Multi-Agent System for AI-Assisted Extraction

Setup Instructions

1. Install Python dependencies:

pip install -r requirements.txt

2. Environment Configuration:

   • Copy .env.example to .env
   • Currently supported configurations:
     • Azure OpenAI (for LLM)
     • Azure Cohere (for embeddings)
   • Fill in your API keys and endpoints in the .env file

3. Frontend Setup:

cd frontend
npm install
npm run dev

Data Structure Requirements

Your data should be organized as follows:

data/
└── SERIES
    └── SEASON
        └── EPISODE
            plot.txt files named as SERIESSXXEXX_plot.txt
            where SERIES is the series identifier (e.g., GA for Grey's Anatomy)
            and XX represents the season and episode numbers
            Example: GAS01E01_plot.txt, GAS01E02_plot.txt, etc.

with Grey's Anatomy Season 1 as an example:

data/
└── GA
    └── S01
        └── E01
            GAS01E01_plot.txt
        └── E02
            GAS01E02_plot.txt

Each plot.txt file should contain the episode's plot description.

Pre-filled Data

The current codebase includes:

• A pre-filled database and vector store containing the first season of Grey's Anatomy (GA)
• You can use this as a reference for how to structure your own data
• The existing Grey's Anatomy episodes follow the naming convention: GAS01E01_plot.txt, GAS01E02_plot.txt, etc. along with other system's generated files for the analysis.

Running the Application

1. Start the backend:

python main.py

2. Start the API server:

uvicorn api.api_main:app --reload

3. The frontend should already be running from the setup steps (if not, run npm run dev in the frontend directory)

Note

Currently, the system only supports Azure OpenAI for LLM operations and Azure Cohere for embeddings. Support for other providers may be added in future updates.