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The backend code for YAC

To run this code I use vllm to run the main finetuned model:

vllm serve HIDIVE/UDI-VIS-Beta-v2-Llama-3.1-8B --port 8080 --host 127.0.0.1

To run the entrypoint into the multi-agent system I run a simple python api.

fastapi run ./src/udi_api.py

This is the endpoint that is called by the YAC frontend. The udi_api.py script makes calls to openai and the finetuned model running with vllm.

set environment variables

Set Environment Variables

Item Command / Value Description
OPEN_API_KEY OPEN_API_KEY=your-key-goes-here Required. The multi-agent system currently maeks calls to open ai.
JWT_SECRET_KEY JWT_SECRET_KEY=your-key-goes-here Required. Secret key for JWT generation.
UDI_MODEL_NAME UDI_MODEL_NAME=HIDIVE/UDI-VIS-Beta-v2-Llama-3.1-8B Required. Path to local or public model name, depending on how the model is served via vllm. Note, this is the model name for the fine-tuned visualization generation model, not a foundation model.

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UDIAgent: Inference for generating visualizations from natural language prompts

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