wehub-resource-sync
73 lines
2.1 KiB
Markdown
73 lines
2.1 KiB
Markdown
# AI Avatar Demo powered by Zep
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A conversational AI assistant powered by [Zep](https://www.getzep.com/) knowledge graphs, custom LLM integration, and Anam AI avatar—creating natural conversations with memory and context-aware responses.
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We use:
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- [Zep](https://www.getzep.com/) for conversation memory and knowledge graph management
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- Anam AI for realistic avatar and voice interactions
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- OpenRouter with Minimax M2 (LLM)
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- FastAPI for streaming backend
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- Streamlit to wrap the logic in an interactive UI
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## Architecture
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## Set Up
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Run these commands in project root
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### Install Dependencies
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```bash
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uv sync
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```
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### Configure Environment
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Create a `.env` file in the project root, similar to `.env.example`, and add your API keys:
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[Get your Zep API keys here](https://www.getzep.com/)
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### Ingest Data
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To populate the knowledge graph with your data:
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```bash
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python scripts/ingest_to_graph.py
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```
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### Run the Application
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Start the backend server:
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```bash
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uvicorn backend:app --port 8000 --reload
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```
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In a separate terminal, start the frontend:
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```bash
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streamlit run app.py
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```
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## Usage
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1. Enter your session unique name in the sidebar
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2. Click "Initialize New Session" to create a Zep session
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3. Click "Start Conversation" to interact with the avatar
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4. The assistant uses knowledge graph context and conversation history for personalized responses
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Note: To understand Zep better, we recommend going through the Jupyter notebook (`zep_demo.ipynb`) provided in the project root.
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## 📬 Stay Updated with Our Newsletter!
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**Get a FREE Data Science eBook** 📖 with 150+ essential lessons in Data Science when you subscribe to our newsletter! Stay in the loop with the latest tutorials, insights, and exclusive resources. [Subscribe now!](https://join.dailydoseofds.com)
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[](https://join.dailydoseofds.com)
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## Contribution
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Contributions are welcome! Feel free to fork this repository and submit pull requests with your improvements.
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