Spaces:
Sleeping
title: The DETERMINATOR
emoji: π
colorFrom: red
colorTo: yellow
sdk: gradio
sdk_version: 6.0.1
python_version: '3.11'
app_file: src/app.py
hf_oauth: true
hf_oauth_expiration_minutes: 480
hf_oauth_scopes:
- inference-api
pinned: true
license: mit
tags:
- mcp-in-action-track-enterprise
- mcp-hackathon
- deep-research
- biomedical-ai
- pydantic-ai
- llamaindex
- modal
- building-mcp-track-enterprise
- building-mcp-track-consumer
- mcp-in-action-track-enterprise
- mcp-in-action-track-consumer
- building-mcp-track-modal
- building-mcp-track-blaxel
- building-mcp-track-llama-index
- building-mcp-track-HUGGINGFACE
You are reading the Gradio Demo README!
- π Documentation: See our technical documentation for detailed information
- π Complete README: Check out the full README for setup, configuration, and contribution guidelines
- π Hackathon Submission: Keep reading below for more information about our MCP Hackathon submission
The DETERMINATOR
About
The DETERMINATOR is a powerful generalist deep research agent system that stops at nothing until finding precise answers to complex questions. It uses iterative search-and-judge loops to comprehensively investigate any research question from any domain.
Key Features:
- Generalist: Handles queries from any domain (medical, technical, business, scientific, etc.)
- Automatic Medical Detection: Automatically determines if medical knowledge sources (PubMed, ClinicalTrials.gov) are needed
- Multi-Source Search: Web search, PubMed, ClinicalTrials.gov, Europe PMC, RAG
- Stops at Nothing: Only stops at configured limits (budget, time, iterations), otherwise continues until finding precise answers
- Evidence Synthesis: Comprehensive reports with proper citations
Important: The DETERMINATOR is a research tool that synthesizes evidence. It cannot provide medical advice or answer medical questions directly.
For this hackathon we're proposing a simple yet powerful Deep Research Agent that iteratively looks for the answer until it finds it using general purpose websearch and special purpose retrievers for technical retrievers.
IF YOU ARE A JUDGE
This project was produced with passion by a group of volunteers please check out or documentation and readmes and please do keep reading below for our story
- π Documentation: See our technical documentation for detailed information
- π Complete README: Check out the full README for setup, configuration, and contribution guidelines
- π Hackathon Submission: Keep reading below for more information about our MCP Hackathon submission
Deep Critical In the Medial
Important information
- readme: configure, deploy , contribute and learn more here.
- docs: want to know how all this works ? read our detailed technical documentation here.
- demo: Try our demo on huggingface
- [team](### Team): Join us , or follow us !
- [video]: See our demo video
Future Developments
- [] Apply Deep Research Systems To Generate Short Form Video (up to 5 minutes)
- [] Visualize Pydantic Graphs as Loading Screens in the UI
- [] Improve Data Science with more Complex Graph Agents
- [] Create The DETERMINATOR Deep Research Demo
- [] Create Deep Critical Literal Review
- [] Create Deep Critical Hypothesis Generator
- [] Create PyPi Package
Completed
- Multi-Source Search: PubMed, ClinicalTrials.gov, bioRxiv/medRxiv
- MCP Integration: Use our tools from Claude Desktop or any MCP client
- HuggingFace OAuth: Sign in with HuggingFace
- Modal Sandbox: Secure execution of AI-generated statistical code
- LlamaIndex RAG: Semantic search and evidence synthesis
- HuggingfaceInference:
- HuggingfaceMCP Custom Config To Use Community Tools:
- Strongly Typed Composable Graphs:
- Specialized Research Teams of Agents:
Team
- ZJ
- πΌ LinkedIn
- Mario Aderman
- π€ HuggingFace
- πΌ LinkedIn
- π X
- **Joseph Pollack
- π€ HuggingFace
- πΌ LinkedIn
- π X
Acknowledgements
- DeepBoner
- Magentic Paper
- Huggingface
- Gradio
- DeepCritical
- Modal
- Microsoft
- Pydantic
- Llama-index
- Anthhropic/MCP
- All our Tool Providers