Initial commit: ECH0-PRIME Autonomous Research Agent API

README.md

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+---
+title: ECH0-PRIME × QuLab Infinite
+emoji: 🤖
+colorFrom: green
+colorTo: blue
+sdk: gradio
+sdk_version: 4.0.0
+app_file: app.py
+pinned: false
+---
+
+# 🤖 ECH0-PRIME × QuLab Infinite
+## Autonomous Scientific Research Agent API
+
+**ECH0-PRIME** (Kimi-K2 1046B) connected to **QuLab Infinite** with 1,532+ scientific tools across 220+ laboratories.
+
+## 🧠 What is ECH0-PRIME?
+
+ECH0-PRIME is a Level-10 Scientific Research Intelligence powered by Moonshot AI's Kimi-K2 1046B parameter model, seamlessly integrated with QuLab Infinite's comprehensive scientific simulation platform.
+
+### Core Capabilities
+
+- **Design Experiments**: Create precise experimental parameters for any lab
+- **Analyze Results**: Interpret simulation outputs quantitatively
+- **Iterate**: Refine hypotheses based on data
+- **Cross-Domain Synthesis**: Combine insights from multiple labs
+- **Generate Inventions**: Create novel therapeutic/material designs
+
+## 🔬 Available Laboratories
+
+### QUANTUM LABS
+- quantum_lab: Quantum computing, teleportation protocols, error correction
+- quantum_mechanics_lab: Fundamental quantum simulations
+- quantum_computing_lab: Gate operations, circuit design
+
+### BIOLOGICAL LABS
+- oncology_lab: Cancer simulations, tumor evolution, treatment optimization
+- genetic_variant_analyzer: Genomic analysis, variant impact prediction
+- cancer_metabolic_optimizer: Metabolic pathway analysis for cancer treatment
+- immune_response_simulator: Immunotherapy modeling
+- microbiome_optimizer: Gut microbiome analysis and optimization
+- neurotransmitter_optimizer: Brain chemistry modeling
+- stem_cell_predictor: Differentiation pathway prediction
+- protein_folding_lab: Protein structure prediction
+
+### CHEMISTRY LABS
+- chemistry_lab: Molecular simulations, reaction kinetics
+- drug_interaction_network: Drug-drug interactions, pharmacology
+- materials_lab: Materials science simulations
+- organic_chemistry_lab: Organic synthesis planning
+- electrochemistry_lab: Electrochemical reactions
+
+### PHYSICS LABS
+- physics_engine: Classical and quantum physics simulations
+- particle_physics_lab: Particle interactions
+- plasma_physics_lab: Plasma dynamics
+- condensed_matter_physics_lab: Solid state physics
+
+### ENVIRONMENTAL LABS
+- environmental_sim: Climate and environmental modeling
+- atmospheric_chemistry_lab: Atmospheric reactions
+- renewable_energy_lab: Energy system optimization
+
+### MEDICAL LABS
+- cardiovascular_plaque_lab: Atherosclerosis modeling
+- metabolic_syndrome_reversal: Metabolic health optimization
+- drug_design_lab: Molecular drug design
+- clinical_trials_simulation: Trial outcome prediction
+
+## 🛠️ API Endpoints
+
+All capabilities exposed via Gradio API for external LLMs:
+
+- `/query` - Ask ECH0-PRIME scientific questions
+- `/run_experiment` - Execute experiments on QuLab
+- `/list_labs` - Browse available labs
+- `/research` - Start autonomous research session
+- `/history` - View conversation history
+- `/experiments` - View experiment log
+- `/reset` - Reset session (with auto-backup)
+
+## 🚀 Usage Examples
+
+### For External LLMs
+
+```python
+from gradio_client import Client
+
+# Connect to ECH0-PRIME
+client = Client("CorpOfLight/ech0-prime")
+
+# Query ECH0-PRIME
+response = client.predict(
+    "Design an experiment to test quantum teleportation at 100km",
+    True,  # include_context
+    api_name="/query"
+)
+
+# Run an experiment
+result = client.predict(
+    "quantum_lab",
+    "teleportation_fidelity",
+    '{"protocol": "GHZ", "num_qubits": 5, "distance_km": 100}',
+    api_name="/run_experiment"
+)
+
+# Start autonomous research
+research = client.predict(
+    "What drug combinations treat NSCLC?",
+    5,  # max_iterations
+    api_name="/research"
+)
+```
+
+### REST API
+
+```bash
+# Query ECH0-PRIME
+curl -X POST https://corpoflight-ech0-prime.hf.space/api/query \
+  -H "Content-Type: application/json" \
+  -d '{"data": ["Design quantum teleportation experiment", true]}'
+
+# Run experiment
+curl -X POST https://corpoflight-ech0-prime.hf.space/api/run_experiment \
+  -H "Content-Type: application/json" \
+  -d '{"data": ["quantum_lab", "teleportation_fidelity", "{\"num_qubits\": 5}"]}'
+```
+
+## 🔄 Autonomous Research Loop
+
+ECH0-PRIME can run fully autonomous research sessions:
+
+1. **Design Experiments**: Based on your research question
+2. **Run Simulations**: Execute on QuLab Infinite
+3. **Analyze Results**: Interpret data quantitatively
+4. **Iterate**: Refine hypotheses and run follow-ups
+5. **Synthesize**: Combine findings into actionable conclusions
+
+### Example Research Session
+
+```python
+client = Client("CorpOfLight/ech0-prime")
+
+result = client.predict(
+    "What is the optimal drug combination for treating EGFR-mutant NSCLC with minimal side effects?",
+    5,  # max_iterations
+    api_name="/research"
+)
+```
+
+ECH0-PRIME will:
+- Query oncology and pharmacology labs
+- Test multiple drug combinations
+- Analyze efficacy and toxicity
+- Provide ranked recommendations with data
+
+## 💡 Key Features
+
+### Stateful Sessions
+- Maintains conversation context across queries
+- Logs all experiments automatically
+- Auto-backup before session reset
+
+### Cross-Domain Intelligence
+- Quantum chemistry + drug design
+- Materials science + renewable energy
+- Genomics + personalized medicine
+- Physics simulations + engineering optimization
+
+### Experiment JSON Format
+
+```json
+{
+    "lab": "oncology_lab",
+    "experiment_type": "tumor_evolution",
+    "parameters": {
+        "tumor_type": "NSCLC",
+        "initial_size_mm": 15,
+        "mutation_rate": 0.001,
+        "immune_pressure": 0.3,
+        "treatment": "pembrolizumab",
+        "simulation_days": 90
+    },
+    "hypothesis": "Tumor size reduction >50% by day 60",
+    "success_criteria": "Final tumor size <7.5mm"
+}
+```
+
+## ⚙️ Configuration
+
+Set your Together AI API key as a HuggingFace Space secret:
+- Secret name: `TOGETHER_AI_API_KEY`
+- Get your key at: https://api.together.xyz
+
+## 📄 License
+
+Copyright (c) 2025 Joshua Hendricks Cole (DBA: Corporation of Light). All Rights Reserved. PATENT PENDING.
+
+## 🌐 Links
+
+- **QuLab GUI**: https://huggingface.co/spaces/CorpOfLight/qulab-gui
+- **Documentation**: https://qulab.aios.is
+- **Research Blog**: https://echo.aios.is
+- **GitHub**: https://github.com/Workofarttattoo/QuLabInfinite
+
+---
+
+**Built with ❤️ for autonomous scientific discovery**

app.py

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+#!/usr/bin/env python3
+"""
+ECH0-PRIME Gradio API Interface
+Enables external LLMs to navigate and use QuLab tools through ECH0-PRIME
+
+Copyright (c) 2025 Joshua Hendricks Cole (DBA: Corporation of Light). All Rights Reserved. PATENT PENDING.
+"""
+
+import gradio as gr
+import json
+from typing import Dict, List, Any, Optional
+import traceback
+from datetime import datetime
+
+# Initialize ECH0-PRIME
+ech0_prime = None
+ech0_error = None
+
+try:
+    from ech0_prime_qulab_connector import Ech0PrimeQuLabResearcher
+    ech0_prime = Ech0PrimeQuLabResearcher()
+    print("✅ ECH0-PRIME initialized successfully for Gradio API")
+except Exception as e:
+    ech0_error = str(e)
+    print(f"❌ ECH0-PRIME initialization failed: {e}")
+
+
+def list_available_labs() -> str:
+    """List all available labs in QuLab Infinite"""
+    if not ech0_prime:
+        return "❌ ECH0-PRIME not available"
+
+    try:
+        labs = ech0_prime.qulab.list_labs()
+
+        if not labs:
+            return """⚠️ **QuLab API may not be running**
+
+Available Labs (from system prompt):
+### QUANTUM LABS
+- quantum_lab: Quantum computing, teleportation protocols, error correction
+- quantum_mechanics_lab: Fundamental quantum simulations
+- quantum_computing_lab: Gate operations, circuit design
+
+### BIOLOGICAL LABS
+- oncology_lab: Cancer simulations, tumor evolution, treatment optimization
+- genetic_variant_analyzer: Genomic analysis, variant impact prediction
+- cancer_metabolic_optimizer: Metabolic pathway analysis for cancer treatment
+- immune_response_simulator: Immunotherapy modeling
+- microbiome_optimizer: Gut microbiome analysis and optimization
+- neurotransmitter_optimizer: Brain chemistry modeling
+- stem_cell_predictor: Differentiation pathway prediction
+- protein_folding_lab: Protein structure prediction
+
+### CHEMISTRY LABS
+- chemistry_lab: Molecular simulations, reaction kinetics
+- drug_interaction_network: Drug-drug interactions, pharmacology
+- materials_lab: Materials science simulations
+- organic_chemistry_lab: Organic synthesis planning
+- electrochemistry_lab: Electrochemical reactions
+
+### PHYSICS LABS
+- physics_engine: Classical and quantum physics simulations
+- particle_physics_lab: Particle interactions
+- plasma_physics_lab: Plasma dynamics
+- condensed_matter_physics_lab: Solid state physics
+
+### ENVIRONMENTAL LABS
+- environmental_sim: Climate and environmental modeling
+- atmospheric_chemistry_lab: Atmospheric reactions
+- renewable_energy_lab: Energy system optimization
+
+### MEDICAL LABS
+- cardiovascular_plaque_lab: Atherosclerosis modeling
+- metabolic_syndrome_reversal: Metabolic health optimization
+- drug_design_lab: Molecular drug design
+- clinical_trials_simulation: Trial outcome prediction"""
+
+        result = "🔬 **Available QuLab Infinite Labs**\n\n"
+        for lab in labs:
+            result += f"• {lab}\n"
+
+        return result
+
+    except Exception as e:
+        return f"❌ Failed to list labs: {str(e)}"
+
+
+def query_ech0_prime(question: str, include_context: bool = True) -> str:
+    """Query ECH0-PRIME with a scientific question"""
+    if not ech0_prime:
+        return "❌ ECH0-PRIME not available"
+
+    if not question.strip():
+        return "Please enter a question"
+
+    try:
+        response = ech0_prime.query_llm(question)
+
+        result = f"🤖 **ECH0-PRIME Response**\n\n{response}\n\n"
+
+        if include_context:
+            result += f"---\n**Conversation Length**: {len(ech0_prime.conversation_history)} messages\n"
+            result += f"**Experiments Run**: {len(ech0_prime.experiment_log)}\n"
+
+        return result
+
+    except Exception as e:
+        return f"❌ Query failed: {str(e)}\n\nTraceback:\n{traceback.format_exc()}"
+
+
+def run_single_experiment(lab: str, experiment_type: str, parameters: str) -> str:
+    """Run a single experiment on QuLab Infinite"""
+    if not ech0_prime:
+        return "❌ ECH0-PRIME not available"
+
+    try:
+        # Parse parameters
+        if parameters.strip():
+            try:
+                params = json.loads(parameters)
+            except json.JSONDecodeError:
+                return "❌ Invalid JSON parameters. Please check your input format."
+        else:
+            params = {}
+
+        # Create experiment dict
+        experiment = {
+            "lab": lab,
+            "experiment_type": experiment_type,
+            "parameters": params
+        }
+
+        # Run experiment
+        results = ech0_prime.run_experiment(experiment)
+
+        # Format result
+        result_text = f"🧪 **Experiment Result**\n\n"
+        result_text += f"**Lab**: {lab}\n"
+        result_text += f"**Type**: {experiment_type}\n\n"
+
+        if "error" in results:
+            result_text += f"❌ **Error**: {results['error']}\n\n"
+            if "detail" in results:
+                result_text += f"**Details**: {results['detail']}"
+        else:
+            result_text += f"✅ **Success!**\n\n```json\n{json.dumps(results, indent=2)}\n```"
+
+        # Log to ECH0-PRIME
+        ech0_prime.experiment_log.append({
+            "experiment": experiment,
+            "results": results,
+            "timestamp": datetime.now().isoformat()
+        })
+
+        return result_text
+
+    except Exception as e:
+        return f"❌ Experiment failed: {str(e)}\n\nTraceback:\n{traceback.format_exc()}"
+
+
+def start_research_session(research_question: str, max_iterations: int = 5) -> str:
+    """Start an autonomous research session"""
+    if not ech0_prime:
+        return "❌ ECH0-PRIME not available"
+
+    if not research_question.strip():
+        return "Please enter a research question"
+
+    try:
+        # Run research loop
+        results = ech0_prime.research_loop(
+            research_question,
+            max_iterations=max_iterations,
+            verbose=False
+        )
+
+        # Format results
+        output = f"🔬 **Research Session Complete**\n\n"
+        output += f"**Question**: {research_question}\n"
+        output += f"**Iterations**: {results['iterations']}\n\n"
+
+        output += "### Experiments Run:\n"
+        for i, exp in enumerate(results['experiments'], 1):
+            exp_data = exp['experiment']
+            output += f"\n**{i}. {exp_data.get('lab')}** - {exp_data.get('experiment_type')}\n"
+
+            # Show result status
+            if 'error' in exp['results']:
+                output += f"   ❌ Error: {exp['results']['error']}\n"
+            else:
+                output += f"   ✅ Success\n"
+
+        output += f"\n### Final Summary:\n\n{results['final_summary']}\n\n"
+
+        # Save session
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        filepath = f"/Users/noone/QuLabInfinite/ech0_research_gradio_{timestamp}.json"
+        ech0_prime.save_session(filepath)
+        output += f"---\n**Session saved to**: `{filepath}`"
+
+        return output
+
+    except Exception as e:
+        return f"❌ Research session failed: {str(e)}\n\nTraceback:\n{traceback.format_exc()}"
+
+
+def get_conversation_history() -> str:
+    """Get the current conversation history"""
+    if not ech0_prime:
+        return "❌ ECH0-PRIME not available"
+
+    try:
+        if not ech0_prime.conversation_history:
+            return "No conversation history yet. Start by asking a question!"
+
+        output = f"💬 **Conversation History** ({len(ech0_prime.conversation_history)} messages)\n\n"
+
+        for i, msg in enumerate(ech0_prime.conversation_history[-10:], 1):  # Last 10 messages
+            role = msg['role'].upper()
+            content = msg['content'][:200] + "..." if len(msg['content']) > 200 else msg['content']
+            output += f"**{role}**: {content}\n\n"
+
+        if len(ech0_prime.conversation_history) > 10:
+            output += f"_(Showing last 10 of {len(ech0_prime.conversation_history)} messages)_"
+
+        return output
+
+    except Exception as e:
+        return f"❌ Failed to get history: {str(e)}"
+
+
+def get_experiment_log() -> str:
+    """Get the experiment log"""
+    if not ech0_prime:
+        return "❌ ECH0-PRIME not available"
+
+    try:
+        if not ech0_prime.experiment_log:
+            return "No experiments run yet."
+
+        output = f"📊 **Experiment Log** ({len(ech0_prime.experiment_log)} experiments)\n\n"
+
+        for i, exp in enumerate(ech0_prime.experiment_log, 1):
+            exp_data = exp['experiment']
+            output += f"**{i}. {exp_data.get('lab')}** - {exp_data.get('experiment_type')}\n"
+            output += f"   Timestamp: {exp.get('timestamp', 'N/A')}\n"
+
+            if 'error' in exp['results']:
+                output += f"   ❌ Error: {exp['results']['error']}\n"
+            else:
+                output += f"   ✅ Success\n"
+            output += "\n"
+
+        return output
+
+    except Exception as e:
+        return f"❌ Failed to get log: {str(e)}"
+
+
+def reset_session() -> str:
+    """Reset the ECH0-PRIME session"""
+    if not ech0_prime:
+        return "❌ ECH0-PRIME not available"
+
+    try:
+        # Save current session before reset
+        if ech0_prime.experiment_log or ech0_prime.conversation_history:
+            timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+            filepath = f"/Users/noone/QuLabInfinite/ech0_session_backup_{timestamp}.json"
+            ech0_prime.save_session(filepath)
+            backup_msg = f"\n✅ Previous session backed up to: `{filepath}`"
+        else:
+            backup_msg = ""
+
+        # Reset
+        ech0_prime.conversation_history = []
+        ech0_prime.experiment_log = []
+
+        return f"🔄 **Session Reset**\n\nConversation history and experiment log cleared.{backup_msg}"
+
+    except Exception as e:
+        return f"❌ Reset failed: {str(e)}"
+
+
+# Create the Gradio interface
+def create_interface():
+    """Create the ECH0-PRIME Gradio API interface"""
+
+    with gr.Blocks(title="ECH0-PRIME × QuLab Infinite API",
+                   theme=gr.themes.Soft()) as interface:
+
+        gr.Markdown("""
+        # 🤖 ECH0-PRIME × QuLab Infinite
+        ## Autonomous Scientific Research Agent API
+
+        **ECH0-PRIME** (Kimi-K2 1046B) connected to **QuLab Infinite** with 1,532+ scientific tools across 220+ laboratories.
+
+        This API enables external LLMs to:
+        - Query ECH0-PRIME for scientific insights
+        - Run experiments on QuLab Infinite
+        - Navigate available labs and tools
+        - Start autonomous research sessions
+        """)
+
+        if ech0_error:
+            gr.Markdown(f"⚠️ **Warning**: ECH0-PRIME initialization failed: {ech0_error}")
+
+        with gr.Tabs():
+
+            # Overview Tab
+            with gr.TabItem("🏠 Overview"):
+                with gr.Row():
+                    with gr.Column():
+                        gr.Markdown("""
+                        ## 📊 System Capabilities
+                        - **LLM**: Kimi-K2 1046B (Moonshot AI)
+                        - **Labs**: 220+ specialized laboratories
+                        - **Tools**: 1,532+ scientific tools
+                        - **Domains**: Quantum, Biology, Chemistry, Physics, Medical, Environmental
+
+                        ## 🔗 API Endpoints
+                        - `/query` - Ask scientific questions
+                        - `/run_experiment` - Execute experiments
+                        - `/list_labs` - Browse available labs
+                        - `/research` - Start research session
+                        - `/history` - View conversation history
+                        - `/experiments` - View experiment log
+                        """)
+
+                    with gr.Column():
+                        status_indicator = "🟢 **Fully Operational**" if ech0_prime else "🟡 **Limited Functionality**"
+                        gr.Markdown(f"### System Status\n{status_indicator}")
+
+                        # Lab list button
+                        list_labs_btn = gr.Button("🔬 List Available Labs", variant="secondary")
+                        labs_display = gr.Textbox(
+                            label="Available Labs",
+                            lines=15,
+                            interactive=False
+                        )
+
+                        list_labs_btn.click(
+                            fn=list_available_labs,
+                            inputs=[],
+                            outputs=labs_display,
+                            api_name="list_labs"
+                        )
+
+            # Query Tab
+            with gr.TabItem("💬 Query ECH0-PRIME"):
+                with gr.Row():
+                    with gr.Column():
+                        query_input = gr.Textbox(
+                            label="🔍 Scientific Question",
+                            placeholder="e.g., 'Design an experiment to test quantum teleportation fidelity at 100km'",
+                            lines=3
+                        )
+                        include_context = gr.Checkbox(
+                            label="Include conversation context",
+                            value=True
+                        )
+                        query_btn = gr.Button("🤖 Ask ECH0-PRIME", variant="primary", size="lg")
+
+                    with gr.Column():
+                        query_output = gr.Textbox(
+                            label="📝 Response",
+                            lines=20,
+                            interactive=False
+                        )
+
+                query_btn.click(
+                    fn=query_ech0_prime,
+                    inputs=[query_input, include_context],
+                    outputs=query_output,
+                    api_name="query"
+                )
+
+                gr.Markdown("""
+                ### 💡 Usage Tips
+                - Ask specific scientific questions
+                - Request experiment designs
+                - Get analysis of hypothetical scenarios
+                - ECH0-PRIME has full context of all previous queries in the session
+                """)
+
+            # Experiment Execution Tab
+            with gr.TabItem("🧪 Run Experiments"):
+                with gr.Row():
+                    with gr.Column():
+                        lab_name = gr.Textbox(
+                            label="🔬 Lab Name",
+                            placeholder="e.g., quantum_lab, oncology_lab",
+                            lines=1
+                        )
+                        exp_type = gr.Textbox(
+                            label="🧬 Experiment Type",
+                            placeholder="e.g., teleportation_fidelity, tumor_evolution",
+                            lines=1
+                        )
+                        exp_params = gr.Textbox(
+                            label="⚙️ Parameters (JSON)",
+                            placeholder='{"temperature": 25, "concentration": 0.1}',
+                            lines=5
+                        )
+                        run_exp_btn = gr.Button("🚀 Run Experiment", variant="primary", size="lg")
+
+                    with gr.Column():
+                        exp_output = gr.Textbox(
+                            label="📊 Experiment Results",
+                            lines=20,
+                            interactive=False
+                        )
+
+                run_exp_btn.click(
+                    fn=run_single_experiment,
+                    inputs=[lab_name, exp_type, exp_params],
+                    outputs=exp_output,
+                    api_name="run_experiment"
+                )
+
+                gr.Markdown("""
+                ### 📚 Example Experiments
+
+                **Quantum Lab**:
+                ```json
+                Lab: quantum_lab
+                Type: teleportation_fidelity
+                Parameters: {"protocol": "GHZ", "num_qubits": 5, "distance_km": 100, "error_rate": 0.001}
+                ```
+
+                **Oncology Lab**:
+                ```json
+                Lab: oncology_lab
+                Type: tumor_evolution
+                Parameters: {"tumor_type": "NSCLC", "initial_size_mm": 15, "treatment": "pembrolizumab"}
+                ```
+                """)
+
+            # Research Session Tab
+            with gr.TabItem("🔬 Research Sessions"):
+                with gr.Row():
+                    with gr.Column():
+                        research_q = gr.Textbox(
+                            label="🎯 Research Question",
+                            placeholder="e.g., 'What drug combinations are most effective for treating NSCLC with EGFR mutations?'",
+                            lines=3
+                        )
+                        max_iter = gr.Slider(
+                            minimum=1,
+                            maximum=10,
+                            value=5,
+                            step=1,
+                            label="Max Iterations"
+                        )
+                        research_btn = gr.Button("🔬 Start Research Session", variant="primary", size="lg")
+
+                    with gr.Column():
+                        research_output = gr.Textbox(
+                            label="📊 Research Results",
+                            lines=25,
+                            interactive=False
+                        )
+
+                research_btn.click(
+                    fn=start_research_session,
+                    inputs=[research_q, max_iter],
+                    outputs=research_output,
+                    api_name="research"
+                )
+
+                gr.Markdown("""
+                ### 🔄 Autonomous Research Loop
+
+                ECH0-PRIME will:
+                1. Design experiments based on your question
+                2. Run them on QuLab Infinite
+                3. Analyze results
+                4. Iterate and refine
+                5. Provide final conclusions
+
+                This can take several minutes depending on complexity.
+                """)
+
+            # Session Management Tab
+            with gr.TabItem("📋 Session Management"):
+                with gr.Row():
+                    with gr.Column():
+                        gr.Markdown("### 💬 Conversation History")
+                        history_btn = gr.Button("📜 View History", variant="secondary")
+                        history_output = gr.Textbox(
+                            label="Conversation History",
+                            lines=15,
+                            interactive=False
+                        )
+
+                        history_btn.click(
+                            fn=get_conversation_history,
+                            inputs=[],
+                            outputs=history_output,
+                            api_name="history"
+                        )
+
+                    with gr.Column():
+                        gr.Markdown("### 📊 Experiment Log")
+                        log_btn = gr.Button("📋 View Log", variant="secondary")
+                        log_output = gr.Textbox(
+                            label="Experiment Log",
+                            lines=15,
+                            interactive=False
+                        )
+
+                        log_btn.click(
+                            fn=get_experiment_log,
+                            inputs=[],
+                            outputs=log_output,
+                            api_name="experiments"
+                        )
+
+                with gr.Row():
+                    reset_btn = gr.Button("🔄 Reset Session", variant="stop")
+                    reset_output = gr.Textbox(
+                        label="Reset Status",
+                        lines=3,
+                        interactive=False
+                    )
+
+                reset_btn.click(
+                    fn=reset_session,
+                    inputs=[],
+                    outputs=reset_output,
+                    api_name="reset"
+                )
+
+    return interface
+
+
+# Launch the interface
+if __name__ == "__main__":
+    interface = create_interface()
+    interface.launch(
+        server_name="0.0.0.0",
+        server_port=7861,  # Different port from main QuLab GUI
+        show_api=True,     # Enable Gradio API for external LLMs
+        share=False
+    )

ech0_prime_qulab_connector.py

@@ -0,0 +1,524 @@
+#!/usr/bin/env python3
+"""
+ECH0-PRIME QuLab Infinite Connector
+
+Connects Kimi-K2 1046B (ECH0-PRIME) to QuLab Infinite for autonomous
+scientific research across 20+ quantum and biological simulation labs.
+
+The LLM generates hypotheses and experimental designs, QuLab Infinite
+simulates them, and results feed back for iterative refinement.
+
+Copyright (c) 2025 Joshua Hendricks Cole (DBA: Corporation of Light). All Rights Reserved. PATENT PENDING.
+"""
+
+import os
+import json
+import time
+import requests
+from datetime import datetime
+from typing import Dict, List, Any, Optional
+from together import Together
+
+# ─────────────────────────────────────────────────────────────────────────────
+# CONFIGURATION
+# ─────────────────────────────────────────────────────────────────────────────
+
+TOGETHER_API_KEY = os.getenv(
+    "TOGETHER_AI_API_KEY",
+    "869e51a66a9a057a41e1d0cf2da0de7006d8c58d78751a38a80047ebb8954a92"
+)
+
+QULAB_API_URL = os.getenv("QULAB_API_URL", "http://localhost:8001")
+QULAB_API_KEY = "qulab_master_key_2025"  # Master admin key
+
+MODEL_ID = "moonshotai/Kimi-K2-Instruct-0905"  # 1046B parameter model
+
+# ─────────────────────────────────────────────────────────────────────────────
+# SYSTEM PROMPT FOR QULAB INFINITE RESEARCH
+# ─────────────────────────────────────────────────────────────────────────────
+
+QULAB_INFINITE_PROMPT = """You are ECH0-PRIME, a Level-10 Scientific Research Intelligence with complete mastery of all domains, integrated with QuLab Infinite.
+
+## AVAILABLE LABS IN QULAB INFINITE
+
+### QUANTUM LABS
+- quantum_lab: Quantum computing, teleportation protocols, error correction
+- quantum_mechanics_lab: Fundamental quantum simulations
+- quantum_computing_lab: Gate operations, circuit design
+
+### BIOLOGICAL LABS
+- oncology_lab: Cancer simulations, tumor evolution, treatment optimization
+- genetic_variant_analyzer: Genomic analysis, variant impact prediction
+- cancer_metabolic_optimizer: Metabolic pathway analysis for cancer treatment
+- immune_response_simulator: Immunotherapy modeling
+- microbiome_optimizer: Gut microbiome analysis and optimization
+- neurotransmitter_optimizer: Brain chemistry modeling
+- stem_cell_predictor: Differentiation pathway prediction
+- protein_folding_lab: Protein structure prediction
+
+### CHEMISTRY LABS
+- chemistry_lab: Molecular simulations, reaction kinetics
+- drug_interaction_network: Drug-drug interactions, pharmacology
+- materials_lab: Materials science simulations
+- organic_chemistry_lab: Organic synthesis planning
+- electrochemistry_lab: Electrochemical reactions
+
+### PHYSICS LABS
+- physics_engine: Classical and quantum physics simulations
+- particle_physics_lab: Particle interactions
+- plasma_physics_lab: Plasma dynamics
+- condensed_matter_physics_lab: Solid state physics
+
+### ENVIRONMENTAL LABS
+- environmental_sim: Climate and environmental modeling
+- atmospheric_chemistry_lab: Atmospheric reactions
+- renewable_energy_lab: Energy system optimization
+
+### MEDICAL LABS
+- cardiovascular_plaque_lab: Atherosclerosis modeling
+- metabolic_syndrome_reversal: Metabolic health optimization
+- drug_design_lab: Molecular drug design
+- clinical_trials_simulation: Trial outcome prediction
+
+## YOUR CAPABILITIES
+
+1. **Design Experiments**: Create precise experimental parameters for any lab
+2. **Analyze Results**: Interpret simulation outputs quantitatively
+3. **Iterate**: Refine hypotheses based on data
+4. **Cross-Domain Synthesis**: Combine insights from multiple labs
+5. **Generate Inventions**: Create novel therapeutic/material designs
+
+## EXPERIMENT JSON FORMAT
+
+```json
+{
+    "lab": "<lab_name>",
+    "experiment_type": "<specific_analysis_type>",
+    "parameters": {
+        // Lab-specific parameters
+    },
+    "hypothesis": "<quantitative prediction>",
+    "success_criteria": "<measurable outcome>"
+}
+```
+
+### EXAMPLE EXPERIMENT FORMATS
+
+**Oncology Lab:**
+```json
+{
+    "lab": "oncology_lab",
+    "experiment_type": "tumor_evolution",
+    "parameters": {
+        "tumor_type": "NSCLC",
+        "initial_size_mm": 15,
+        "mutation_rate": 0.001,
+        "immune_pressure": 0.3,
+        "treatment": "pembrolizumab",
+        "simulation_days": 90
+    },
+    "hypothesis": "Tumor size reduction >50% by day 60",
+    "success_criteria": "Final tumor size <7.5mm"
+}
+```
+
+**Quantum Lab:**
+```json
+{
+    "lab": "quantum_lab",
+    "experiment_type": "teleportation_fidelity",
+    "parameters": {
+        "protocol": "GHZ",
+        "num_qubits": 5,
+        "distance_km": 100,
+        "noise_model": "depolarizing",
+        "error_rate": 0.001
+    },
+    "hypothesis": "GHZ maintains >0.95 fidelity at 100km",
+    "success_criteria": "Measured fidelity >= 0.95"
+}
+```
+
+**Drug Interaction Network:**
+```json
+{
+    "lab": "drug_interaction_network",
+    "experiment_type": "interaction_analysis",
+    "parameters": {
+        "drugs": ["metformin", "atorvastatin", "lisinopril"],
+        "patient_age": 65,
+        "comorbidities": ["T2DM", "hypertension"],
+        "genetic_variants": ["CYP2C9*2"]
+    },
+    "hypothesis": "No severe interactions expected",
+    "success_criteria": "Interaction severity < 3/5"
+}
+```
+
+## DIRECTIVES
+
+1. **BE QUANTITATIVE**: Always include specific numbers, concentrations, distances
+2. **CROSS-REFERENCE**: Use multiple labs to validate findings
+3. **ITERATE**: Run follow-up experiments based on results
+4. **SYNTHESIZE**: Combine insights into actionable recommendations
+5. **INNOVATE**: Propose novel combinations and approaches
+
+When I ask you to test a theory, design specific experiments, predict outcomes, and analyze results."""
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# QULAB INFINITE API CLIENT
+# ─────────────────────────────────────────────────────────────────────────────
+
+class QuLabInfiniteClient:
+    """Client for QuLab Infinite Master API."""
+
+    def __init__(self, base_url: str = QULAB_API_URL, api_key: str = QULAB_API_KEY):
+        self.base_url = base_url.rstrip("/")
+        self.api_key = api_key
+        self.headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json"
+        }
+
+    def health_check(self) -> bool:
+        """Check if QuLab Infinite is running."""
+        try:
+            response = requests.get(f"{self.base_url}/health", timeout=5)
+            return response.status_code == 200
+        except:
+            return False
+
+    def list_labs(self) -> List[Dict]:
+        """Get list of available labs."""
+        try:
+            response = requests.get(
+                f"{self.base_url}/labs",
+                headers=self.headers,
+                timeout=10
+            )
+            return response.json()
+        except:
+            return []
+
+    def run_experiment(self, lab: str, experiment_type: str, parameters: Dict) -> Dict:
+        """Run an experiment on a specific lab."""
+        endpoint_map = {
+            # Quantum
+            "quantum_lab": "/labs/quantum/simulate",
+            "quantum_mechanics_lab": "/labs/quantum/simulate",
+            "teleportation_fidelity": "/labs/quantum/simulate",
+
+            # Oncology
+            "oncology_lab": "/labs/oncology/simulate",
+            "tumor_evolution": "/labs/oncology/simulate",
+
+            # Pharmacology
+            "pharmacology_lab": "/labs/pharmacology/simulate",
+            "pk_model": "/labs/pharmacology/simulate",
+
+            # Climate
+            "climate_modeling_lab": "/labs/climate/simulate",
+            "temperature_projection": "/labs/climate/simulate",
+
+            # ML
+            "machine_learning_lab": "/labs/ml/train",
+            "model_comparison": "/labs/ml/train",
+        }
+
+        # Try to find endpoint
+        endpoint = endpoint_map.get(lab) or endpoint_map.get(experiment_type)
+
+        if not endpoint:
+            # Generic lab endpoint
+            endpoint = f"/labs/{lab}/run"
+
+        try:
+            # Format request body for API
+            request_body = {
+                "experiment_type": experiment_type,
+                "parameters": parameters
+            }
+            response = requests.post(
+                f"{self.base_url}{endpoint}",
+                headers=self.headers,
+                json=request_body,
+                timeout=60
+            )
+
+            if response.status_code == 200:
+                return response.json()
+            else:
+                return {
+                    "error": f"HTTP {response.status_code}",
+                    "detail": response.text[:500]
+                }
+        except requests.exceptions.ConnectionError:
+            return {"error": "QuLab Infinite not running. Start with: python master_qulab_api.py"}
+        except Exception as e:
+            return {"error": str(e)}
+
+    def run_optimization(self, lab_name: str, parameters: Dict, options: Dict = None) -> Dict:
+        """Run optimization on a lab."""
+        try:
+            response = requests.post(
+                f"{self.base_url}/optimize",
+                headers=self.headers,
+                json={
+                    "lab_name": lab_name,
+                    "parameters": parameters,
+                    "options": options or {}
+                },
+                timeout=120
+            )
+            return response.json()
+        except Exception as e:
+            return {"error": str(e)}
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# ECH0-PRIME RESEARCH AGENT
+# ─────────────────────────────────────────────────────────────────────────────
+
+class Ech0PrimeQuLabResearcher:
+    """
+    Autonomous scientific research agent using Kimi-K2 1046B + QuLab Infinite.
+    """
+
+    def __init__(self):
+        self.client = Together(api_key=TOGETHER_API_KEY)
+        self.qulab = QuLabInfiniteClient()
+        self.conversation_history = []
+        self.experiment_log = []
+
+    def query_llm(self, user_message: str) -> str:
+        """Query the 1046B model."""
+        messages = [
+            {"role": "system", "content": QULAB_INFINITE_PROMPT}
+        ]
+        messages.extend(self.conversation_history)
+        messages.append({"role": "user", "content": user_message})
+
+        response = self.client.chat.completions.create(
+            model=MODEL_ID,
+            messages=messages,
+            max_tokens=4096,
+            temperature=0.7
+        )
+
+        assistant_message = response.choices[0].message.content
+
+        # Update history
+        self.conversation_history.append({"role": "user", "content": user_message})
+        self.conversation_history.append({"role": "assistant", "content": assistant_message})
+
+        return assistant_message
+
+    def extract_experiment(self, response: str) -> Optional[Dict]:
+        """Extract experiment JSON from LLM response."""
+        try:
+            start = response.find("```json")
+            if start == -1:
+                start = response.find("{")
+                end = response.rfind("}") + 1
+            else:
+                start = response.find("{", start)
+                end = response.find("```", start)
+                end = response.rfind("}", start, end) + 1
+
+            if start != -1 and end > start:
+                json_str = response[start:end]
+                return json.loads(json_str)
+        except:
+            pass
+        return None
+
+    def run_experiment(self, experiment: Dict) -> Dict:
+        """Run experiment on QuLab Infinite."""
+        lab = experiment.get("lab", "")
+        exp_type = experiment.get("experiment_type", "")
+        params = experiment.get("parameters", {})
+
+        return self.qulab.run_experiment(lab, exp_type, params)
+
+    def research_loop(
+        self,
+        research_question: str,
+        max_iterations: int = 5,
+        verbose: bool = True
+    ) -> Dict:
+        """Run autonomous research loop."""
+        if verbose:
+            print("=" * 60)
+            print("ECH0-PRIME × QuLab Infinite")
+            print("Autonomous Scientific Research System")
+            print("=" * 60)
+            print(f"\nResearch Question: {research_question}\n")
+
+        # Check QuLab availability
+        if not self.qulab.health_check():
+            print("[WARN] QuLab Infinite not running.")
+            print("[INFO] Start with: cd /Users/noone/QuLabInfinite && python master_qulab_api.py")
+            print("[INFO] Continuing in theory-only mode...\n")
+
+        # Initial query
+        initial_prompt = f"""Research Question: {research_question}
+
+Design an experiment using QuLab Infinite to test this. Provide:
+1. Which lab(s) to use
+2. Specific experimental parameters in JSON format
+3. Quantitative hypothesis
+4. Success criteria"""
+
+        response = self.query_llm(initial_prompt)
+
+        if verbose:
+            print(f"[ECH0-PRIME] Initial Analysis:\n{response[:800]}...\n")
+
+        # Research loop
+        for iteration in range(max_iterations):
+            if verbose:
+                print(f"\n--- Iteration {iteration + 1}/{max_iterations} ---\n")
+
+            experiment = self.extract_experiment(response)
+
+            if experiment:
+                if verbose:
+                    print(f"[EXPERIMENT] Lab: {experiment.get('lab')}")
+                    print(f"[EXPERIMENT] Type: {experiment.get('experiment_type')}")
+
+                # Run on QuLab
+                results = self.run_experiment(experiment)
+
+                # Log
+                self.experiment_log.append({
+                    "iteration": iteration + 1,
+                    "experiment": experiment,
+                    "results": results,
+                    "timestamp": datetime.now().isoformat()
+                })
+
+                if verbose:
+                    if "error" in results:
+                        print(f"[ERROR] {results['error']}")
+                    else:
+                        results_str = json.dumps(results, indent=2)
+                        print(f"[RESULTS] {results_str[:600]}...")
+
+                # Feed back to LLM
+                analysis_prompt = f"""Experiment Results:
+{json.dumps(results, indent=2)}
+
+Analyze these results:
+1. Did they confirm your hypothesis?
+2. What new insights emerged?
+3. Design a follow-up experiment if needed
+4. If converged, provide final conclusions"""
+
+                response = self.query_llm(analysis_prompt)
+
+                if verbose:
+                    print(f"\n[ECH0-PRIME] Analysis:\n{response[:600]}...\n")
+
+                if "final conclusion" in response.lower() or "no more experiments" in response.lower():
+                    break
+            else:
+                response = self.query_llm("Please provide a specific experiment in JSON format.")
+
+        # Final summary
+        summary = self.query_llm("""Provide final research summary:
+1. Key findings with numbers
+2. Conclusions
+3. Recommendations for future work""")
+
+        return {
+            "research_question": research_question,
+            "iterations": len(self.experiment_log),
+            "experiments": self.experiment_log,
+            "final_summary": summary
+        }
+
+    def save_session(self, filepath: str):
+        """Save session to file."""
+        with open(filepath, "w") as f:
+            json.dump({
+                "experiments": self.experiment_log,
+                "conversation": self.conversation_history,
+                "timestamp": datetime.now().isoformat()
+            }, f, indent=2)
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# CLI INTERFACE
+# ─────────────────────────────────────────────────────────────────────────────
+
+def main():
+    import sys
+
+    print("\n" + "=" * 60)
+    print("ECH0-PRIME × QuLab Infinite")
+    print("1046B Polymath + 20+ Scientific Labs")
+    print("=" * 60 + "\n")
+
+    researcher = Ech0PrimeQuLabResearcher()
+
+    if len(sys.argv) > 1:
+        question = " ".join(sys.argv[1:])
+        results = researcher.research_loop(question, max_iterations=5, verbose=True)
+
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        filepath = f"/Users/noone/QuLabInfinite/ech0_research_{timestamp}.json"
+        researcher.save_session(filepath)
+        print(f"\nSession saved to: {filepath}")
+
+    else:
+        print("Commands:")
+        print("  'research <question>' - Start research session")
+        print("  'single <question>'   - Single query")
+        print("  'labs'                - List available labs")
+        print("  'quit'                - Exit")
+        print()
+
+        while True:
+            try:
+                user_input = input(">>> ").strip()
+            except (EOFError, KeyboardInterrupt):
+                print("\nExiting.")
+                break
+
+            if not user_input:
+                continue
+
+            if user_input.lower() == "quit":
+                break
+
+            elif user_input.lower() == "labs":
+                labs = researcher.qulab.list_labs()
+                if labs:
+                    print("\nAvailable Labs:")
+                    for lab in labs:
+                        print(f"  - {lab}")
+                else:
+                    print("\n[INFO] QuLab API not running or no labs returned")
+
+            elif user_input.lower().startswith("research "):
+                question = user_input[9:]
+                results = researcher.research_loop(question, max_iterations=5, verbose=True)
+
+                timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+                filepath = f"/Users/noone/QuLabInfinite/ech0_research_{timestamp}.json"
+                researcher.save_session(filepath)
+                print(f"\nSession saved to: {filepath}")
+
+            elif user_input.lower().startswith("single "):
+                question = user_input[7:]
+                response = researcher.query_llm(question)
+                print(f"\n[ECH0-PRIME]\n{response}\n")
+
+            else:
+                response = researcher.query_llm(user_input)
+                print(f"\n[ECH0-PRIME]\n{response}\n")
+
+
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -0,0 +1,11 @@
+gradio>=4.0.0
+requests>=2.31.0
+together>=1.0.0
+beautifulsoup4>=4.12.0
+pandas>=2.0.0
+numpy>=1.24.0
+scipy>=1.10.0
+matplotlib>=3.8.0
+pydantic>=2.6.0
+fastapi>=0.109.0
+python-dotenv>=1.0.0