7AM7 / movie-recommender-chatbot

Movie recommender chatbot using LangChain, OpenAI and Semantic Router

Movie Recommender Chatbot

Movie recommender chatbot using FastAPI, Streamlit, LangChain and semantic-router with FAISS RAG.

How to Run it 🛫

Navigate to the project directory 1.

cd movie-recommender-chatbot

2. Create .env file and add these keys

OPENAI_API_KEY={OPENAI_API_KEY}
RETRIEVER_EMBEDDING_MODEL=text-embedding-3-small
OPENAI_TIMEOUT=30
OPENAI_TEMPERATURE=0.3
OPENAI_MODEL_NAME=gpt-4o
RETRIEVER_EMBEDDING_THRESHOLD=0.4

Run - with Docker 🐳

docker-compose up --build

Run - locally 💻

Backend

1. Make sure you have Poetry innstalled in your enviornment

pip install poetry

2. Navigate to the backed directory

cd components/backend

3. Install dependencies

poetry shell
poetry install

4. Run the app

 cd src/
 uvicorn app:app --host 0.0.0.0 --port 8080

Frontend

1. Navigate to the backed directory

cd components/frontend

2. Install dependencies

poetry shell
poetry install

3. Run the frontend (optional)

Make sure you are in the right dir frontend

streamlit run src/app.py --server.port 8081 --server.address 0.0.0.0

APIs

• URL: /chat
• Method: POST
• Description: stream the chatbot response to the user
• Request Body:

{
    "message": "hello",
    "clear_history": false
}

• Success Response:

• Response Type: text/event-stream

• Code: 200 OK

• Content:

    data: {"streamed_text": "Hello! I'm here to help you find the perfect movie to watch. ", "is_final": false}
  
    data: {"streamed_text": "Could you tell me a bit about what you're in the mood for? ", "is_final": false}
  
    data: {"streamed_text": "Are there any specific themes, settings, or favorite movies you'd like me to consider for my recommendations?", "is_final": true}