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"""
HuggingFace Spaces App for DReamMachine
Gradio interface for the multi-agent dream orchestration system
"""
import os
import gradio as gr
import logging
from datetime import datetime
import json
from typing import List, Tuple
from orchestrator import DreamOrchestrator
from data_logger import DataLogger
# Configure logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
handlers=[
logging.StreamHandler(),
logging.FileHandler('dreammachine.log')
]
)
logger = logging.getLogger(__name__)
# Initialize orchestrator (will use HF_TOKEN from environment)
orchestrator = None
data_logger = None
def initialize_system():
"""Initialize the orchestrator and data logger"""
global orchestrator, data_logger
try:
hf_token = os.getenv('HF_TOKEN')
if not hf_token:
logger.warning("HF_TOKEN not found. Some features may be limited.")
return "β οΈ HF_TOKEN not set. Please add it in Space settings."
orchestrator = DreamOrchestrator(config_path="config.yaml", hf_token=hf_token)
data_logger = DataLogger(config_path="config.yaml", hf_token=hf_token)
# Initialize HuggingFace dataset
try:
data_logger.initialize_hf_dataset()
except Exception as e:
logger.warning(f"Could not initialize HF dataset: {str(e)}")
logger.info("System initialized successfully")
return "β System initialized successfully!"
except Exception as e:
logger.error(f"Failed to initialize system: {str(e)}")
import traceback
logger.error(traceback.format_exc())
return f"β Initialization error: {str(e)}"
def run_single_dream_round(stage: str = "init_1_25") -> Tuple[str, str, str, str, str]:
"""
Run a single dream round and return results
Returns:
Tuple of (summary, pitch, technical, feasibility, scorecard)
"""
global orchestrator
if orchestrator is None:
init_msg = initialize_system()
if "error" in init_msg.lower():
return init_msg, "", "", "", ""
try:
logger.info(f"Running dream round with stage: {stage}")
# Run the dream round
session_data = orchestrator.run_dream_round(stage=stage)
# Extract results
summary = f"""
# Dream Session Complete!
**Session ID**: {session_data.get('session_id', 'N/A')}
**Life Stage**: {session_data.get('life_stage', 'N/A')}
**Execution Time**: {session_data.get('execution_time_seconds', 0):.2f} seconds
## Scores
- **Originality**: {session_data['curator_scorecard'].get('originality', 'N/A')}/10
- **Feasibility**: {session_data['curator_scorecard'].get('feasibility', 'N/A')}/10
- **Global Impact**: {session_data['curator_scorecard'].get('global_impact', 'N/A')}/10
- **Narrative Coherence**: {session_data['curator_scorecard'].get('narrative_coherence', 'N/A')}/10
**Reforge Flag**: {"β Yes" if session_data['curator_scorecard'].get('reforge_flag') else "β No"}
## Next Action
**Type**: {session_data['next_action'].get('type', 'N/A')}
**Reason**: {session_data['next_action'].get('reason', 'N/A')}
"""
pitch = session_data.get('pitch_narrative', '')
technical = session_data.get('technical_components', '')
feasibility = session_data.get('feasibility_report', '')
scorecard = json.dumps(session_data.get('curator_scorecard', {}), indent=2)
return summary, pitch, technical, feasibility, scorecard
except Exception as e:
error_msg = f"Error running dream round: {str(e)}"
logger.error(error_msg)
return error_msg, "", "", "", ""
def run_batch_rounds(num_rounds: int, sleep_between: int) -> str:
"""
Run multiple dream rounds in batch
Args:
num_rounds: Number of rounds to run
sleep_between: Seconds between rounds
Returns:
Summary of batch execution
"""
global orchestrator
if orchestrator is None:
init_msg = initialize_system()
if "error" in init_msg.lower():
return init_msg
try:
logger.info(f"Starting batch mode: {num_rounds} rounds")
results = orchestrator.run_batch_mode(
num_rounds=int(num_rounds),
sleep_between=int(sleep_between)
)
# Generate summary
summary = f"# Batch Execution Complete!\n\n"
summary += f"**Total Rounds**: {len(results)}\n"
summary += f"**Successful**: {len([r for r in results if r.get('curator_scorecard')])}\n\n"
# Count outcomes
reforge_count = sum(1 for r in results if r.get('curator_scorecard', {}).get('reforge_flag'))
summary += f"**Reforge-Eligible Ideas**: {reforge_count}\n\n"
# Average scores
if results:
avg_originality = sum(r.get('curator_scorecard', {}).get('originality', 0) for r in results) / len(results)
avg_feasibility = sum(r.get('curator_scorecard', {}).get('feasibility', 0) for r in results) / len(results)
avg_impact = sum(r.get('curator_scorecard', {}).get('global_impact', 0) for r in results) / len(results)
summary += f"## Average Scores\n"
summary += f"- Originality: {avg_originality:.1f}/10\n"
summary += f"- Feasibility: {avg_feasibility:.1f}/10\n"
summary += f"- Global Impact: {avg_impact:.1f}/10\n\n"
# List sessions
summary += f"## Session IDs\n"
for i, result in enumerate(results, 1):
session_id = result.get('session_id', 'N/A')
reforge = "β" if result.get('curator_scorecard', {}).get('reforge_flag') else "β"
summary += f"{i}. {session_id} (Reforge: {reforge})\n"
return summary
except Exception as e:
error_msg = f"Error in batch mode: {str(e)}"
logger.error(error_msg)
return error_msg
def view_session_history() -> str:
"""View all logged sessions"""
global data_logger
if data_logger is None:
data_logger = DataLogger(config_path="config.yaml", hf_token=os.getenv('HF_TOKEN'))
try:
sessions = data_logger.get_all_sessions()
if not sessions:
return "No sessions found in history."
summary = f"# Session History ({len(sessions)} total)\n\n"
for i, session in enumerate(sessions, 1):
scorecard = session.get('curator_scorecard', {})
summary += f"## {i}. {session.get('session_id', 'Unknown')}\n"
summary += f"- **Stage**: {session.get('life_stage', 'N/A')}\n"
summary += f"- **Timestamp**: {session.get('timestamp', 'N/A')}\n"
summary += f"- **Originality**: {scorecard.get('originality', 'N/A')}/10\n"
summary += f"- **Feasibility**: {scorecard.get('feasibility', 'N/A')}/10\n"
summary += f"- **Reforge**: {'Yes' if scorecard.get('reforge_flag') else 'No'}\n\n"
return summary
except Exception as e:
return f"Error loading history: {str(e)}"
# Create Gradio interface
with gr.Blocks(title="DReamMachine - LLM Brainstorm System", theme=gr.themes.Soft()) as demo:
gr.Markdown("""
# π DReamMachine: Dream A LiL(LLM) Dream
Multi-agent LLM orchestration system for breakthrough innovation discovery via guided hallucination.
## How It Works
1. **Dreamers** (3x creative LLMs) generate radical ideas
2. **Writer/Logger/Narrator** refine concepts into coherent narratives
3. **Deep Thinker** evaluates scientific feasibility
4. **Curator** scores ideas across multiple dimensions
5. **System** decides whether to advance ideas through life stages (1-25, 26-50, 51-75, 76-100 years)
Ideas that score high on originality AND feasibility progress through simulated 100-year lifespans!
""")
# Status indicator
with gr.Row():
status_text = gr.Markdown("### System Status")
init_btn = gr.Button("π Initialize System", size="sm", variant="secondary")
init_output = gr.Markdown("")
init_btn.click(fn=initialize_system, inputs=[], outputs=[init_output])
with gr.Tab("Single Dream Round"):
gr.Markdown("### Run a single dream round")
stage_selector = gr.Dropdown(
choices=["init_1_25", "mid_26_50", "late_51_75", "final_76_100"],
value="init_1_25",
label="Life Stage",
info="Select which life stage to run"
)
run_single_btn = gr.Button("π Run Dream Round", variant="primary", size="lg")
with gr.Row():
with gr.Column():
summary_output = gr.Markdown(label="Session Summary")
with gr.Accordion("Dream Outputs", open=False):
pitch_output = gr.Textbox(label="Narrative Pitch", lines=10)
technical_output = gr.Textbox(label="Technical Components", lines=10)
feasibility_output = gr.Textbox(label="Feasibility Report", lines=10)
scorecard_output = gr.Textbox(label="Curator Scorecard (JSON)", lines=10)
run_single_btn.click(
fn=run_single_dream_round,
inputs=[stage_selector],
outputs=[summary_output, pitch_output, technical_output, feasibility_output, scorecard_output]
)
with gr.Tab("Batch Mode"):
gr.Markdown("### Run multiple dream rounds automatically")
with gr.Row():
num_rounds_input = gr.Slider(
minimum=1,
maximum=50,
value=5,
step=1,
label="Number of Rounds"
)
sleep_input = gr.Slider(
minimum=0,
maximum=300,
value=10,
step=5,
label="Sleep Between Rounds (seconds)"
)
run_batch_btn = gr.Button("π Run Batch Mode", variant="primary", size="lg")
batch_output = gr.Markdown(label="Batch Results")
run_batch_btn.click(
fn=run_batch_rounds,
inputs=[num_rounds_input, sleep_input],
outputs=[batch_output]
)
with gr.Tab("Session History"):
gr.Markdown("### View all logged sessions")
refresh_history_btn = gr.Button("π Refresh History", variant="secondary")
history_output = gr.Markdown(label="Session History")
refresh_history_btn.click(
fn=view_session_history,
inputs=[],
outputs=[history_output]
)
with gr.Tab("About"):
gr.Markdown("""
## π― Project Concept
**DReamMachine** is an experimental system that uses "controlled hallucination" to discover breakthrough innovations.
By guiding LLMs through a simulated 100-year creative journey, the system explores the full lifecycle of ideas -
from initial discovery through real-world challenges to mass adoption and legacy.
### The 7-Step Dream Cycle
Each "dream round" follows this process:
1. **Setup**: Initialize life stage prompt and constraints
2. **Dream & Generate**: 3 creative LLMs generate wild ideas
3. **Log & Narrate**: Writer/Logger/Narrator refine outputs
4. **Deep Think & Verify**: Analytical LLM checks feasibility
5. **Curate & Grade**: Evaluation LLM scores the concept
6. **Data Storage**: Archive to HuggingFace dataset
7. **Reforge Loop**: Advance successful ideas to next life stage
### Life Stages
- **Ages 1-25**: Foundational Discovery (bold creativity)
- **Ages 26-50**: Commercialization & Crisis (real-world testing)
- **Ages 51-75**: Mass Adoption & Ethics (societal impact)
- **Ages 76-100**: Legacy & Vision (long-term thinking)
### Scoring Criteria
- **Originality** (1-10): How novel is the idea?
- **Feasibility** (1-10): Can this actually be built?
- **Global Impact** (1-10): How many people benefit?
- **Narrative Coherence** (1-10): Is the pitch compelling?
Ideas with Feasibility > 7 AND Originality > 5 advance to the next life stage!
---
**Created by**: Dave Roby / DRStudios
**Inspired by**: Conversations with Gemini 2.5 Flash
**Built with**: Claude Sonnet 4.5 via Claude Code
""")
if __name__ == "__main__":
# For HuggingFace Spaces
# Try to initialize on startup (but don't crash if it fails)
try:
logger.info("Attempting to initialize system on startup...")
result = initialize_system()
logger.info(f"Initialization result: {result}")
except Exception as e:
logger.error(f"Startup initialization failed: {str(e)}")
logger.error("App will start anyway. Initialize manually from the interface.")
demo.launch(server_name="0.0.0.0", server_port=7860)
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