:

    - User message after anonymize:

      ![anonymized message](/assets/anonymized_output.png)

    - Anonymized prompt before input to LLM:

      ![anonymized_prompt](/assets/anonymized_prompt.png)

    - De-anonymized response to user after LLM call:

  

      ![de-anonymized_output.png](/assets/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](https://docs.smith.langchain.com/)

- Configure environment to connect to LangSmith.

  ```commandline

  export LANGCHAIN_TRACING_V2=true

  export LANGCHAIN_ENDPOINT="https://api.smith.langchain.com"

  export LANGCHAIN_API_KEY=""

  export LANGCHAIN_PROJECT="chatbot-with-langchain"

  ```

### Running

0. Download the models for the languages to use in anonymizer. PII support.

    1. `python -m spacy download en_core_web_md`

1. 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`

2. RUN frontend

    1. `cd chatbot_frontend`

    2. Install packages: `npm i`

    3. Start frontend: `npm start dev`