README.md

metadata

title: Template Final Assignment
emoji: 🕵🏻‍♂️
colorFrom: indigo
colorTo: indigo
sdk: gradio
sdk_version: 5.25.2
app_file: app.py
pinned: false
hf_oauth: true
hf_oauth_expiration_minutes: 480

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Local Setup

Install dependencies and run the smoke checks with uv:

uv sync
uv run pytest
uv run python scripts/run_one.py

Copy .env.example to .env and set the LiteLLM model you want to test:

LITELLM_MODEL=anthropic/claude-3-5-sonnet-latest
ANTHROPIC_API_KEY=...

LiteLLM can also route OpenAI-compatible models through the same code path:

LITELLM_MODEL=openai/gpt-4o-mini
OPENAI_API_KEY=...

If you run a LiteLLM proxy, set LITELLM_API_BASE and LITELLM_API_KEY.

Agent V1

The agent uses a routed LangGraph flow:

ingest_task -> classify_task -> specialized solver -> verify_answer -> normalize_final_answer

Routes cover direct reasoning, computation/table questions, web search, YouTube transcripts, spreadsheets, Python files, audio files, and image files.

For audio questions, configure a LiteLLM transcription-compatible provider. By default the code uses AUDIO_TRANSCRIPTION_MODEL=whisper-1 and reads OPENAI_API_KEY, or you can set:

AUDIO_TRANSCRIPTION_MODEL=whisper-1
AUDIO_TRANSCRIPTION_API_KEY=...
AUDIO_TRANSCRIPTION_API_BASE=...

For image questions, use a vision-capable LITELLM_MODEL.