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DeepBoner Examples
NO MOCKS. NO FAKE DATA. REAL SCIENCE.
These demos run the REAL sexual health research pipeline with actual API calls.
Prerequisites
You MUST have API keys configured:
# Copy the example and add your keys
cp .env.example .env
# Required (pick one):
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
# Optional (higher PubMed rate limits):
NCBI_API_KEY=your-key
Examples
1. Search Demo (No LLM Required)
Demonstrates REAL parallel search across PubMed, ClinicalTrials.gov, and Europe PMC.
uv run python examples/search_demo/run_search.py "testosterone libido"
What's REAL:
- Actual NCBI E-utilities API calls (PubMed)
- Actual ClinicalTrials.gov API calls
- Actual Europe PMC API calls (includes preprints)
- Real papers, real trials, real preprints
2. Embeddings Demo (No LLM Required)
Demonstrates REAL semantic search and deduplication.
uv run python examples/embeddings_demo/run_embeddings.py
What's REAL:
- Actual sentence-transformers model (all-MiniLM-L6-v2)
- Actual ChromaDB vector storage
- Real cosine similarity computations
- Real semantic deduplication
3. Orchestrator Demo (LLM Required)
Demonstrates the REAL search-judge-synthesize loop.
uv run python examples/orchestrator_demo/run_agent.py "testosterone libido"
uv run python examples/orchestrator_demo/run_agent.py "sildenafil erectile dysfunction" --iterations 5
What's REAL:
- Real PubMed + ClinicalTrials + Europe PMC searches
- Real LLM judge evaluating evidence quality
- Real iterative refinement based on LLM decisions
- Real research synthesis
4. Magentic Demo (OpenAI Required)
Demonstrates REAL multi-agent coordination using Microsoft Agent Framework.
# Requires OPENAI_API_KEY specifically
uv run python examples/orchestrator_demo/run_magentic.py "testosterone libido"
What's REAL:
- Real MagenticBuilder orchestration
- Real SearchAgent, JudgeAgent, HypothesisAgent, ReportAgent
- Real manager-based coordination
5. Hypothesis Demo (LLM Required)
Demonstrates REAL mechanistic hypothesis generation.
uv run python examples/hypothesis_demo/run_hypothesis.py "testosterone libido"
uv run python examples/hypothesis_demo/run_hypothesis.py "sildenafil erectile dysfunction"
What's REAL:
- Real PubMed + Web search first
- Real embedding-based deduplication
- Real LLM generating Drug -> Target -> Pathway -> Effect chains
- Real knowledge gap identification
6. Full-Stack Demo (LLM Required)
THE COMPLETE PIPELINE - All phases working together.
uv run python examples/full_stack_demo/run_full.py "testosterone libido"
uv run python examples/full_stack_demo/run_full.py "sildenafil erectile dysfunction" -i 3
What's REAL:
- Real PubMed + ClinicalTrials + Europe PMC evidence collection
- Real embedding-based semantic deduplication
- Real LLM mechanistic hypothesis generation
- Real LLM evidence quality assessment
- Real LLM structured scientific report generation
Output: Publication-quality research report with validated citations.
API Key Requirements
| Example | LLM Required | Keys |
|---|---|---|
| search_demo | No | Optional: NCBI_API_KEY |
| embeddings_demo | No | None |
| orchestrator_demo | Yes | OPENAI_API_KEY or ANTHROPIC_API_KEY |
| run_magentic | Yes | OPENAI_API_KEY (Magentic requires OpenAI) |
| hypothesis_demo | Yes | OPENAI_API_KEY or ANTHROPIC_API_KEY |
| full_stack_demo | Yes | OPENAI_API_KEY or ANTHROPIC_API_KEY |
Architecture
User Query
|
v
[REAL Search] --> PubMed + ClinicalTrials + Europe PMC APIs
|
v
[REAL Embeddings] --> Actual sentence-transformers
|
v
[REAL Hypothesis] --> Actual LLM reasoning
|
v
[REAL Judge] --> Actual LLM assessment
|
+---> Need more? --> Loop back to Search
|
+---> Sufficient --> Continue
|
v
[REAL Report] --> Actual LLM synthesis
|
v
Publication-Quality Research Report
Why No Mocks?
"Authenticity is the feature."
Mocks belong in tests/unit/, not in demos. When you run these examples, you see:
- Real papers from real databases
- Real AI reasoning about real evidence
- Real scientific hypotheses
- Real research reports
This is what DeepBoner actually does. No fake data. No canned responses.