README.md

metadata

title: Judge-GPT
emoji: ⚖️
colorFrom: yellow
colorTo: red
sdk: gradio
sdk_version: 6.17.3
app_file: app.py
pinned: false
license: mit
short_description: AI-native miniature trials under 32B.

Judge-GPT

Judge-GPT is a cinematic Gradio Space for the Build Small Hackathon's Thousand Token Wood track. It runs two-minute AI-native miniature trials where small-model agents act as advocates, judge, jurors, clerk, and evidence auditor.

The app is built to stay under the 32B named-model budget:

• openai/gpt-oss-20b for primary legal reasoning.
• openbmb/AgentCPM-Explore for clerk/stage/verdict style.
• nvidia/Nemotron-Orchestrator-8B for juror and evidence-auditor review.

Total named budget: 32B parameters.

What the app can do

• Run cached trials for the Socrates and Barnaby demo cases without network search.
• Run the Live Search Tribunal path, which builds a search packet from a user query and stops if live material is too weak to support a trial.
• Add a hypothetical sidebar to shift the framing of a trial without editing cached case files.
• Switch trial pacing between swift, measured, and ceremonial speeds.
• Stage the courtroom with phase-specific visuals, agent puppets, evidence props, captions, and browser audio cues.
• Show the Mind Layer as a compact JSON trace of agent turns and phase metadata.
• Call a Modal streaming endpoint when MODAL_TRIAL_URL is configured. Endpoint or model failures stop the trial instead of substituting cached dialogue.
• Retain decree and agent-trace export helpers in sovereign_bench/export.py for future UI restoration.

Limitations

• Judge-GPT is not legal advice and should not be used for real legal decisions.
• Live search snippets are not independently verified by the app.
• Output quality depends on Modal GPU availability, token limits, and the configured Hugging Face models.
• Model, Modal, or live retrieval failures stop the current trial rather than returning substitute courtroom dialogue.
• Trial results are not persisted across sessions.
• Export generation remains in the codebase, but the visible download UI is currently hidden.

Run locally

python -m pip install -r requirements.txt
python app.py

Modal backend

The Gradio app works locally without Modal. If MODAL_TRIAL_URL is set, the Space calls the Modal streaming endpoint and stops the trial if the endpoint is unavailable.

The deployed Modal endpoint runs each role prompt through a GPU-backed vLLM class on H100 by default. Traces mark successful GPU calls with runtime: modal-gpu-vllm, provider: modal-gpu-vllm, and gpu: H100. If a GPU/model load fails, the trial stops; the app does not substitute provider or cached dialogue.

python -m modal deploy modal_app.py

Keep the deployed endpoint URL as a Hugging Face Space variable named MODAL_TRIAL_URL.

Project targets

Workspace connected to:

• GitHub: https://github.com/aliiqbal24/BuildSmallfinal.git
• Modal profile: ali-j-iqbal24
• Hugging Face user: AliIqbal05

Secrets

Credentials are not committed to this repo.

• Local Hugging Face CLI auth is stored in the Hugging Face cache.
• Modal auth is stored in the local Modal profile.
• Modal has a secret named huggingface with HF_TOKEN.

Use the Modal secret in functions like this:

@app.function(secrets=[modal.Secret.from_name("huggingface")])
def run_model():
    token = os.getenv("HF_TOKEN")

Developer guide

• app.py: Gradio UI, CSS, JavaScript audio hooks, HTML renderers, and Modal/local streaming switch.
• sovereign_bench/engine.py: trial phases, agent orchestration, verdict assembly, and trace construction.
• sovereign_bench/llm.py: Hugging Face calls, strict model error handling, and prompt building.
• sovereign_bench/retrieval.py: live search packet construction.
• sovereign_bench/models.py: Pydantic schemas for cases, evidence, events, turns, votes, and verdicts.
• sovereign_bench/cases.py: cached demo case packets.
• sovereign_bench/export.py: dormant decree and trace writers.
• modal_app.py: Modal deployment and GPU-backed streaming endpoint.
• tests/: engine, case, and rendering regression coverage.

Verify Modal to Hugging Face

python -m modal run modal_app.py