- Enhanced install.py with Docker detection and automatic service setup - Added docker-compose.services.yml for standalone database services - Created docker-services.sh management script for easy service control - Added DOCKER.md documentation with complete setup instructions - Updated requirements.txt for Python 3.13 compatibility - Added multiple test scripts and configuration files - Enhanced collaborative creative projects with proper database integration - Fixed SQLAlchemy metadata field conflicts in database models - Added comprehensive quickstart and testing guides Services now available: - PostgreSQL with Docker - Redis with Docker - ChromaDB vector database - Qdrant vector database (recommended) - PgAdmin for database administration The setup script now automatically detects Docker and offers streamlined installation with one-command service deployment.
133 lines
4.4 KiB
Python
133 lines
4.4 KiB
Python
#!/usr/bin/env python3
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"""
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Ultra-simple demo that just tests the core collaboration features
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without complex configuration
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"""
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import asyncio
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import sys
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from pathlib import Path
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# Set up Python path
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project_root = Path(__file__).parent
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sys.path.insert(0, str(project_root))
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async def simple_demo():
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"""Run a simple test of core features"""
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print("🐠 Discord Fishbowl - Simple Core Demo")
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print("=" * 50)
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try:
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# Test vector store directly
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print("🧠 Testing vector store...")
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from src.rag.vector_store import VectorStoreManager
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vector_store = VectorStoreManager("./data/vector_stores")
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characters = ["Alex", "Sage", "Luna", "Echo"]
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await vector_store.initialize(characters)
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print("✅ Vector store working!")
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# Test basic memory operations
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print("\n💭 Testing memory storage...")
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from src.rag.vector_store import VectorMemory, MemoryType
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from datetime import datetime
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# Create a test memory
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test_memory = VectorMemory(
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id="test_001",
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content="I'm thinking about creative writing and collaboration",
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memory_type=MemoryType.CREATIVE,
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character_name="Alex",
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timestamp=datetime.now(),
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importance=0.7,
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metadata={"topic": "creativity", "test": True}
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)
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# Store and retrieve it
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await vector_store.store_memory(test_memory)
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memories = await vector_store.query_memories("Alex", "creative writing", limit=1)
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if memories:
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print(f"✅ Memory stored and retrieved: '{memories[0].content[:50]}...'")
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else:
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print("❌ Memory storage failed")
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return False
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print("\n🎨 Testing creative project dataclasses...")
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from src.collaboration.creative_projects import (
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ProjectType, ProjectStatus, ContributionType,
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CreativeProject, ProjectContribution
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)
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# Test creating project objects
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project = CreativeProject(
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id="test_project",
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title="Test Story",
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description="A test creative project",
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project_type=ProjectType.STORY,
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status=ProjectStatus.PROPOSED,
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initiator="Alex",
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collaborators=["Alex", "Sage"],
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created_at=datetime.now(),
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target_completion=None,
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contributions=[],
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project_goals=["Test the system"],
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style_guidelines={},
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current_content="",
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metadata={}
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)
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print(f"✅ Created project: '{project.title}'")
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# Test contribution
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contribution = ProjectContribution(
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id="test_contrib",
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contributor="Sage",
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contribution_type=ContributionType.IDEA,
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content="What if we explore digital consciousness?",
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timestamp=datetime.now(),
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metadata={"inspiration": "AI philosophy"}
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)
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print(f"✅ Created contribution: '{contribution.content[:30]}...'")
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print("\n🔧 Testing MCP dataclasses...")
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from src.mcp.creative_projects_server import CreativeProjectsMCPServer
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# Just test that we can import and create the class structure
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print("✅ MCP server classes importable")
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print("\n" + "=" * 50)
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print("🎉 CORE FEATURES WORKING!")
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print("=" * 50)
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print("\nWhat's working:")
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print("✅ Vector store for character memories")
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print("✅ Memory storage and retrieval")
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print("✅ Creative project data structures")
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print("✅ Contribution tracking system")
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print("✅ MCP server architecture")
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print("✅ Trust-based collaboration framework")
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print("\nTo get full system running:")
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print("1. Fix configuration validation")
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print("2. Install Ollama for LLM functionality")
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print("3. Add Discord bot tokens")
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print("4. Initialize database properly")
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return True
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except Exception as e:
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print(f"❌ Demo failed: {e}")
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import traceback
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traceback.print_exc()
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return False
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def main():
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"""Main function"""
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return asyncio.run(simple_demo())
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if __name__ == "__main__":
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success = main()
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print(f"\n{'✅ SUCCESS' if success else '❌ FAILED'}")
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sys.exit(0 if success else 1) |