-
🔥 Code-Forge
-
Localized Multi-KB RAG System with MCP Integration
+---
+
+## 🚀 What is Code-Forge?
+
+**Code-Forge** is a **localized, production-grade RAG (Retrieval-Augmented Generation) system** that runs entirely on your machine.
+
+### Key Features:
+
+- **🗄️ PostgreSQL + pgvector** - ACID-compliant vector database
+- **🤖 Ollama** - Local LLMs and embeddings (no API keys needed)
+- **🔌 MCP Integration** - Expose knowledge bases to AI agents
+- **📚 Multi-KB Architecture** - Isolated knowledge bases per project
+- **🧠 Advanced RAG** - Vector search, hybrid search, reranking, agentic RAG
+- **🎨 Beautiful UI** - Archon-inspired design
+
+---
+""")
+
+# System Status Check
+st.markdown("## 🔍 System Status")
+
+col1, col2, col3 = st.columns(3)
+
+# Check PostgreSQL
+with col1:
+ st.markdown("### PostgreSQL")
+ try:
+ pg_manager = get_pg_manager()
+ # Try to list collections
+ collections = pg_manager.list_collections()
+ st.markdown(f'
✅ Connected
', unsafe_allow_html=True)
+ st.metric("Knowledge Bases", len(collections))
+ except Exception as e:
+ st.markdown(f'
❌ Not Connected
', unsafe_allow_html=True)
+ st.error(f"Error: {str(e)}")
+ st.info("Make sure PostgreSQL is running and the `codeforge` database exists.")
+
+# Check Ollama
+with col2:
+ st.markdown("### Ollama")
+ try:
+ response = requests.get(f"{Config.OLLAMA_HOST}/api/tags", timeout=2)
+ if response.status_code == 200:
+ models = response.json().get("models", [])
+ st.markdown(f'
✅ Running
', unsafe_allow_html=True)
+ st.metric("Models Installed", len(models))
+ else:
+ st.markdown(f'
⚠️ Unexpected Response
', unsafe_allow_html=True)
+ except Exception as e:
+ st.markdown(f'
❌ Not Running
', unsafe_allow_html=True)
+ st.error(f"Error: {str(e)}")
+ st.info("Make sure Ollama container is running: `docker-compose up -d`")
+
+# Check Required Models
+with col3:
+ st.markdown("### Required Models")
+ try:
+ response = requests.get(f"{Config.OLLAMA_HOST}/api/tags", timeout=2)
+ if response.status_code == 200:
+ models = response.json().get("models", [])
+ model_names = [m["name"] for m in models]
+
+ required_models = ["nomic-embed-text:latest", "llama3.2:3b"]
+ missing_models = [m for m in required_models if m not in model_names]
+
+ if not missing_models:
+ st.markdown(f'
✅ All Present
', unsafe_allow_html=True)
+ st.success("All required models are installed!")
+ else:
+ st.markdown(f'
⚠️ Missing Models
', unsafe_allow_html=True)
+ st.warning(f"Missing: {', '.join(missing_models)}")
+ st.info("Run: `ollama pull nomic-embed-text && ollama pull llama3.2:3b`")
+ except Exception:
+ st.markdown(f'
❌ Cannot Check
', unsafe_allow_html=True)
+
+st.markdown("---")
+
+# Quick Start Guide
+st.markdown("## 🎯 Quick Start Guide")
+
+tab1, tab2, tab3, tab4 = st.tabs(["1️⃣ Create KB", "2️⃣ Ingest Docs", "3️⃣ Query", "4️⃣ MCP"])
+
+with tab1:
+ st.markdown("""
+ ### Creating Your First Knowledge Base
+
+ 1. **Navigate to the main page** (use the sidebar)
+ 2. **Expand "➕ Create New KB"** in the sidebar
+ 3. **Choose a KB type**:
+ - 📚 **GENERIC** - General-purpose knowledge
+ - 💻 **CODE** - Source code repositories
+ - 📖 **DOCUMENTATION** - Technical documentation
+ - 🤖 **AGENT_OS** - Spec-driven development
+ 4. **Enter a name** (e.g., `my-project`)
+ 5. **Add a description** (optional)
+ 6. **Click "Create"**
+
+ ✨ Your knowledge base is now ready for documents!
+ """)
+
+ st.info("💡 **Tip**: Use separate KBs for different projects to keep contexts isolated.")
+
+with tab2:
+ st.markdown("""
+ ### Ingesting Documents
+
+ **Option 1: File Upload**
+ 1. Select your KB from the sidebar
+ 2. Go to the **"📚 Knowledge Base"** tab
+ 3. Click **"Choose files"** and select documents
+ 4. Click **"Upload Files"**
+
+ **Option 2: Directory Import**
+ 1. Select your KB from the sidebar
+ 2. Go to the **"📚 Knowledge Base"** tab
+ 3. Enter the full path to your project directory
+ 4. Click **"Import Directory"**
+
+ **Supported File Types:**
+ - Documents: `.md`, `.txt`, `.pdf`
+ - Code: `.py`, `.js`, `.jsx`, `.ts`, `.tsx`, `.go`, `.rs`, `.java`, `.cpp`, `.c`, `.h`
+ - Config: `.json`, `.yaml`, `.yml`
+ """)
+
+ st.info("💡 **Tip**: For large codebases, use directory import to ingest all files at once.")
+
+with tab3:
+ st.markdown("""
+ ### Querying Your Knowledge Base
+
+ 1. **Select your KB** from the sidebar
+ 2. **Go to the "💬 Chat" tab**
+ 3. **Choose a RAG strategy**:
+ - 🔍 **Base** - Simple vector search (fastest)
+ - 🔀 **Hybrid** - BM25 + vector fusion (better for keywords)
+ - 🎯 **Reranking** - Cross-encoder reranking (most accurate)
+ - 🤖 **Agentic** - Sub-question decomposition (best for complex queries)
+ 4. **Type your question** and press Enter
+ 5. **View sources** by expanding "📚 View Sources"
+
+ **Example Queries:**
+ - "How does authentication work in this codebase?"
+ - "What are the main components of the system?"
+ - "Show me examples of error handling"
+ """)
+
+ st.info("💡 **Tip**: Use hybrid search for technical queries with specific keywords.")
+
+with tab4:
+ st.markdown("""
+ ### MCP Integration (Model Context Protocol)
+
+ Code-Forge exposes your knowledge bases via HTTP for AI agent integration.
+
+ **MCP Server Endpoint:**
+ ```
+ http://localhost:8051/mcp
+ ```
+
+ **Available Tools:**
+ - `list_knowledge_bases` - List all KBs
+ - `create_knowledge_base` - Create new KB
+ - `search_knowledge_base` - Query KB with RAG
+ - `get_kb_stats` - Get KB statistics
+ - `ingest_documents` - Add documents
+ - `get_standards` - Get Agent OS standards
+ - `get_workflows` - Get Agent OS workflows
+ - `get_specs` - Get Agent OS specs
+
+ **Example Request:**
+ ```bash
+ curl -X POST http://localhost:8051/mcp \\
+ -H "Content-Type: application/json" \\
+ -d '{
+ "jsonrpc": "2.0",
+ "id": 1,
+ "method": "tools/call",
+ "params": {
+ "name": "search_knowledge_base",
+ "arguments": {
+ "kb_name": "my-docs",
+ "query": "How do I configure authentication?",
+ "strategy": "hybrid"
+ }
+ }
+ }'
+ ```
+ """)
+
+ st.info("💡 **Tip**: See the README for full MCP API documentation.")
+
+st.markdown("---")
+
+# Feature Highlights
+st.markdown("## ✨ Feature Highlights")
+
+col1, col2 = st.columns(2)
+
+with col1:
+ st.markdown("""
+
+
🗄️ Production-Grade Database
+
PostgreSQL + pgvector ensures your data is safe with ACID compliance,
+ transaction safety, and bulletproof persistence. Your data survives all
+ Docker operations and system restarts.
+
+ """, unsafe_allow_html=True)
+
+ st.markdown("""
+
+
🧠 Advanced RAG Strategies
+
Choose from multiple retrieval strategies: vector search, hybrid search
+ (BM25 + vector), reranking with cross-encoders, or agentic RAG with
+ sub-question decomposition.
+
+ """, unsafe_allow_html=True)
+
+ st.markdown("""
+
+
🔒 100% Local & Private
+
All data stays on your machine. No API keys, no cloud dependencies,
+ no telemetry. Perfect for sensitive codebases and proprietary documentation.
+
+ """, unsafe_allow_html=True)
+
+with col2:
+ st.markdown("""
+
+
🤖 Agent OS Support
+
First-class support for spec-driven development with Agent OS.
+ Ingest standards, workflows, and specs with specialized retrieval tools.
+
+ """, unsafe_allow_html=True)
+
+ st.markdown("""
+
+
🔌 MCP Integration
+
Expose your knowledge bases to AI agents via Model Context Protocol.
+ 12 HTTP endpoints for seamless integration with Claude Desktop and other agents.
+
+ """, unsafe_allow_html=True)
+
+ st.markdown("""
+
+
📚 Multi-KB Architecture
+
Create isolated knowledge bases for different projects. Each KB has
+ its own type, metadata, and documents. Perfect for teams working on
+ multiple projects.
+
+ """, unsafe_allow_html=True)
+
+st.markdown("---")
+
+# Resources
+st.markdown("## 📚 Resources")
+
+col1, col2, col3 = st.columns(3)
+
+with col1:
+ st.markdown("""
+ ### 📖 Documentation
+ - [README.md](../README.md)
+ - [Setup Guide](../docs/SETUP.md)
+ - [Usage Guide](../docs/USAGE.md)
+ - [Troubleshooting](../docs/TROUBLESHOOTING.md)
+ """)
+
+with col2:
+ st.markdown("""
+ ### 🔗 Quick Links
+ - [Streamlit UI](http://localhost:8501)
+ - [MCP Server](http://localhost:8051)
+ - [Ollama API](http://localhost:11434)
+ """)
+
+with col3:
+ st.markdown("""
+ ### 🛠️ Useful Commands
+ ```bash
+ # View logs
+ docker-compose logs -f
+
+ # Restart services
+ docker-compose restart
+
+ # Stop services
+ docker-compose down
+ ```
+ """)
+
+st.markdown("---")
+
+# Footer
+st.markdown("""
+
+
Ready to get started?
+
Use the sidebar to navigate to the main page and create your first knowledge base!
+
Built with ❤️ for the local-first AI community
""", unsafe_allow_html=True)
-# Sidebar
-with st.sidebar:
- st.markdown("## ⚙️ Settings")
-
- # Connection Status
- st.markdown("### 🔌 Connection Status")
-
- ollama_status = check_ollama_health()
- chroma_status = check_chroma_health()
-
- if ollama_status["status"] == "healthy":
- st.markdown('
🟢 Ollama Connected
', unsafe_allow_html=True)
- if ollama_status.get("models"):
- st.caption(f"Models: {', '.join(ollama_status['models'][:3])}")
- else:
- st.markdown('
🔴 Ollama Disconnected
', unsafe_allow_html=True)
- st.caption(ollama_status.get("error", "Unknown error"))
-
- if chroma_status["status"] == "healthy":
- st.markdown('
🟢 ChromaDB Connected
', unsafe_allow_html=True)
- else:
- st.markdown('
🔴 ChromaDB Disconnected
', unsafe_allow_html=True)
- st.caption(chroma_status.get("error", "Unknown error"))
-
- st.divider()
-
- # MCP Server Info
- st.markdown("### 🔗 MCP Server")
- mcp_url = f"http://localhost:{Config.MCP_SERVER_PORT}/mcp"
- st.code(mcp_url, language="text")
-
- st.caption("**Connection Command:**")
- st.code(f"claude mcp add --transport http code-forge {mcp_url}", language="bash")
-
- st.divider()
-
- # Knowledge Base Selector
- st.markdown("### 📚 Knowledge Base")
-
- chroma_manager = get_chroma_manager()
- collections = chroma_manager.list_collections()
-
- if collections:
- selected = st.selectbox(
- "Select KB",
- collections,
- key="kb_selector"
- )
- st.session_state.selected_kb = selected
- else:
- st.warning("No knowledge bases found. Create one below!")
- st.session_state.selected_kb = None
-
- # Create new KB
- with st.expander("➕ Create New KB"):
- new_kb_name = st.text_input("KB Name", key="new_kb_name")
- if st.button("Create"):
- if new_kb_name:
- if chroma_manager.create_collection(new_kb_name):
- st.success(f"Created KB: {new_kb_name}")
- st.rerun()
- else:
- st.error("Failed to create KB")
- else:
- st.error("Please enter a KB name")
-
- st.divider()
-
- # RAG Strategy Toggles
- st.markdown("### 🎯 RAG Strategies")
-
- st.session_state.rag_settings["hybrid"] = st.checkbox(
- "🔀 Hybrid Search",
- value=st.session_state.rag_settings["hybrid"],
- help="**Hybrid Search**: Combines semantic vector search with BM25 keyword search for better recall. Uses reciprocal rank fusion to merge results. Best for queries with specific technical terms."
- )
-
- st.session_state.rag_settings["rerank"] = st.checkbox(
- "🎯 Reranking",
- value=st.session_state.rag_settings["rerank"],
- help="**Reranking**: Re-scores retrieved chunks using a cross-encoder model (ms-marco-MiniLM) for higher precision. Keeps top 3 most relevant results. Improves answer quality but adds latency."
- )
-
- st.session_state.rag_settings["agentic"] = st.checkbox(
- "🤖 Agentic RAG",
- value=st.session_state.rag_settings["agentic"],
- help="**Agentic RAG**: Breaks complex questions into sub-questions and answers them independently before synthesizing. Best for multi-part or analytical queries. Slower but more thorough."
- )
-
-# Main content tabs
-tab1, tab2 = st.tabs(["📚 Knowledge Base", "💬 Chat"])
-
-# Tab 1: Knowledge Base Management
-with tab1:
- st.markdown("## 📚 Knowledge Base Management")
-
- if not st.session_state.selected_kb:
- st.info("👈 Please select or create a knowledge base from the sidebar")
- else:
- st.markdown(f"### Current KB: **{st.session_state.selected_kb}**")
-
- st.markdown("---")
-
- # Document Upload
- col1, col2 = st.columns(2, gap="large")
-
- with col1:
- st.markdown("#### 📤 Upload Documents")
- st.caption("Choose files to upload to the knowledge base")
-
- # Initialize upload counter in session state
- if "upload_counter" not in st.session_state:
- st.session_state.upload_counter = 0
-
- # Use dynamic key to reset file uploader after upload
- uploaded_files = st.file_uploader(
- "Choose files",
- accept_multiple_files=True,
- type=[ext.replace(".", "") for ext in Config.SUPPORTED_FILE_TYPES],
- label_visibility="collapsed",
- key=f"file_uploader_{st.session_state.upload_counter}"
- )
-
- if uploaded_files and st.button("Upload Files", key="upload_files_btn", use_container_width=True):
- try:
- Config.ensure_upload_dir()
- progress_bar = st.progress(0)
- status_container = st.container()
-
- for i, uploaded_file in enumerate(uploaded_files):
- with status_container:
- st.write(f"Processing: {uploaded_file.name}...")
-
- # Save file
- file_path = Path(Config.UPLOAD_DIR) / uploaded_file.name
- with open(file_path, "wb") as f:
- f.write(uploaded_file.getbuffer())
-
- # Ingest file
- result = ingest_file(
- str(file_path),
- st.session_state.selected_kb,
- uploaded_file.name
- )
-
- with status_container:
- if result["status"] == "success":
- st.success(f"✅ {uploaded_file.name}: {result['chunks']} chunks")
- else:
- st.error(f"❌ {uploaded_file.name}: {result.get('error', 'Unknown error')}")
-
- progress_bar.progress((i + 1) / len(uploaded_files))
-
- with status_container:
- st.success("🎉 Upload complete! Refreshing document list...")
-
- # Increment counter to reset file uploader on next render
- st.session_state.upload_counter += 1
-
- # Wait a moment before rerun so user can see the success message
- import time
- time.sleep(1.5)
- st.rerun()
-
- except Exception as e:
- st.error(f"❌ Upload failed: {str(e)}")
- import traceback
- st.code(traceback.format_exc())
-
- with col2:
- st.markdown("#### 📁 Import Directory")
- st.caption("Import all supported files from a directory")
-
- st.info("💡 **Tip:** Mount your directory as a volume in docker-compose.yml first. Paths are relative to `/workspace` in the container.")
-
- dir_path = st.text_input(
- "Directory Path",
- placeholder="/workspace/mounted_docs",
- help="Path must exist inside the Docker container",
- label_visibility="collapsed"
- )
-
- if st.button("Import Directory", key="import_dir_btn", use_container_width=True):
- if not dir_path:
- st.error("Please enter a directory path")
- else:
- with st.spinner("Importing files..."):
- results = ingest_directory(dir_path, st.session_state.selected_kb)
-
- if not results:
- st.warning("No supported files found in directory")
- elif results[0].get("error") and "not found" in results[0].get("error", ""):
- st.error(f"Directory not found: {dir_path}")
- else:
- success_count = sum(1 for r in results if r.get("status") == "success")
- error_count = len(results) - success_count
-
- if success_count > 0:
- st.success(f"✅ Imported {success_count} file(s)")
- if error_count > 0:
- st.warning(f"⚠️ {error_count} file(s) failed")
-
- # Show first 5 results
- for result in results[:5]:
- if result.get("status") == "success":
- st.caption(f"✅ {result.get('filename', 'Unknown')}")
- else:
- st.caption(f"❌ {result.get('filename', 'Unknown')}: {result.get('error', 'Unknown error')}")
-
- if len(results) > 5:
- st.caption(f"... and {len(results) - 5} more")
-
- st.rerun()
-
- st.divider()
-
- # Document Grid
- st.markdown("#### 📄 Documents")
-
- docs = get_documents_metadata(st.session_state.selected_kb)
-
- if not docs:
- st.info("No documents in this knowledge base. Upload files to get started!")
- else:
- # Display in 3-column grid
- cols = st.columns(3)
-
- for i, doc in enumerate(docs):
- with cols[i % 3]:
- # File icon based on type
- icon_map = {
- ".py": "🐍", ".js": "📜", ".jsx": "⚛️",
- ".ts": "📘", ".tsx": "⚛️", ".md": "📄",
- ".pdf": "📕", ".json": "📋", ".yaml": "⚙️"
- }
- icon = icon_map.get(doc["file_type"], "📄")
-
- # Create card
- tags_html = "".join([f'
{tag} ' for tag in doc["tags"]])
-
- st.markdown(f"""
-
-
{icon}
-
{doc["filename"]}
-
{tags_html}
-
- {doc["formatted_date"]}
- {doc["chunk_count"]} chunks
-
-
- """, unsafe_allow_html=True)
-
-# Tab 2: Chat Interface
-with tab2:
- st.markdown("## 💬 Chat with Your Knowledge Base")
-
- if not st.session_state.selected_kb:
- st.info("👈 Please select a knowledge base from the sidebar")
- else:
- # Display active strategies banner
- active_strategies = []
- if st.session_state.rag_settings["hybrid"]:
- active_strategies.append("🔀 Hybrid Search")
- if st.session_state.rag_settings["rerank"]:
- active_strategies.append("🎯 Reranking")
- if st.session_state.rag_settings["agentic"]:
- active_strategies.append("🤖 Agentic RAG")
-
- if active_strategies:
- strategies_text = " + ".join(active_strategies)
- st.markdown(f"""
-
- 🎯 Active Retrieval Strategies: {strategies_text}
-
- """, unsafe_allow_html=True)
- else:
- st.markdown(f"""
-
- 📊 Mode: Standard Vector Search
-
- """, unsafe_allow_html=True)
-
- # Display chat history
- for message in st.session_state.chat_history:
- with st.chat_message(message["role"]):
- st.markdown(message["content"])
-
- if message["role"] == "assistant" and message.get("sources"):
- with st.expander("📚 View Sources"):
- for i, source in enumerate(message["sources"][:3], 1):
- st.markdown(f"**Source {i}:**")
- st.code(source["text"][:200] + "..." if len(source["text"]) > 200 else source["text"])
- if source.get("metadata"):
- st.caption(f"From: {source['metadata'].get('filename', 'Unknown')}")
- if source.get("score"):
- st.caption(f"Score: {source['score']:.3f}")
- st.divider()
-
- # Chat input
- if prompt := st.chat_input("Ask a question about your knowledge base..."):
- # Add user message
- st.session_state.chat_history.append({
- "role": "user",
- "content": prompt
- })
-
- # Display user message
- with st.chat_message("user"):
- st.markdown(prompt)
-
- # Generate response
- with st.chat_message("assistant"):
- with st.spinner("Thinking..."):
- try:
- rag_engine = RAGEngine(st.session_state.selected_kb)
- result = rag_engine.query(
- prompt,
- use_hybrid=st.session_state.rag_settings["hybrid"],
- use_rerank=st.session_state.rag_settings["rerank"],
- use_agentic=st.session_state.rag_settings["agentic"]
- )
-
- answer = result.get("answer", "No answer generated")
- sources = result.get("sources", [])
-
- st.markdown(answer)
-
- # Add to history
- st.session_state.chat_history.append({
- "role": "assistant",
- "content": answer,
- "sources": sources
- })
-
- # Display sources
- if sources:
- with st.expander("📚 View Sources"):
- for i, source in enumerate(sources[:3], 1):
- st.markdown(f"**Source {i}:**")
- st.code(source["text"][:200] + "..." if len(source["text"]) > 200 else source["text"])
- if source.get("metadata"):
- st.caption(f"From: {source['metadata'].get('filename', 'Unknown')}")
- if source.get("score"):
- st.caption(f"Score: {source['score']:.3f}")
- st.divider()
-
- except Exception as e:
- error_msg = f"Error: {str(e)}"
- st.error(error_msg)
- st.session_state.chat_history.append({
- "role": "assistant",
- "content": error_msg
- })
-
- # Clear chat button
- if st.session_state.chat_history and st.button("🗑️ Clear Chat"):
- st.session_state.chat_history = []
- st.rerun()
-
diff --git a/app/pages/0_Welcome.py b/app/pages/0_Welcome.py
new file mode 100644
index 0000000..ba161ac
--- /dev/null
+++ b/app/pages/0_Welcome.py
@@ -0,0 +1,185 @@
+"""
+Welcome page for Code-Forge - Default landing page
+"""
+
+import streamlit as st
+from pathlib import Path
+
+# Page config
+st.set_page_config(
+ page_title="Welcome to Code-Forge",
+ page_icon="🔥",
+ layout="wide",
+ initial_sidebar_state="collapsed"
+)
+
+# Custom CSS - Archon-inspired badass styling
+st.markdown("""
+
+""", unsafe_allow_html=True)
+
+# Hero Section
+hero_path = Path("assets/hero.png")
+
+st.markdown('
', unsafe_allow_html=True)
+
+if hero_path.exists():
+ st.image(str(hero_path), use_container_width=False, output_format="PNG")
+else:
+ st.markdown('
🔥
', unsafe_allow_html=True)
+
+st.markdown("""
+
CODE-FORGE
+
Production-Grade RAG System with PostgreSQL + pgvector
+
+""", unsafe_allow_html=True)
+
+# Navigation
+nav1, nav2, nav3 = st.columns([1, 1, 6])
+with nav1:
+ if st.button("🏠 Welcome", use_container_width=True, type="primary"):
+ st.switch_page("pages/0_Welcome.py")
+with nav2:
+ if st.button("⚙️ Main", use_container_width=True):
+ st.switch_page("pages/1_Main.py")
+
+st.markdown("
", unsafe_allow_html=True)
+
+st.markdown("""
+## 🚀 What is Code-Forge?
+
+**Code-Forge** is a **localized, production-grade RAG system** that runs entirely on your machine.
+
+### Key Features:
+
+- 🗄️ **PostgreSQL + pgvector** - ACID-compliant vector database
+- 🤖 **Ollama** - Local LLMs and embeddings
+- 🔌 **MCP Integration** - Expose knowledge bases to AI agents
+- 📚 **Multi-KB Architecture** - Isolated knowledge bases per project
+- 🧠 **Advanced RAG** - Vector search, hybrid search, reranking, agentic RAG
+
+## 🎯 Quick Start
+
+1. Click **"⚙️ Main"** button above
+2. Create a Knowledge Base from the left panel
+3. Upload documents or import a directory
+4. Start chatting with your knowledge base
+
+---
+
+**Ready to get started? Click the "⚙️ Main" button above!**
+""")
diff --git a/app/pages/1_Main.py b/app/pages/1_Main.py
new file mode 100644
index 0000000..8b5b421
--- /dev/null
+++ b/app/pages/1_Main.py
@@ -0,0 +1,851 @@
+"""
+Code-Forge: Localized Multi-KB RAG System
+Main Streamlit application with badass Archon-inspired UI.
+"""
+
+import logging
+import os
+from pathlib import Path
+
+import streamlit as st
+
+from app.core.pg_manager import get_pg_manager
+from app.core.config import Config
+from app.core.health import check_chroma_health, check_ollama_health
+from app.core.ingestion import ingest_directory, ingest_file
+from app.core.kb_metadata import get_documents_metadata, get_kb_type_badge, get_kb_type_summary
+from app.core.kb_types import KBType, get_kb_type_choices, get_kb_type_info
+from app.core.rag_engine import RAGEngine
+from app.core.agent_os_ingestion import AgentOSIngestion
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Page configuration
+st.set_page_config(
+ page_title="Code-Forge 🔥",
+ page_icon="🔥",
+ layout="wide",
+ initial_sidebar_state="collapsed"
+)
+
+# Initialize session state
+if "selected_kb" not in st.session_state:
+ st.session_state.selected_kb = None
+if "chat_history" not in st.session_state:
+ st.session_state.chat_history = []
+if "rag_settings" not in st.session_state:
+ st.session_state.rag_settings = {
+ "hybrid": False,
+ "rerank": False,
+ "agentic": False
+ }
+
+# Custom CSS with Archon aesthetic
+st.markdown("""
+
+
+
+""", unsafe_allow_html=True)
+
+# Header
+st.markdown("""
+
+
🔥 Code-Forge
+
Localized Multi-KB RAG System with MCP Integration
+
+""", unsafe_allow_html=True)
+
+# Navigation
+nav1, nav2, nav3 = st.columns([1, 1, 6])
+with nav1:
+ if st.button("🏠 Welcome", use_container_width=True, key="nav_welcome"):
+ st.switch_page("pages/0_Welcome.py")
+with nav2:
+ if st.button("⚙️ Main", use_container_width=True, key="nav_main", type="primary"):
+ st.switch_page("pages/1_Main.py")
+
+st.divider()
+
+# Create two-column layout: left panel + main content
+left_col, main_col = st.columns([1, 3], gap="medium")
+
+# Left Panel
+with left_col:
+ st.markdown("## ⚙️ Settings")
+
+ # Connection Status
+ st.markdown("### 🔌 Connection Status")
+
+ ollama_status = check_ollama_health()
+ chroma_status = check_chroma_health()
+
+ if ollama_status["status"] == "healthy":
+ st.markdown('
🟢 Ollama Connected
', unsafe_allow_html=True)
+ if ollama_status.get("models"):
+ st.caption(f"Models: {', '.join(ollama_status['models'][:3])}")
+ else:
+ st.markdown('
🔴 Ollama Disconnected
', unsafe_allow_html=True)
+ st.caption(ollama_status.get("error", "Unknown error"))
+
+ if chroma_status["status"] == "healthy":
+ st.markdown('
🟢 PostgreSQL Connected
', unsafe_allow_html=True)
+ else:
+ st.markdown('
🔴 PostgreSQL Disconnected
', unsafe_allow_html=True)
+ st.caption(chroma_status.get("error", "Unknown error"))
+
+ st.divider()
+
+ # MCP Server Info
+ st.markdown("### 🔗 MCP Server")
+ mcp_url = f"http://localhost:{Config.MCP_SERVER_PORT}/mcp"
+ st.code(mcp_url, language="text")
+
+ st.caption("**Connection Command:**")
+ st.code(f"claude mcp add --transport http code-forge {mcp_url}", language="bash")
+
+ st.divider()
+
+ # Knowledge Base Selector
+ st.markdown("### 📚 Knowledge Base")
+
+ pg_manager = get_pg_manager()
+ collections = pg_manager.list_collections()
+
+ if collections:
+ # Optional type filter
+ type_summary = get_kb_type_summary()
+ filter_options = ["All Types"] + [
+ f"{get_kb_type_info(KBType(kb_type)).icon} {get_kb_type_info(KBType(kb_type)).name} ({count})"
+ for kb_type, count in type_summary.items() if count > 0
+ ]
+
+ selected_filter = st.selectbox(
+ "Filter by Type",
+ options=filter_options,
+ key="kb_type_filter"
+ )
+
+ # Filter collections if needed
+ if selected_filter != "All Types":
+ # Extract the KB type value from the filter string
+ filter_type_value = None
+ for kb_type, count in type_summary.items():
+ type_info = get_kb_type_info(KBType(kb_type))
+ if f"{type_info.icon} {type_info.name}" in selected_filter:
+ filter_type_value = kb_type
+ break
+
+ if filter_type_value:
+ collections = [
+ col for col in collections
+ if col["metadata"].get("kb_type") == filter_type_value
+ ]
+
+ # Build display options with type badges
+ kb_display_options = []
+ kb_name_map = {} # Map display string to actual name
+
+ for col in collections:
+ name = col["name"]
+ metadata = col["metadata"]
+ kb_type = KBType(metadata.get("kb_type", KBType.GENERIC.value))
+ type_info = get_kb_type_info(kb_type)
+
+ display_name = f"{type_info.icon} {name}"
+ kb_display_options.append(display_name)
+ kb_name_map[display_name] = name
+
+ selected_display = st.selectbox(
+ "Select KB",
+ kb_display_options,
+ key="kb_selector"
+ )
+
+ # Map back to actual KB name
+ st.session_state.selected_kb = kb_name_map[selected_display]
+
+ # Display selected KB metadata
+ selected_col = next(
+ (col for col in collections if col["name"] == st.session_state.selected_kb),
+ None
+ )
+
+ if selected_col:
+ metadata = selected_col["metadata"]
+ kb_type = KBType(metadata.get("kb_type", KBType.GENERIC.value))
+
+ # Show type badge
+ st.markdown(get_kb_type_badge(kb_type), unsafe_allow_html=True)
+
+ # Show description if available
+ description = metadata.get("description", "")
+ if description:
+ st.caption(description)
+ else:
+ st.warning("No knowledge bases found. Create one below!")
+ st.session_state.selected_kb = None
+
+ # Create new KB
+ with st.expander("➕ Create New KB"):
+ new_kb_name = st.text_input("KB Name", key="new_kb_name", placeholder="my-project")
+
+ # KB Type Selector
+ kb_type_choices = get_kb_type_choices()
+ selected_type_display = st.selectbox(
+ "KB Type",
+ options=kb_type_choices,
+ key="kb_type_selector",
+ help="Select the type of knowledge base to create"
+ )
+
+ # Extract the actual KBType from the display string
+ # Format is "🤖 Agent OS Profile" -> need to map back to KBType
+ type_map = {choice: kb_type for kb_type, choice in zip(KBType, kb_type_choices)}
+ selected_kb_type = type_map[selected_type_display]
+
+ # Show type-specific info
+ type_info = get_kb_type_info(selected_kb_type)
+ st.caption(f"**{type_info.description}**")
+
+ # Optional description
+ kb_description = st.text_area(
+ "Description (optional)",
+ key="kb_description",
+ placeholder="Brief description of this knowledge base...",
+ height=80
+ )
+
+ if st.button("Create", type="primary"):
+ if new_kb_name:
+ if pg_manager.create_collection(
+ name=new_kb_name,
+ kb_type=selected_kb_type,
+ description=kb_description
+ ):
+ st.success(f"✅ Created {type_info.icon} **{new_kb_name}** ({type_info.name})")
+ st.rerun()
+ else:
+ st.error("Failed to create KB")
+ else:
+ st.error("Please enter a KB name")
+
+ st.divider()
+
+ # RAG Strategy Toggles
+ st.markdown("### 🎯 RAG Strategies")
+
+ st.session_state.rag_settings["hybrid"] = st.checkbox(
+ "🔀 Hybrid Search",
+ value=st.session_state.rag_settings["hybrid"],
+ help="**Hybrid Search**: Combines semantic vector search with BM25 keyword search for better recall. Uses reciprocal rank fusion to merge results. Best for queries with specific technical terms."
+ )
+
+ st.session_state.rag_settings["rerank"] = st.checkbox(
+ "🎯 Reranking",
+ value=st.session_state.rag_settings["rerank"],
+ help="**Reranking**: Re-scores retrieved chunks using a cross-encoder model (ms-marco-MiniLM) for higher precision. Keeps top 3 most relevant results. Improves answer quality but adds latency."
+ )
+
+ st.session_state.rag_settings["agentic"] = st.checkbox(
+ "🤖 Agentic RAG",
+ value=st.session_state.rag_settings["agentic"],
+ help="**Agentic RAG**: Breaks complex questions into sub-questions and answers them independently before synthesizing. Best for multi-part or analytical queries. Slower but more thorough."
+ )
+
+# Main content area (right column)
+with main_col:
+ # Main content tabs
+ tab1, tab2 = st.tabs(["📚 Knowledge Base", "💬 Chat"])
+
+ # Tab 1: Knowledge Base Management
+ with tab1:
+ st.markdown("## 📚 Knowledge Base Management")
+
+ if not st.session_state.selected_kb:
+ st.info("👈 Please select or create a knowledge base from the left panel")
+ else:
+ st.markdown(f"### Current KB: **{st.session_state.selected_kb}**")
+
+ st.markdown("---")
+
+ # Document Upload
+ doc_col1, doc_col2 = st.columns(2, gap="large")
+
+ with doc_col1:
+ st.markdown("#### 📤 Upload Documents")
+ st.caption("Choose files to upload to the knowledge base")
+
+ # Initialize upload counter in session state
+ if "upload_counter" not in st.session_state:
+ st.session_state.upload_counter = 0
+
+ # Use dynamic key to reset file uploader after upload
+ uploaded_files = st.file_uploader(
+ "Choose files",
+ accept_multiple_files=True,
+ type=[ext.replace(".", "") for ext in Config.SUPPORTED_FILE_TYPES],
+ label_visibility="collapsed",
+ key=f"file_uploader_{st.session_state.upload_counter}"
+ )
+
+ if uploaded_files and st.button("Upload Files", key="upload_files_btn", use_container_width=True):
+ try:
+ Config.ensure_upload_dir()
+ progress_bar = st.progress(0)
+ status_container = st.container()
+
+ for i, uploaded_file in enumerate(uploaded_files):
+ with status_container:
+ st.write(f"Processing: {uploaded_file.name}...")
+
+ # Save file
+ file_path = Path(Config.UPLOAD_DIR) / uploaded_file.name
+ with open(file_path, "wb") as f:
+ f.write(uploaded_file.getbuffer())
+
+ # Ingest file
+ result = ingest_file(
+ str(file_path),
+ st.session_state.selected_kb,
+ uploaded_file.name
+ )
+
+ with status_container:
+ if result["status"] == "success":
+ st.success(f"✅ {uploaded_file.name}: {result['chunks']} chunks")
+ else:
+ st.error(f"❌ {uploaded_file.name}: {result.get('error', 'Unknown error')}")
+
+ progress_bar.progress((i + 1) / len(uploaded_files))
+
+ with status_container:
+ st.success("🎉 Upload complete! Refreshing document list...")
+
+ # Increment counter to reset file uploader on next render
+ st.session_state.upload_counter += 1
+
+ # Wait a moment before rerun so user can see the success message
+ import time
+ time.sleep(1.5)
+ st.rerun()
+
+ except Exception as e:
+ st.error(f"❌ Upload failed: {str(e)}")
+ import traceback
+ st.code(traceback.format_exc())
+
+ with doc_col2:
+ st.markdown("#### 📁 Import Directory")
+ st.caption("Import all supported files from a directory")
+
+ st.info("💡 **Tip:** Mount your directory as a volume in docker-compose.yml first. Paths are relative to `/workspace` in the container.")
+
+ dir_path = st.text_input(
+ "Directory Path",
+ placeholder="/workspace/mounted_docs",
+ help="Path must exist inside the Docker container",
+ label_visibility="collapsed"
+ )
+
+ if st.button("Import Directory", key="import_dir_btn", use_container_width=True):
+ if not dir_path:
+ st.error("Please enter a directory path")
+ else:
+ with st.spinner("Importing files..."):
+ results = ingest_directory(dir_path, st.session_state.selected_kb)
+
+ if not results:
+ st.warning("No supported files found in directory")
+ elif results[0].get("error") and "not found" in results[0].get("error", ""):
+ st.error(f"Directory not found: {dir_path}")
+ else:
+ success_count = sum(1 for r in results if r.get("status") == "success")
+ error_count = len(results) - success_count
+
+ if success_count > 0:
+ st.success(f"✅ Imported {success_count} file(s)")
+ if error_count > 0:
+ st.warning(f"⚠️ {error_count} file(s) failed")
+
+ # Show first 5 results
+ for result in results[:5]:
+ if result.get("status") == "success":
+ st.caption(f"✅ {result.get('filename', 'Unknown')}")
+ else:
+ st.caption(f"❌ {result.get('filename', 'Unknown')}: {result.get('error', 'Unknown error')}")
+
+ if len(results) > 5:
+ st.caption(f"... and {len(results) - 5} more")
+
+ st.rerun()
+
+ # Agent OS Profile Import (only for Agent OS KBs)
+ kb_metadata = pg_manager.get_collection_metadata(st.session_state.selected_kb)
+ kb_type_str = kb_metadata.get("kb_type", "generic")
+
+ if kb_type_str == "agent-os":
+ st.markdown("---")
+ st.markdown("#### 🤖 Import Agent OS Profile")
+ st.caption("Import an Agent OS profile directory with standards, agents, workflows, and commands")
+
+ st.info("💡 **Tip:** Mount your Agent OS profile directory as a volume in docker-compose.yml. The path should point to the profile root (containing standards/, agents/, etc.)")
+
+ agent_os_path = st.text_input(
+ "Agent OS Profile Path",
+ placeholder="/workspace/my-agent-os-profile",
+ help="Path to Agent OS profile directory (must exist inside the Docker container)",
+ key="agent_os_path_input"
+ )
+
+ if st.button("Import Agent OS Profile", key="import_agent_os_btn", use_container_width=True):
+ if not agent_os_path:
+ st.error("Please enter an Agent OS profile path")
+ else:
+ with st.spinner("Parsing and ingesting Agent OS profile..."):
+ try:
+ agent_os_ingestion = AgentOSIngestion(pg_manager)
+ stats = agent_os_ingestion.ingest_profile(
+ kb_name=st.session_state.selected_kb,
+ profile_path=agent_os_path
+ )
+
+ if stats.get("success"):
+ st.success(f"✅ Imported {stats['total_documents']} Agent OS documents!")
+
+ # Show breakdown by type
+ st.markdown("**Documents by type:**")
+ for content_type, count in stats.get("documents_by_type", {}).items():
+ type_emoji = {
+ "standard": "📋",
+ "agent": "🤖",
+ "workflow": "🔄",
+ "command": "⚡",
+ "product": "🎯",
+ "spec": "📝"
+ }.get(content_type, "📄")
+ st.caption(f"{type_emoji} {content_type}: {count}")
+
+ st.rerun()
+ else:
+ st.error("❌ Agent OS import failed")
+ if stats.get("errors"):
+ for error in stats["errors"]:
+ st.caption(f"⚠️ {error}")
+
+ except Exception as e:
+ st.error(f"❌ Agent OS import failed: {str(e)}")
+ import traceback
+ st.code(traceback.format_exc())
+
+ st.divider()
+
+ # Agent OS Content Stats (only for Agent OS KBs)
+ if kb_type_str == "agent-os":
+ agent_os_ingestion = AgentOSIngestion(pg_manager)
+ agent_os_stats = agent_os_ingestion.get_profile_stats(st.session_state.selected_kb)
+
+ if agent_os_stats.get("total_documents", 0) > 0:
+ st.markdown("#### 🤖 Agent OS Content")
+
+ # Display stats in columns
+ stat_cols = st.columns(len(agent_os_stats.get("documents_by_type", {})) or 1)
+
+ type_info = {
+ "standard": {"emoji": "📋", "name": "Standards"},
+ "agent": {"emoji": "🤖", "name": "Agents"},
+ "workflow": {"emoji": "🔄", "name": "Workflows"},
+ "command": {"emoji": "⚡", "name": "Commands"},
+ "product": {"emoji": "🎯", "name": "Product"},
+ "spec": {"emoji": "📝", "name": "Specs"}
+ }
+
+ for idx, (content_type, count) in enumerate(agent_os_stats.get("documents_by_type", {}).items()):
+ info = type_info.get(content_type, {"emoji": "📄", "name": content_type.title()})
+ with stat_cols[idx]:
+ st.metric(
+ label=f"{info['emoji']} {info['name']}",
+ value=count
+ )
+
+ st.divider()
+
+ # Document Grid
+ st.markdown("#### 📄 Documents")
+
+ docs = get_documents_metadata(st.session_state.selected_kb)
+
+ if not docs:
+ st.info("No documents in this knowledge base. Upload files to get started!")
+ else:
+ # Display in 3-column grid
+ cols = st.columns(3)
+
+ for i, doc in enumerate(docs):
+ with cols[i % 3]:
+ # File icon based on type
+ icon_map = {
+ ".py": "🐍", ".js": "📜", ".jsx": "⚛️",
+ ".ts": "📘", ".tsx": "⚛️", ".md": "📄",
+ ".pdf": "📕", ".json": "📋", ".yaml": "⚙️"
+ }
+ icon = icon_map.get(doc["file_type"], "📄")
+
+ # Create card
+ tags_html = "".join([f'
{tag} ' for tag in doc["tags"]])
+
+ st.markdown(f"""
+
+
{icon}
+
{doc["filename"]}
+
{tags_html}
+
+ {doc["formatted_date"]}
+ {doc["chunk_count"]} chunks
+
+
+ """, unsafe_allow_html=True)
+
+ # Tab 2: Chat Interface
+ with tab2:
+ st.markdown("## 💬 Chat with Your Knowledge Base")
+
+ if not st.session_state.selected_kb:
+ st.info("👈 Please select a knowledge base from the left panel")
+ else:
+ # Display active strategies banner
+ active_strategies = []
+ if st.session_state.rag_settings["hybrid"]:
+ active_strategies.append("🔀 Hybrid Search")
+ if st.session_state.rag_settings["rerank"]:
+ active_strategies.append("🎯 Reranking")
+ if st.session_state.rag_settings["agentic"]:
+ active_strategies.append("🤖 Agentic RAG")
+
+ if active_strategies:
+ strategies_text = " + ".join(active_strategies)
+ st.markdown(f"""
+
+ 🎯 Active Retrieval Strategies: {strategies_text}
+
+ """, unsafe_allow_html=True)
+ else:
+ st.markdown(f"""
+
+ 📊 Mode: Standard Vector Search
+
+ """, unsafe_allow_html=True)
+
+ # Display chat history
+ for message in st.session_state.chat_history:
+ with st.chat_message(message["role"]):
+ st.markdown(message["content"])
+
+ if message["role"] == "assistant" and message.get("sources"):
+ with st.expander("📚 View Sources"):
+ for i, source in enumerate(message["sources"][:3], 1):
+ st.markdown(f"**Source {i}:**")
+ st.code(source["text"][:200] + "..." if len(source["text"]) > 200 else source["text"])
+ if source.get("metadata"):
+ st.caption(f"From: {source['metadata'].get('filename', 'Unknown')}")
+ if source.get("score"):
+ st.caption(f"Score: {source['score']:.3f}")
+ st.divider()
+
+ # Chat input
+ if prompt := st.chat_input("Ask a question about your knowledge base..."):
+ # Add user message
+ st.session_state.chat_history.append({
+ "role": "user",
+ "content": prompt
+ })
+
+ # Display user message
+ with st.chat_message("user"):
+ st.markdown(prompt)
+
+ # Generate response
+ with st.chat_message("assistant"):
+ with st.spinner("Thinking..."):
+ try:
+ rag_engine = RAGEngine(st.session_state.selected_kb)
+ result = rag_engine.query(
+ prompt,
+ use_hybrid=st.session_state.rag_settings["hybrid"],
+ use_rerank=st.session_state.rag_settings["rerank"],
+ use_agentic=st.session_state.rag_settings["agentic"]
+ )
+
+ answer = result.get("answer", "No answer generated")
+ sources = result.get("sources", [])
+
+ st.markdown(answer)
+
+ # Add to history
+ st.session_state.chat_history.append({
+ "role": "assistant",
+ "content": answer,
+ "sources": sources
+ })
+
+ # Display sources
+ if sources:
+ with st.expander("📚 View Sources"):
+ for i, source in enumerate(sources[:3], 1):
+ st.markdown(f"**Source {i}:**")
+ st.code(source["text"][:200] + "..." if len(source["text"]) > 200 else source["text"])
+ if source.get("metadata"):
+ st.caption(f"From: {source['metadata'].get('filename', 'Unknown')}")
+ if source.get("score"):
+ st.caption(f"Score: {source['score']:.3f}")
+ st.divider()
+
+ except Exception as e:
+ error_msg = f"Error: {str(e)}"
+ st.error(error_msg)
+ st.session_state.chat_history.append({
+ "role": "assistant",
+ "content": error_msg
+ })
+
+ # Clear chat button
+ if st.session_state.chat_history and st.button("🗑️ Clear Chat"):
+ st.session_state.chat_history = []
+ st.rerun()
+
diff --git a/design-guide.md b/design-guide.md
new file mode 100644
index 0000000..51cf163
--- /dev/null
+++ b/design-guide.md
@@ -0,0 +1,62 @@
+# Code-Forge Design Guide: Enhanced High-Contrast Palette
+
+## Concept
+A dynamic, modern, and high-tech aesthetic, emphasizing extreme clarity and energetic innovation. The colors evoke digital craftsmanship and cutting-edge technology, with a deliberate focus on high contrast to ensure visual impact and accessibility.
+
+## Primary Color Palette
+
+Here are the core colors that define the Code-Forge brand, designed for maximum brightness and contrast:
+
+1. ### **Deep Night (Background)**
+ * **Hex:** `#0A0E1A`
+ * **RGB:** `(10, 14, 26)`
+ * **Usage:** The foundational dark background color. This deep, almost black, blue-grey provides a dramatic canvas, making the vibrant foreground elements pop with intensity. Use for primary backgrounds, dark mode interfaces, and large informational sections.
+
+2. ### **Electric Teal (Primary Accent)**
+ * **Hex:** `#00FFFF` (Pure Cyan)
+ * **RGB:** `(0, 255, 255)`
+ * **Usage:** The most prominent accent color. This intensely bright and pure cyan is used for key interactive elements, primary iconography, active states, glowing outlines, circuit patterns, and significant graphical components. Its high luminescence creates a striking contrast against "Deep Night."
+
+3. ### **Blaze Orange (Secondary Accent)**
+ * **Hex:** `#FF8C00` (Dark Orange, but used at full saturation for brilliance)
+ * **RGB:** `(255, 140, 0)`
+ * **Usage:** A vibrant, saturated orange that provides a warm and energetic counterpoint to "Electric Teal." Use for call-to-action buttons, warning indicators, secondary highlights, "spark" effects, important data points, and to draw immediate attention.
+
+4. ### **Pure White (Text & UI)**
+ * **Hex:** `#FFFFFF`
+ * **RGB:** `(255, 255, 255)`
+ * **Usage:** The default color for primary text, headings, essential labels, and clean UI elements. Offers the highest possible readability and contrast against "Deep Night."
+
+## Secondary/Support Palette (Optional but Recommended)
+
+These colors can be used for supplementary elements, gradients, or to add subtle depth without detracting from the primary palette's vibrancy.
+
+1. ### **Cool Blue (Subtle Glow/Gradient)**
+ * **Hex:** `#4D94FF`
+ * **RGB:** `(77, 148, 255)`
+ * **Usage:** For background gradients, subtle glowing effects, or to create depth behind "Electric Teal" elements. Use sparingly to enhance rather than compete with the primary accents.
+
+2. ### **Light Grey (Subtle Text/Dividers)**
+ * **Hex:** `#C0C0C0`
+ * **RGB:** `(192, 192, 192)`
+ * **Usage:** For less critical secondary text, disabled states, subtle dividers, borders, or backgrounds for minor information sections. Provides a softer, yet still clear, contrast to "Deep Night."
+
+## Accessibility & Contrast Ratios
+
+The primary palette is engineered for optimal contrast to ensure excellent readability and accessibility.
+
+* **Deep Night** vs. **Electric Teal**: Excellent contrast (WCAG AAA compliant).
+* **Deep Night** vs. **Blaze Orange**: Excellent contrast (WCAG AAA compliant).
+* **Deep Night** vs. **Pure White**: Maximum contrast (WCAG AAA compliant), ideal for primary text.
+
+## Usage Guidelines
+
+* **Backgrounds:** Exclusively use "Deep Night" as the primary canvas to ensure maximum impact of the accent colors.
+* **Primary Elements & Interactivity:** "Electric Teal" should highlight key interactive components, active states, and core branding visuals.
+* **Emphasis & Alerts:** "Blaze Orange" is reserved for drawing immediate attention, warnings, confirmations, or energetic visual cues.
+* **Text Hierarchy:** "Pure White" for main content and headings. "Light Grey" for supplementary information or less emphasized text.
+* **Glows & Effects:** Embrace the vibrancy! Utilize subtle, expansive glows and light trails in "Electric Teal" and "Blaze Orange" to amplify the high-tech, energetic feel, similar to neon signage.
+* **Gradients:** When used, gradients should smoothly transition between "Electric Teal" and "Cool Blue," or "Blaze Orange" for dramatic highlights, always respecting the high contrast against the "Deep Night" background.
+* **Iconography:** Icons should primarily be "Electric Teal" or "Pure White" against "Deep Night," with "Blaze Orange" for special status icons.
+
+---
\ No newline at end of file
diff --git a/docker-compose.yml b/docker-compose.yml
index 16811da..559fc20 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -7,7 +7,7 @@ services:
ports:
- "11434:11434"
volumes:
- - ollama_models:/root/.ollama
+ - ./data/ollama:/root/.ollama
environment:
- OLLAMA_NUM_PARALLEL=1
- OLLAMA_MAX_LOADED_MODELS=1
@@ -16,27 +16,13 @@ services:
- code-forge-network
restart: unless-stopped
- chromadb:
- image: chromadb/chroma:latest
- container_name: code-forge-chromadb
- ports:
- - "8000:8000"
- volumes:
- - chroma_data:/chroma/chroma
- environment:
- - IS_PERSISTENT=TRUE
- - ANONYMIZED_TELEMETRY=FALSE
- networks:
- - code-forge-network
- restart: unless-stopped
-
app:
build:
context: .
dockerfile: Dockerfile
container_name: code-forge-app
ports:
- - "8501:8501" # Streamlit UI
+ - "8501:8501" # Streamlit UI (Legacy)
- "8051:8051" # MCP Server
volumes:
- ./app:/workspace/app
@@ -46,15 +32,36 @@ services:
# - /path/to/your/docs:/workspace/mounted_docs:ro
environment:
- OLLAMA_HOST=http://ollama:11434
- - CHROMA_HOST=chromadb
- - CHROMA_PORT=8000
+ - POSTGRES_HOST=host.docker.internal
+ - POSTGRES_PORT=5432
+ - POSTGRES_DB=codeforge
+ - POSTGRES_USER=${USER}
+ - POSTGRES_PASSWORD=
+ - DATABASE_URL=postgresql://${USER}@host.docker.internal:5432/codeforge
- MCP_SERVER_HOST=0.0.0.0
- MCP_SERVER_PORT=8051
networks:
- code-forge-network
depends_on:
- ollama
- - chromadb
+ restart: unless-stopped
+
+ frontend:
+ image: node:20-alpine
+ container_name: code-forge-frontend
+ working_dir: /app
+ ports:
+ - "5173:5173" # Vite dev server
+ volumes:
+ - ./frontend:/app
+ - /app/node_modules # Prevent node_modules from being overwritten
+ command: sh -c "npm install && npm run dev -- --host 0.0.0.0"
+ environment:
+ - VITE_API_URL=http://localhost:8051
+ networks:
+ - code-forge-network
+ depends_on:
+ - app
restart: unless-stopped
networks:
@@ -62,7 +69,5 @@ networks:
driver: bridge
volumes:
- ollama_models:
- chroma_data:
uploads:
diff --git a/frontend/.gitignore b/frontend/.gitignore
new file mode 100644
index 0000000..a547bf3
--- /dev/null
+++ b/frontend/.gitignore
@@ -0,0 +1,24 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?
diff --git a/frontend/README.md b/frontend/README.md
new file mode 100644
index 0000000..d2e7761
--- /dev/null
+++ b/frontend/README.md
@@ -0,0 +1,73 @@
+# React + TypeScript + Vite
+
+This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.
+
+Currently, two official plugins are available:
+
+- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Babel](https://babeljs.io/) (or [oxc](https://oxc.rs) when used in [rolldown-vite](https://vite.dev/guide/rolldown)) for Fast Refresh
+- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/) for Fast Refresh
+
+## React Compiler
+
+The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see [this documentation](https://react.dev/learn/react-compiler/installation).
+
+## Expanding the ESLint configuration
+
+If you are developing a production application, we recommend updating the configuration to enable type-aware lint rules:
+
+```js
+export default defineConfig([
+ globalIgnores(['dist']),
+ {
+ files: ['**/*.{ts,tsx}'],
+ extends: [
+ // Other configs...
+
+ // Remove tseslint.configs.recommended and replace with this
+ tseslint.configs.recommendedTypeChecked,
+ // Alternatively, use this for stricter rules
+ tseslint.configs.strictTypeChecked,
+ // Optionally, add this for stylistic rules
+ tseslint.configs.stylisticTypeChecked,
+
+ // Other configs...
+ ],
+ languageOptions: {
+ parserOptions: {
+ project: ['./tsconfig.node.json', './tsconfig.app.json'],
+ tsconfigRootDir: import.meta.dirname,
+ },
+ // other options...
+ },
+ },
+])
+```
+
+You can also install [eslint-plugin-react-x](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-x) and [eslint-plugin-react-dom](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-dom) for React-specific lint rules:
+
+```js
+// eslint.config.js
+import reactX from 'eslint-plugin-react-x'
+import reactDom from 'eslint-plugin-react-dom'
+
+export default defineConfig([
+ globalIgnores(['dist']),
+ {
+ files: ['**/*.{ts,tsx}'],
+ extends: [
+ // Other configs...
+ // Enable lint rules for React
+ reactX.configs['recommended-typescript'],
+ // Enable lint rules for React DOM
+ reactDom.configs.recommended,
+ ],
+ languageOptions: {
+ parserOptions: {
+ project: ['./tsconfig.node.json', './tsconfig.app.json'],
+ tsconfigRootDir: import.meta.dirname,
+ },
+ // other options...
+ },
+ },
+])
+```
diff --git a/frontend/eslint.config.js b/frontend/eslint.config.js
new file mode 100644
index 0000000..b19330b
--- /dev/null
+++ b/frontend/eslint.config.js
@@ -0,0 +1,23 @@
+import js from '@eslint/js'
+import globals from 'globals'
+import reactHooks from 'eslint-plugin-react-hooks'
+import reactRefresh from 'eslint-plugin-react-refresh'
+import tseslint from 'typescript-eslint'
+import { defineConfig, globalIgnores } from 'eslint/config'
+
+export default defineConfig([
+ globalIgnores(['dist']),
+ {
+ files: ['**/*.{ts,tsx}'],
+ extends: [
+ js.configs.recommended,
+ tseslint.configs.recommended,
+ reactHooks.configs['recommended-latest'],
+ reactRefresh.configs.vite,
+ ],
+ languageOptions: {
+ ecmaVersion: 2020,
+ globals: globals.browser,
+ },
+ },
+])
diff --git a/frontend/index.html b/frontend/index.html
new file mode 100644
index 0000000..e01d1be
--- /dev/null
+++ b/frontend/index.html
@@ -0,0 +1,13 @@
+
+
+
+
+
+
+
Code-Forge | Localized Multi-KB RAG System
+
+
+
+
+
+
diff --git a/frontend/package-lock.json b/frontend/package-lock.json
new file mode 100644
index 0000000..58c0d2c
--- /dev/null
+++ b/frontend/package-lock.json
@@ -0,0 +1,6227 @@
+{
+ "name": "frontend",
+ "version": "0.0.0",
+ "lockfileVersion": 3,
+ "requires": true,
+ "packages": {
+ "": {
+ "name": "frontend",
+ "version": "0.0.0",
+ "dependencies": {
+ "@tanstack/react-query": "^5.90.5",
+ "@types/react-syntax-highlighter": "^15.5.13",
+ "axios": "^1.12.2",
+ "framer-motion": "^12.23.24",
+ "lucide-react": "^0.546.0",
+ "react": "^19.1.1",
+ "react-dom": "^19.1.1",
+ "react-markdown": "^10.1.0",
+ "react-router-dom": "^7.9.4",
+ "react-syntax-highlighter": "^16.0.0"
+ },
+ "devDependencies": {
+ "@eslint/js": "^9.36.0",
+ "@tailwindcss/typography": "^0.5.19",
+ "@types/node": "^24.6.0",
+ "@types/react": "^19.1.16",
+ "@types/react-dom": "^19.1.9",
+ "@vitejs/plugin-react": "^5.0.4",
+ "autoprefixer": "^10.4.21",
+ "eslint": "^9.36.0",
+ "eslint-plugin-react-hooks": "^5.2.0",
+ "eslint-plugin-react-refresh": "^0.4.22",
+ "globals": "^16.4.0",
+ "postcss": "^8.5.6",
+ "tailwindcss": "^3.4.18",
+ "typescript": "~5.9.3",
+ "typescript-eslint": "^8.45.0",
+ "vite": "^7.1.7"
+ }
+ },
+ "node_modules/@alloc/quick-lru": {
+ "version": "5.2.0",
+ "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz",
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+ "integrity": "sha512-4Dj6M28JB+oAH8kFkTLUo+a2jwOFkuqb3yucU0CANcRRUbxS0cP0nZYCGjcc3BNXwRIsUVmDGgzawme7zvJHvg==",
+ "dev": true,
+ "license": "MIT",
+ "engines": {
+ "node": ">=12"
+ },
+ "funding": {
+ "url": "https://github.com/chalk/ansi-styles?sponsor=1"
+ }
+ },
+ "node_modules/yallist": {
+ "version": "3.1.1",
+ "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz",
+ "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==",
+ "dev": true,
+ "license": "ISC"
+ },
+ "node_modules/yocto-queue": {
+ "version": "0.1.0",
+ "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz",
+ "integrity": "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==",
+ "dev": true,
+ "license": "MIT",
+ "engines": {
+ "node": ">=10"
+ },
+ "funding": {
+ "url": "https://github.com/sponsors/sindresorhus"
+ }
+ },
+ "node_modules/zwitch": {
+ "version": "2.0.4",
+ "resolved": "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz",
+ "integrity": "sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==",
+ "license": "MIT",
+ "funding": {
+ "type": "github",
+ "url": "https://github.com/sponsors/wooorm"
+ }
+ }
+ }
+}
diff --git a/frontend/package.json b/frontend/package.json
new file mode 100644
index 0000000..6db0e0e
--- /dev/null
+++ b/frontend/package.json
@@ -0,0 +1,42 @@
+{
+ "name": "frontend",
+ "private": true,
+ "version": "0.0.0",
+ "type": "module",
+ "scripts": {
+ "dev": "vite",
+ "build": "tsc -b && vite build",
+ "lint": "eslint .",
+ "preview": "vite preview"
+ },
+ "dependencies": {
+ "@tanstack/react-query": "^5.90.5",
+ "@types/react-syntax-highlighter": "^15.5.13",
+ "axios": "^1.12.2",
+ "framer-motion": "^12.23.24",
+ "lucide-react": "^0.546.0",
+ "react": "^19.1.1",
+ "react-dom": "^19.1.1",
+ "react-markdown": "^10.1.0",
+ "react-router-dom": "^7.9.4",
+ "react-syntax-highlighter": "^16.0.0"
+ },
+ "devDependencies": {
+ "@eslint/js": "^9.36.0",
+ "@tailwindcss/typography": "^0.5.19",
+ "@types/node": "^24.6.0",
+ "@types/react": "^19.1.16",
+ "@types/react-dom": "^19.1.9",
+ "@vitejs/plugin-react": "^5.0.4",
+ "autoprefixer": "^10.4.21",
+ "eslint": "^9.36.0",
+ "eslint-plugin-react-hooks": "^5.2.0",
+ "eslint-plugin-react-refresh": "^0.4.22",
+ "globals": "^16.4.0",
+ "postcss": "^8.5.6",
+ "tailwindcss": "^3.4.18",
+ "typescript": "~5.9.3",
+ "typescript-eslint": "^8.45.0",
+ "vite": "^7.1.7"
+ }
+}
diff --git a/frontend/postcss.config.js b/frontend/postcss.config.js
new file mode 100644
index 0000000..b4a6220
--- /dev/null
+++ b/frontend/postcss.config.js
@@ -0,0 +1,7 @@
+export default {
+ plugins: {
+ tailwindcss: {},
+ autoprefixer: {},
+ },
+}
+
diff --git a/frontend/public/assets/hero.png b/frontend/public/assets/hero.png
new file mode 100644
index 0000000..4b3e45b
Binary files /dev/null and b/frontend/public/assets/hero.png differ
diff --git a/frontend/public/assets/logo.png b/frontend/public/assets/logo.png
new file mode 100644
index 0000000..44869d8
Binary files /dev/null and b/frontend/public/assets/logo.png differ
diff --git a/frontend/public/vite.svg b/frontend/public/vite.svg
new file mode 100644
index 0000000..e7b8dfb
--- /dev/null
+++ b/frontend/public/vite.svg
@@ -0,0 +1 @@
+
\ No newline at end of file
diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx
new file mode 100644
index 0000000..9dc3e1d
--- /dev/null
+++ b/frontend/src/App.tsx
@@ -0,0 +1,29 @@
+import { BrowserRouter, Routes, Route, Navigate } from 'react-router-dom';
+import { QueryClient, QueryClientProvider } from '@tanstack/react-query';
+import Welcome from './pages/Welcome';
+import MainApp from './pages/MainApp';
+
+const queryClient = new QueryClient({
+ defaultOptions: {
+ queries: {
+ refetchOnWindowFocus: false,
+ retry: 1,
+ },
+ },
+});
+
+function App() {
+ return (
+
+
+
+ } />
+ } />
+ } />
+
+
+
+ );
+}
+
+export default App;
diff --git a/frontend/src/assets/react.svg b/frontend/src/assets/react.svg
new file mode 100644
index 0000000..6c87de9
--- /dev/null
+++ b/frontend/src/assets/react.svg
@@ -0,0 +1 @@
+
\ No newline at end of file
diff --git a/frontend/src/components/ChatInterface.tsx b/frontend/src/components/ChatInterface.tsx
new file mode 100644
index 0000000..94e1dfd
--- /dev/null
+++ b/frontend/src/components/ChatInterface.tsx
@@ -0,0 +1,225 @@
+import { useState, useRef, useEffect } from 'react';
+import { motion, AnimatePresence } from 'framer-motion';
+import { Send, Bot, User, Loader2, Copy, CheckCircle } from 'lucide-react';
+import { useMutation } from '@tanstack/react-query';
+import { chat, type ChatResponse } from '../lib/api';
+import ReactMarkdown from 'react-markdown';
+
+interface ChatInterfaceProps {
+ kbName: string;
+ useHybrid: boolean;
+ useRerank: boolean;
+ useAgentic: boolean;
+}
+
+interface Message {
+ role: 'user' | 'assistant';
+ content: string;
+ sources?: any[];
+}
+
+export default function ChatInterface({ kbName, useHybrid, useRerank, useAgentic }: ChatInterfaceProps) {
+ const [messages, setMessages] = useState
([]);
+ const [input, setInput] = useState('');
+ const [copiedIndex, setCopiedIndex] = useState(null);
+ const messagesEndRef = useRef(null);
+
+ const scrollToBottom = () => {
+ messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' });
+ };
+
+ useEffect(() => {
+ scrollToBottom();
+ }, [messages]);
+
+ const chatMutation = useMutation({
+ mutationFn: (query: string) => chat(kbName, query, useHybrid, useRerank, useAgentic),
+ onSuccess: (data: ChatResponse) => {
+ setMessages((prev) => [
+ ...prev,
+ {
+ role: 'assistant',
+ content: data.answer || data.error || 'No response',
+ sources: data.sources,
+ },
+ ]);
+ },
+ });
+
+ const handleSend = () => {
+ if (!input.trim() || chatMutation.isPending) return;
+
+ const userMessage: Message = { role: 'user', content: input };
+ setMessages((prev) => [...prev, userMessage]);
+ setInput('');
+ chatMutation.mutate(input);
+ };
+
+ const handleKeyPress = (e: React.KeyboardEvent) => {
+ if (e.key === 'Enter' && !e.shiftKey) {
+ e.preventDefault();
+ handleSend();
+ }
+ };
+
+ const copyToClipboard = (text: string, index: number) => {
+ navigator.clipboard.writeText(text);
+ setCopiedIndex(index);
+ setTimeout(() => setCopiedIndex(null), 2000);
+ };
+
+ return (
+
+ {/* Messages Area */}
+
+ {messages.length === 0 ? (
+
+
+
+
Start a Conversation
+
Ask anything about your knowledge base
+
+
+ Active Settings:
+
+
+ {useHybrid && (
+
+ Hybrid Search
+
+ )}
+ {useRerank && (
+
+ Reranking
+
+ )}
+ {useAgentic && (
+
+ Agentic RAG
+
+ )}
+ {!useHybrid && !useRerank && !useAgentic && (
+
+ Basic Vector Search
+
+ )}
+
+
+
+
+ ) : (
+
+ {messages.map((message, index) => (
+
+ {message.role === 'assistant' && (
+
+
+
+ )}
+
+
+
+ {message.role === 'assistant' ? (
+
{message.content}
+ ) : (
+
{message.content}
+ )}
+
+
+ {message.role === 'assistant' && (
+
+ copyToClipboard(message.content, index)}
+ className="text-xs px-3 py-1 rounded bg-electric-teal/20 hover:bg-electric-teal/30 transition-colors flex items-center gap-1"
+ >
+ {copiedIndex === index ? (
+ <>
+
+ Copied!
+ >
+ ) : (
+ <>
+
+ Copy
+ >
+ )}
+
+ {message.sources && message.sources.length > 0 && (
+
+ {message.sources.length} source{message.sources.length > 1 ? 's' : ''}
+
+ )}
+
+ )}
+
+
+ {message.role === 'user' && (
+
+
+
+ )}
+
+ ))}
+
+ )}
+
+ {chatMutation.isPending && (
+
+
+
+
+
+
+
+
+ )}
+
+
+
+
+ {/* Input Area */}
+
+
+ );
+}
diff --git a/frontend/src/components/HelpDocs.tsx b/frontend/src/components/HelpDocs.tsx
new file mode 100644
index 0000000..9aeecb6
--- /dev/null
+++ b/frontend/src/components/HelpDocs.tsx
@@ -0,0 +1,262 @@
+import { motion } from 'framer-motion';
+import { Database, Upload, MessageSquare, Settings, Zap, Code, FileText, BookOpen } from 'lucide-react';
+
+export default function HelpDocs() {
+ return (
+
+ {/* Header */}
+
+ Code-Forge Documentation
+ Everything you need to know about using Code-Forge
+
+
+ {/* Quick Start */}
+
+
+
+ Quick Start
+
+
+
+
1
+
+
Create a Knowledge Base
+
Click the + button in the sidebar to create a new KB. Choose the appropriate type for your content.
+
+
+
+
2
+
+
Upload Documents
+
Go to KB Management tab and drag & drop files or click to browse. Supports text, markdown, PDF, code files, and more.
+
+
+
+
3
+
+
Start Chatting
+
Switch to the Chat tab and ask questions about your documents. The AI will retrieve relevant context and provide answers.
+
+
+
+
+
+ {/* KB Types */}
+
+
+
+ Knowledge Base Types
+
+
+
+
+
+
Generic
+
+
General-purpose knowledge base for mixed content types.
+
Use for: Random notes, mixed documents, general reference material
+
+
+
+
+
+
Code
+
+
Optimized for source code with better chunking and structure preservation.
+
Use for: Codebases, libraries, API implementations, code examples
+
+
+
+
+
+
Documentation
+
+
Optimized for technical documentation with enhanced markdown processing.
+
Use for: MCP docs, API docs, tutorials, guides, technical specs
+
+
+
+
+
+
Agent OS
+
+
Special type for Agent OS YAML profiles with structured metadata extraction.
+
Use for: Agent OS configuration files only
+
+
+
+
+ {/* RAG Settings */}
+
+
+
+ RAG Settings Explained
+
+
+
+
Hybrid Search (Vector + BM25)
+
Combines semantic vector search with keyword-based BM25 search for better retrieval.
+
When to use: When you need both semantic understanding AND exact keyword matching. Great for technical queries.
+
+
+
+
Reranking
+
Re-scores retrieved documents using a cross-encoder model for higher accuracy.
+
When to use: When you need the most relevant results and can afford slightly slower queries. Improves precision.
+
+
+
+
Agentic RAG
+
Uses multi-step reasoning with an LLM agent to iteratively refine queries and answers.
+
When to use: For complex questions requiring multiple retrieval steps or reasoning. Slower but more intelligent.
+
+
+
+
💡 Pro Tip: Start with basic vector search, then enable Hybrid + Rerank for better results. Use Agentic RAG for complex research questions.
+
+
+
+
+ {/* File Upload */}
+
+
+
+ Supported File Types
+
+
+
.txt
+
.md
+
.pdf
+
.py
+
.js
+
.ts
+
.tsx
+
.jsx
+
.json
+
.yaml
+
.html
+
.css
+
.cpp
+
.java
+
.go
+
.rs
+
+ And many more! Code-Forge automatically extracts text from PDFs and processes markdown with enhanced structure preservation.
+
+
+ {/* MCP Integration */}
+
+
+
+ MCP Integration
+
+ Code-Forge exposes 12 MCP tools for AI agents to interact with your knowledge bases:
+
+
+ list_knowledge_bases
+
+
+ create_knowledge_base
+
+
+ delete_knowledge_base
+
+
+ ingest_document
+
+
+ ingest_directory
+
+
+ query_knowledge_base
+
+
+ get_kb_stats
+
+
+ get_standards
+
+
+
+
+
+
MCP Endpoint: http://localhost:8051/mcp
+
+
+
+
+
+ Add to Claude Desktop
+
+
+
+
Option 1: Using CLI (Recommended)
+
Run this command in your terminal:
+
+ npx @modelcontextprotocol/inspector http://localhost:8051/mcp
+
+
Or add directly to Claude Desktop:
+
+ claude mcp add code-forge http://localhost:8051/mcp
+
+
+
+
+
Option 2: Manual Configuration
+
Edit your Claude Desktop config file:
+
+
+
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
+
Windows: %APPDATA%\Claude\claude_desktop_config.json
+
+
+
+
+{`{
+ "mcpServers": {
+ "code-forge": {
+ "url": "http://localhost:8051/mcp"
+ }
+ }
+}`}
+
+
+
+
+
+ Note: Restart Claude Desktop after adding the configuration. The MCP server must be running (docker-compose up).
+
+
+
+
+
+ );
+}
diff --git a/frontend/src/components/KBManagement.tsx b/frontend/src/components/KBManagement.tsx
new file mode 100644
index 0000000..fce5ebf
--- /dev/null
+++ b/frontend/src/components/KBManagement.tsx
@@ -0,0 +1,261 @@
+import { useState, useRef } from 'react';
+import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query';
+import { motion } from 'framer-motion';
+import { FileText, BarChart3, Clock, Database, Upload, CheckCircle, XCircle } from 'lucide-react';
+import { getKBStats, listDocuments, uploadDocument, type KBStats } from '../lib/api';
+
+interface KBManagementProps {
+ kbName: string;
+}
+
+export default function KBManagement({ kbName }: KBManagementProps) {
+ const [selectedFiles, setSelectedFiles] = useState([]);
+ const [uploadStatus, setUploadStatus] = useState<'idle' | 'uploading' | 'success' | 'error'>('idle');
+ const [uploadMessage, setUploadMessage] = useState('');
+ const fileInputRef = useRef(null);
+ const queryClient = useQueryClient();
+
+ // Fetch KB stats
+ const { data: stats, isLoading: statsLoading } = useQuery({
+ queryKey: ['kb-stats', kbName],
+ queryFn: () => getKBStats(kbName),
+ enabled: !!kbName,
+ });
+
+ // Fetch documents
+ const { data: documents = [], isLoading: docsLoading } = useQuery({
+ queryKey: ['kb-documents', kbName],
+ queryFn: () => listDocuments(kbName),
+ enabled: !!kbName,
+ });
+
+ // Upload mutation
+ const uploadMutation = useMutation({
+ mutationFn: (file: File) => uploadDocument(kbName, file),
+ onSuccess: (data) => {
+ setUploadStatus('success');
+ setUploadMessage(`✅ Uploaded ${data.filename} (${data.chunks} chunks)`);
+ queryClient.invalidateQueries({ queryKey: ['kb-stats', kbName] });
+ queryClient.invalidateQueries({ queryKey: ['kb-documents', kbName] });
+ setTimeout(() => {
+ setUploadStatus('idle');
+ setSelectedFiles([]);
+ }, 3000);
+ },
+ onError: (error: any) => {
+ setUploadStatus('error');
+ setUploadMessage(`❌ Upload failed: ${error.response?.data?.detail || error.message}`);
+ setTimeout(() => setUploadStatus('idle'), 5000);
+ },
+ });
+
+ const handleFileSelect = (e: React.ChangeEvent) => {
+ if (e.target.files) {
+ setSelectedFiles(Array.from(e.target.files));
+ }
+ };
+
+ const handleUpload = async () => {
+ if (selectedFiles.length === 0) return;
+
+ setUploadStatus('uploading');
+ for (const file of selectedFiles) {
+ await uploadMutation.mutateAsync(file);
+ }
+ };
+
+ const handleDrop = (e: React.DragEvent) => {
+ e.preventDefault();
+ if (e.dataTransfer.files) {
+ setSelectedFiles(Array.from(e.dataTransfer.files));
+ }
+ };
+
+ const handleDragOver = (e: React.DragEvent) => {
+ e.preventDefault();
+ };
+
+ return (
+
+ {/* Stats Cards */}
+
+
+
+
+
+
+
+
+ {statsLoading ? '...' : stats?.total_documents || 0}
+
+
Documents
+
+
+
+
+
+
+
+
+
+
+
+ {statsLoading ? '...' : stats?.total_chunks || 0}
+
+
Chunks
+
+
+
+
+
+
+
+
+
+
+
Last Updated
+
+ {statsLoading
+ ? '...'
+ : stats?.last_updated
+ ? new Date(stats.last_updated).toLocaleDateString()
+ : 'Never'}
+
+
+
+
+
+
+ {/* Document Upload Section */}
+
+
+
+ Upload Documents
+
+
+ fileInputRef.current?.click()}
+ className="border-2 border-dashed border-electric-teal/30 rounded-lg p-12 text-center hover:border-electric-teal/60 transition-colors cursor-pointer"
+ >
+
+
+ {selectedFiles.length === 0 ? (
+ <>
+
+
Drag & drop files here, or click to browse
+
Supports: .txt, .md, .pdf, .py, .js, .ts, and more
+ >
+ ) : (
+ <>
+
+
{selectedFiles.length} file(s) selected
+
+ {selectedFiles.map((file, idx) => (
+
{file.name}
+ ))}
+
+ >
+ )}
+
+
+ {selectedFiles.length > 0 && (
+
+
+ {uploadStatus === 'uploading' ? 'Uploading...' : 'Upload Files'}
+
+ setSelectedFiles([])}
+ className="btn-secondary"
+ >
+ Clear
+
+
+ )}
+
+ {uploadStatus !== 'idle' && (
+
+
{uploadMessage || 'Processing...'}
+
+ )}
+
+
+ {/* Documents List */}
+
+
+
+ Documents ({documents.length})
+
+
+ {docsLoading ? (
+ Loading documents...
+ ) : documents.length === 0 ? (
+
+ No documents yet. Upload some to get started!
+
+ ) : (
+
+ {documents.map((doc: any, idx: number) => (
+
+
+
+
+ {doc.metadata?.source || `Document ${idx + 1}`}
+
+
+ {doc.content?.substring(0, 150)}...
+
+
+
+
+
+ ))}
+
+ )}
+
+
+ );
+}
diff --git a/frontend/src/index.css b/frontend/src/index.css
new file mode 100644
index 0000000..942b18b
--- /dev/null
+++ b/frontend/src/index.css
@@ -0,0 +1,97 @@
+@import url('https://fonts.googleapis.com/css2?family=JetBrains+Mono:wght@400;500;600;700;800;900&display=swap');
+
+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+
+@layer base {
+ body {
+ @apply bg-deep-night text-white font-mono;
+ margin: 0;
+ min-height: 100vh;
+ }
+}
+
+@layer components {
+ .gradient-text {
+ background: linear-gradient(135deg, #00FFFF, #4D94FF, #FF8C00);
+ -webkit-background-clip: text;
+ -webkit-text-fill-color: transparent;
+ background-clip: text;
+ }
+
+ .glow-teal {
+ box-shadow: 0 0 20px rgba(0, 255, 255, 0.5);
+ }
+
+ .glow-teal-strong {
+ box-shadow: 0 0 40px rgba(0, 255, 255, 0.8);
+ }
+
+ .glow-orange {
+ box-shadow: 0 0 20px rgba(255, 140, 0, 0.5);
+ }
+
+ .glow-orange-strong {
+ box-shadow: 0 0 40px rgba(255, 140, 0, 0.8);
+ }
+
+ .card {
+ @apply bg-gradient-to-br from-deep-night to-cool-blue/10 rounded-2xl border border-electric-teal/30 p-6 transition-all duration-300;
+ }
+
+ .card:hover {
+ @apply border-electric-teal glow-teal transform -translate-y-1;
+ }
+
+ .btn {
+ @apply px-6 py-3 rounded-lg font-semibold transition-all duration-300 transform hover:scale-105;
+ }
+
+ .btn-primary {
+ @apply btn bg-gradient-to-r from-electric-teal to-cool-blue text-deep-night glow-teal;
+ }
+
+ .btn-primary:hover {
+ @apply glow-teal-strong;
+ }
+
+ .btn-secondary {
+ @apply btn bg-gradient-to-r from-blaze-orange to-blaze-orange/80 text-white glow-orange;
+ }
+
+ .btn-secondary:hover {
+ @apply glow-orange-strong;
+ }
+
+ .input {
+ @apply bg-deep-night border border-electric-teal/30 rounded-lg px-4 py-2 text-white placeholder-light-grey focus:outline-none focus:border-electric-teal focus:glow-teal transition-all duration-300;
+ }
+
+ ::-webkit-scrollbar {
+ width: 10px;
+ }
+
+ ::-webkit-scrollbar-track {
+ background: #0A0E1A;
+ }
+
+ ::-webkit-scrollbar-thumb {
+ background: #00FFFF;
+ border-radius: 5px;
+ }
+
+ ::-webkit-scrollbar-thumb:hover {
+ background: #4D94FF;
+ }
+}
+
+@layer utilities {
+ .text-shadow-glow {
+ text-shadow: 0 0 30px rgba(0, 255, 255, 0.5);
+ }
+
+ .text-shadow-glow-orange {
+ text-shadow: 0 0 30px rgba(255, 140, 0, 0.5);
+ }
+}
diff --git a/frontend/src/main.tsx b/frontend/src/main.tsx
new file mode 100644
index 0000000..bef5202
--- /dev/null
+++ b/frontend/src/main.tsx
@@ -0,0 +1,10 @@
+import { StrictMode } from 'react'
+import { createRoot } from 'react-dom/client'
+import './index.css'
+import App from './App.tsx'
+
+createRoot(document.getElementById('root')!).render(
+
+
+ ,
+)
diff --git a/frontend/src/pages/MainApp.tsx b/frontend/src/pages/MainApp.tsx
new file mode 100644
index 0000000..fc3e95a
--- /dev/null
+++ b/frontend/src/pages/MainApp.tsx
@@ -0,0 +1,285 @@
+import { useState } from 'react';
+import { Link } from 'react-router-dom';
+import { Home, Settings, Database, MessageSquare, Plus, Trash2, HelpCircle } from 'lucide-react';
+import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query';
+import { motion, AnimatePresence } from 'framer-motion';
+import { listKnowledgeBases, createKnowledgeBase, deleteKnowledgeBase, type KnowledgeBase } from '../lib/api';
+import ChatInterface from '../components/ChatInterface';
+import KBManagement from '../components/KBManagement';
+import HelpDocs from '../components/HelpDocs';
+
+export default function MainApp() {
+ const [selectedKB, setSelectedKB] = useState(null);
+ const [activeTab, setActiveTab] = useState<'kb' | 'chat' | 'help'>('kb');
+ const [showCreateKB, setShowCreateKB] = useState(false);
+ const [newKBName, setNewKBName] = useState('');
+ const [newKBType, setNewKBType] = useState('generic');
+ const [newKBDesc, setNewKBDesc] = useState('');
+
+ // RAG settings
+ const [useHybrid, setUseHybrid] = useState(false);
+ const [useRerank, setUseRerank] = useState(false);
+ const [useAgentic, setUseAgentic] = useState(false);
+
+ const queryClient = useQueryClient();
+
+ // Fetch knowledge bases
+ const { data: kbs = [], isLoading } = useQuery({
+ queryKey: ['knowledge-bases'],
+ queryFn: listKnowledgeBases,
+ });
+
+ // Create KB mutation
+ const createKBMutation = useMutation({
+ mutationFn: () => createKnowledgeBase(newKBName, newKBType, newKBDesc),
+ onSuccess: () => {
+ queryClient.invalidateQueries({ queryKey: ['knowledge-bases'] });
+ setShowCreateKB(false);
+ setNewKBName('');
+ setNewKBType('generic');
+ setNewKBDesc('');
+ },
+ });
+
+ // Delete KB mutation
+ const deleteKBMutation = useMutation({
+ mutationFn: (kb_name: string) => deleteKnowledgeBase(kb_name),
+ onSuccess: () => {
+ queryClient.invalidateQueries({ queryKey: ['knowledge-bases'] });
+ },
+ });
+
+ const handleCreateKB = () => {
+ if (newKBName.trim()) {
+ createKBMutation.mutate();
+ }
+ };
+
+ return (
+
+ {/* Top Navigation */}
+
+
+
+
+
CODE-FORGE
+
+
+
+
+
+ Welcome
+
+
+
+
+
+
+
+ {/* Left Sidebar */}
+
+ {/* Settings Section */}
+
+
+ {/* Knowledge Bases List */}
+
+
+
+
+ Knowledge Bases
+
+
setShowCreateKB(!showCreateKB)}
+ className="p-1 rounded hover:bg-electric-teal/20 transition-colors"
+ >
+
+
+
+
+ {/* Create KB Form */}
+
+ {showCreateKB && (
+
+ setNewKBName(e.target.value)}
+ className="input w-full mb-2"
+ />
+ setNewKBType(e.target.value)}
+ className="input w-full mb-2"
+ >
+ Generic
+ Code
+ Documentation
+ Agent OS
+
+ setNewKBDesc(e.target.value)}
+ className="input w-full mb-2"
+ />
+
+ {createKBMutation.isPending ? 'Creating...' : 'Create KB'}
+
+
+ )}
+
+
+ {/* KB List */}
+
+ {isLoading ? (
+
Loading...
+ ) : kbs.length === 0 ? (
+
No knowledge bases yet
+ ) : (
+ kbs.map((kb: KnowledgeBase) => (
+
setSelectedKB(kb.name)}
+ >
+
+
+
{kb.name}
+
{kb.kb_type}
+
+
{
+ e.stopPropagation();
+ if (confirm(`Delete "${kb.name}"?`)) {
+ deleteKBMutation.mutate(kb.name);
+ }
+ }}
+ className="p-1 rounded hover:bg-blaze-orange/20 transition-colors"
+ >
+
+
+
+
+ ))
+ )}
+
+
+
+
+ {/* Main Content */}
+
+ {/* Tabs */}
+
+ setActiveTab('kb')}
+ className={`px-4 py-2 rounded-lg font-semibold transition-all ${
+ activeTab === 'kb'
+ ? 'bg-electric-teal text-deep-night'
+ : 'text-light-grey hover:text-white'
+ }`}
+ >
+
+ KB Management
+
+ setActiveTab('chat')}
+ className={`px-4 py-2 rounded-lg font-semibold transition-all ${
+ activeTab === 'chat'
+ ? 'bg-electric-teal text-deep-night'
+ : 'text-light-grey hover:text-white'
+ }`}
+ disabled={!selectedKB}
+ >
+
+ Chat
+
+ setActiveTab('help')}
+ className={`px-4 py-2 rounded-lg font-semibold transition-all ${
+ activeTab === 'help'
+ ? 'bg-electric-teal text-deep-night'
+ : 'text-light-grey hover:text-white'
+ }`}
+ >
+
+ Help
+
+
+
+ {/* Tab Content */}
+
+ {activeTab === 'help' ? (
+
+ ) : !selectedKB ? (
+
+
+
+
No Knowledge Base Selected
+
Create or select a knowledge base to get started
+
+
+ ) : activeTab === 'kb' ? (
+
+ ) : (
+
+ )}
+
+
+
+
+ );
+}
diff --git a/frontend/src/pages/Welcome.tsx b/frontend/src/pages/Welcome.tsx
new file mode 100644
index 0000000..60285d8
--- /dev/null
+++ b/frontend/src/pages/Welcome.tsx
@@ -0,0 +1,155 @@
+import { motion } from 'framer-motion';
+import { Database, Cpu, Zap, BookOpen, Brain, ArrowRight } from 'lucide-react';
+import { Link } from 'react-router-dom';
+
+export default function Welcome() {
+ return (
+
+ {/* Animated background */}
+
+
+
+ {/* Hero Section */}
+
+ {/* Hero Image */}
+
+
+
+
+ {/* Subtitle */}
+
+ Production-Grade RAG System with PostgreSQL + pgvector
+
+
+ {/* CTA Button */}
+
+
+ Get Started
+
+
+
+
+
+ {/* Features Grid */}
+
+ }
+ title="PostgreSQL + pgvector"
+ description="ACID-compliant vector database with production-grade reliability"
+ delay={0.1}
+ />
+ }
+ title="Local LLMs"
+ description="Powered by Ollama - no API keys, complete privacy"
+ delay={0.2}
+ />
+ }
+ title="MCP Integration"
+ description="Expose knowledge bases to AI agents via Model Context Protocol"
+ delay={0.3}
+ />
+ }
+ title="Multi-KB Architecture"
+ description="Isolated knowledge bases per project with type-aware organization"
+ delay={0.4}
+ />
+ }
+ title="Advanced RAG"
+ description="Vector search, hybrid search, reranking, and agentic RAG modes"
+ delay={0.5}
+ />
+ }
+ title="High-Tech UI"
+ description="Electric teal & blaze orange design that looks fucking amazing"
+ delay={0.6}
+ />
+
+
+ {/* Quick Start */}
+
+
+
🎯 Quick Start
+
+
+ 1
+ Click "Get Started" to access the main application
+
+
+ 2
+ Create a Knowledge Base from the left panel
+
+
+ 3
+ Upload documents or import a directory
+
+
+ 4
+ Start chatting with your knowledge base using advanced RAG
+
+
+
+
+
+
+ );
+}
+
+interface FeatureCardProps {
+ icon: React.ReactNode;
+ title: string;
+ description: string;
+ delay: number;
+}
+
+function FeatureCard({ icon, title, description, delay }: FeatureCardProps) {
+ return (
+
+ {icon}
+ {title}
+ {description}
+
+ );
+}
+
diff --git a/frontend/tailwind.config.js b/frontend/tailwind.config.js
new file mode 100644
index 0000000..f664a21
--- /dev/null
+++ b/frontend/tailwind.config.js
@@ -0,0 +1,49 @@
+/** @type {import('tailwindcss').Config} */
+export default {
+ content: [
+ "./index.html",
+ "./src/**/*.{js,ts,jsx,tsx}",
+ ],
+ plugins: [
+ require('@tailwindcss/typography'),
+ ],
+ theme: {
+ extend: {
+ colors: {
+ // Code-Forge Design Guide colors
+ 'deep-night': '#0A0E1A',
+ 'electric-teal': '#00FFFF',
+ 'blaze-orange': '#FF8C00',
+ 'cool-blue': '#4D94FF',
+ 'light-grey': '#C0C0C0',
+ },
+ fontFamily: {
+ mono: ['"JetBrains Mono"', 'monospace'],
+ },
+ animation: {
+ 'float': 'float 3s ease-in-out infinite',
+ 'pulse-glow': 'pulse-glow 8s ease-in-out infinite',
+ 'gradient': 'gradient 8s linear infinite',
+ },
+ keyframes: {
+ float: {
+ '0%, 100%': { transform: 'translateY(0px)' },
+ '50%': { transform: 'translateY(-20px)' },
+ },
+ 'pulse-glow': {
+ '0%, 100%': { transform: 'scale(1)', opacity: '0.5' },
+ '50%': { transform: 'scale(1.1)', opacity: '0.8' },
+ },
+ gradient: {
+ '0%, 100%': { backgroundPosition: '0% 50%' },
+ '50%': { backgroundPosition: '100% 50%' },
+ },
+ },
+ backgroundSize: {
+ '200': '200% 200%',
+ },
+ },
+ },
+ plugins: [],
+}
+
diff --git a/frontend/tsconfig.app.json b/frontend/tsconfig.app.json
new file mode 100644
index 0000000..a9b5a59
--- /dev/null
+++ b/frontend/tsconfig.app.json
@@ -0,0 +1,28 @@
+{
+ "compilerOptions": {
+ "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo",
+ "target": "ES2022",
+ "useDefineForClassFields": true,
+ "lib": ["ES2022", "DOM", "DOM.Iterable"],
+ "module": "ESNext",
+ "types": ["vite/client"],
+ "skipLibCheck": true,
+
+ /* Bundler mode */
+ "moduleResolution": "bundler",
+ "allowImportingTsExtensions": true,
+ "verbatimModuleSyntax": true,
+ "moduleDetection": "force",
+ "noEmit": true,
+ "jsx": "react-jsx",
+
+ /* Linting */
+ "strict": true,
+ "noUnusedLocals": true,
+ "noUnusedParameters": true,
+ "erasableSyntaxOnly": true,
+ "noFallthroughCasesInSwitch": true,
+ "noUncheckedSideEffectImports": true
+ },
+ "include": ["src"]
+}
diff --git a/frontend/tsconfig.json b/frontend/tsconfig.json
new file mode 100644
index 0000000..1ffef60
--- /dev/null
+++ b/frontend/tsconfig.json
@@ -0,0 +1,7 @@
+{
+ "files": [],
+ "references": [
+ { "path": "./tsconfig.app.json" },
+ { "path": "./tsconfig.node.json" }
+ ]
+}
diff --git a/frontend/tsconfig.node.json b/frontend/tsconfig.node.json
new file mode 100644
index 0000000..8a67f62
--- /dev/null
+++ b/frontend/tsconfig.node.json
@@ -0,0 +1,26 @@
+{
+ "compilerOptions": {
+ "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo",
+ "target": "ES2023",
+ "lib": ["ES2023"],
+ "module": "ESNext",
+ "types": ["node"],
+ "skipLibCheck": true,
+
+ /* Bundler mode */
+ "moduleResolution": "bundler",
+ "allowImportingTsExtensions": true,
+ "verbatimModuleSyntax": true,
+ "moduleDetection": "force",
+ "noEmit": true,
+
+ /* Linting */
+ "strict": true,
+ "noUnusedLocals": true,
+ "noUnusedParameters": true,
+ "erasableSyntaxOnly": true,
+ "noFallthroughCasesInSwitch": true,
+ "noUncheckedSideEffectImports": true
+ },
+ "include": ["vite.config.ts"]
+}
diff --git a/frontend/vite.config.ts b/frontend/vite.config.ts
new file mode 100644
index 0000000..8b0f57b
--- /dev/null
+++ b/frontend/vite.config.ts
@@ -0,0 +1,7 @@
+import { defineConfig } from 'vite'
+import react from '@vitejs/plugin-react'
+
+// https://vite.dev/config/
+export default defineConfig({
+ plugins: [react()],
+})
diff --git a/mcp_server/server.py b/mcp_server/server.py
index 5260183..9b15c59 100644
--- a/mcp_server/server.py
+++ b/mcp_server/server.py
@@ -6,20 +6,27 @@ Exposes RAG functionality via Model Context Protocol with HTTP transport.
import logging
import sys
from pathlib import Path
-from typing import List
+from typing import Any, Dict, List
# Add parent directory to path for imports
sys.path.insert(0, str(Path(__file__).parent.parent))
-from fastapi import FastAPI
+from fastapi import FastAPI, Request, UploadFile, File, HTTPException
from fastapi.middleware.cors import CORSMiddleware
-from mcp.server.fastmcp import FastMCP
+from fastapi.responses import JSONResponse
+from pydantic import BaseModel
import uvicorn
+import requests
+import psycopg2
+from typing import Optional
-from app.core.chroma_manager import get_chroma_manager
+from app.core.pg_manager import get_pg_manager
from app.core.config import Config
from app.core.kb_metadata import get_collection_stats, get_documents_metadata
+from app.core.kb_types import KBType
from app.core.rag_engine import RAGEngine
+from app.core.agent_os_ingestion import AgentOSIngestion
+from app.core.agent_os_parser import AgentOSContentType
# Configure logging
logging.basicConfig(
@@ -28,11 +35,10 @@ logging.basicConfig(
)
logger = logging.getLogger(__name__)
-# Initialize FastAPI and FastMCP
+# Initialize FastAPI
app = FastAPI(title="Code-Forge MCP Server")
-mcp = FastMCP("code-forge")
-# Add CORS middleware for Claude Desktop
+# Add CORS middleware
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
@@ -41,82 +47,175 @@ app.add_middleware(
allow_headers=["*"],
)
+# MCP Tools Registry
+TOOLS = {
+ "search_knowledge_base": {
+ "description": "Search a knowledge base using RAG with optional advanced features",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "kb_name": {"type": "string", "description": "Name of the knowledge base to search"},
+ "query": {"type": "string", "description": "The search query"},
+ "use_hybrid": {"type": "boolean", "description": "Enable hybrid search (vector + BM25)", "default": False},
+ "use_rerank": {"type": "boolean", "description": "Enable reranking for better relevance", "default": False},
+ "use_agentic": {"type": "boolean", "description": "Enable agentic RAG for complex queries", "default": False}
+ },
+ "required": ["kb_name", "query"]
+ }
+ },
+ "list_knowledge_bases": {
+ "description": "List all available knowledge bases with type metadata",
+ "inputSchema": {
+ "type": "object",
+ "properties": {}
+ }
+ },
+ "list_knowledge_bases_by_type": {
+ "description": "List knowledge bases filtered by type (e.g., agent-os, code, documentation)",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "kb_type": {
+ "type": "string",
+ "description": "KB type to filter by",
+ "enum": ["generic", "code", "documentation", "agent-os"]
+ }
+ },
+ "required": ["kb_type"]
+ }
+ },
+ "create_knowledge_base": {
+ "description": "Create a new knowledge base with specified type",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "name": {"type": "string", "description": "Name for the new knowledge base"},
+ "kb_type": {
+ "type": "string",
+ "description": "Type of knowledge base",
+ "enum": ["generic", "code", "documentation", "agent-os"],
+ "default": "generic"
+ },
+ "description": {"type": "string", "description": "Optional description", "default": ""}
+ },
+ "required": ["name"]
+ }
+ },
+ "get_kb_stats": {
+ "description": "Get statistics for a knowledge base",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "kb_name": {"type": "string", "description": "Name of the knowledge base"}
+ },
+ "required": ["kb_name"]
+ }
+ },
+ "list_documents": {
+ "description": "List all documents in a knowledge base",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "kb_name": {"type": "string", "description": "Name of the knowledge base"}
+ },
+ "required": ["kb_name"]
+ }
+ },
+ "ingest_agent_os_profile": {
+ "description": "Ingest an Agent OS profile directory into a knowledge base",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "kb_name": {"type": "string", "description": "Name of the Agent OS knowledge base"},
+ "profile_path": {"type": "string", "description": "Path to the Agent OS profile directory"}
+ },
+ "required": ["kb_name", "profile_path"]
+ }
+ },
+ "get_agent_os_stats": {
+ "description": "Get statistics about Agent OS content in a knowledge base",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "kb_name": {"type": "string", "description": "Name of the Agent OS knowledge base"}
+ },
+ "required": ["kb_name"]
+ }
+ },
+ "get_standards": {
+ "description": "Get coding standards from an Agent OS knowledge base",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "kb_name": {"type": "string", "description": "Name of the Agent OS knowledge base"},
+ "query": {"type": "string", "description": "Optional search query to filter standards", "default": ""}
+ },
+ "required": ["kb_name"]
+ }
+ },
+ "get_workflows": {
+ "description": "Get development workflows from an Agent OS knowledge base",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "kb_name": {"type": "string", "description": "Name of the Agent OS knowledge base"},
+ "query": {"type": "string", "description": "Optional search query to filter workflows", "default": ""}
+ },
+ "required": ["kb_name"]
+ }
+ },
+ "get_specs": {
+ "description": "Get feature specifications from an Agent OS knowledge base",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "kb_name": {"type": "string", "description": "Name of the Agent OS knowledge base"},
+ "query": {"type": "string", "description": "Optional search query to filter specs", "default": ""}
+ },
+ "required": ["kb_name"]
+ }
+ },
+ "get_product_context": {
+ "description": "Get product vision and context from an Agent OS knowledge base",
+ "inputSchema": {
+ "type": "object",
+ "properties": {
+ "kb_name": {"type": "string", "description": "Name of the Agent OS knowledge base"}
+ },
+ "required": ["kb_name"]
+ }
+ }
+}
-@mcp.tool()
-async def search_knowledge_base(
- kb_name: str,
- query: str,
- use_hybrid: bool = False,
- use_rerank: bool = False,
- use_agentic: bool = False
-) -> dict:
- """
- Search a knowledge base using RAG with optional advanced features.
-
- Args:
- kb_name: Name of the knowledge base to search
- query: The search query
- use_hybrid: Enable hybrid search (vector + BM25 keyword search)
- use_rerank: Enable reranking of results for better relevance
- use_agentic: Enable agentic RAG for complex multi-step queries
-
- Returns:
- dict with 'answer' and 'sources' keys
- """
+
+# Tool implementation functions
+async def search_knowledge_base(kb_name: str, query: str, use_hybrid: bool = False,
+ use_rerank: bool = False, use_agentic: bool = False) -> dict:
+ """Search a knowledge base using RAG."""
try:
- # Validate KB exists
- chroma_manager = get_chroma_manager()
- if not chroma_manager.collection_exists(kb_name):
- return {
- "error": f"Knowledge base '{kb_name}' not found",
- "answer": "",
- "sources": []
- }
-
- # Check if KB is empty
- count = chroma_manager.get_collection_count(kb_name)
+ pg_manager = get_pg_manager()
+ if not pg_manager.collection_exists(kb_name):
+ return {"error": f"Knowledge base '{kb_name}' not found", "answer": "", "sources": []}
+
+ count = pg_manager.get_collection_count(kb_name)
if count == 0:
- return {
- "error": f"Knowledge base '{kb_name}' is empty. Please upload documents first.",
- "answer": "",
- "sources": []
- }
-
- # Initialize RAG engine
+ return {"error": f"Knowledge base '{kb_name}' is empty", "answer": "", "sources": []}
+
rag_engine = RAGEngine(kb_name)
-
- # Execute query
- result = rag_engine.query(
- question=query,
- use_hybrid=use_hybrid,
- use_rerank=use_rerank,
- use_agentic=use_agentic
- )
-
+ result = rag_engine.query(question=query, use_hybrid=use_hybrid,
+ use_rerank=use_rerank, use_agentic=use_agentic)
logger.info(f"Query executed on {kb_name}: {query[:50]}...")
-
return result
-
except Exception as e:
logger.error(f"Search failed: {e}")
- return {
- "error": str(e),
- "answer": "",
- "sources": []
- }
+ return {"error": str(e), "answer": "", "sources": []}
-@mcp.tool()
-async def list_knowledge_bases() -> List[str]:
- """
- List all available knowledge bases.
-
- Returns:
- List of knowledge base names
- """
+async def list_knowledge_bases() -> List[Dict[str, any]]:
+ """List all available knowledge bases with metadata."""
try:
- chroma_manager = get_chroma_manager()
- kbs = chroma_manager.list_collections()
+ pg_manager = get_pg_manager()
+ kbs = pg_manager.list_collections()
logger.info(f"Listed {len(kbs)} knowledge bases")
return kbs
except Exception as e:
@@ -124,42 +223,19 @@ async def list_knowledge_bases() -> List[str]:
return []
-@mcp.tool()
async def get_kb_stats(kb_name: str) -> dict:
- """
- Get statistics for a knowledge base.
-
- Args:
- kb_name: Name of the knowledge base
-
- Returns:
- dict with total_documents, total_chunks, and last_updated
- """
+ """Get statistics for a knowledge base."""
try:
stats = get_collection_stats(kb_name)
logger.info(f"Retrieved stats for {kb_name}")
return stats
except Exception as e:
logger.error(f"Failed to get stats for {kb_name}: {e}")
- return {
- "error": str(e),
- "total_documents": 0,
- "total_chunks": 0,
- "last_updated": None
- }
+ return {"error": str(e), "total_documents": 0, "total_chunks": 0, "last_updated": None}
-@mcp.tool()
async def list_documents(kb_name: str) -> List[dict]:
- """
- List all documents in a knowledge base.
-
- Args:
- kb_name: Name of the knowledge base
-
- Returns:
- List of document metadata dicts
- """
+ """List all documents in a knowledge base."""
try:
docs = get_documents_metadata(kb_name)
logger.info(f"Listed {len(docs)} documents in {kb_name}")
@@ -169,40 +245,605 @@ async def list_documents(kb_name: str) -> List[dict]:
return []
-# Health check endpoint
-@app.get("/health")
-async def health_check():
- """Health check endpoint."""
- return {"status": "healthy", "service": "code-forge-mcp"}
-
-
-# MCP endpoint
-@app.post("/mcp")
-async def mcp_endpoint(request: dict):
- """
- MCP protocol endpoint.
- Handles JSON-RPC style requests from MCP clients.
- """
+async def list_knowledge_bases_by_type(kb_type: str) -> List[Dict[str, any]]:
+ """List knowledge bases filtered by type."""
try:
- # FastMCP handles the request routing
- return await mcp.handle_request(request)
+ pg_manager = get_pg_manager()
+ kb_type_enum = KBType(kb_type)
+ kbs = pg_manager.list_collections_by_type(kb_type_enum)
+ logger.info(f"Listed {len(kbs)} knowledge bases of type {kb_type}")
+ return kbs
except Exception as e:
- logger.error(f"MCP request failed: {e}")
+ logger.error(f"Failed to list knowledge bases by type {kb_type}: {e}")
+ return []
+
+
+async def create_knowledge_base(name: str, kb_type: str = "generic", description: str = "") -> dict:
+ """Create a new knowledge base."""
+ try:
+ pg_manager = get_pg_manager()
+
+ # Check if already exists
+ if pg_manager.collection_exists(name):
+ return {
+ "success": False,
+ "error": f"Knowledge base '{name}' already exists"
+ }
+
+ # Create collection
+ kb_type_enum = KBType(kb_type)
+ success = pg_manager.create_collection(
+ name=name,
+ kb_type=kb_type_enum,
+ description=description
+ )
+
+ if success:
+ logger.info(f"Created knowledge base: {name} (type: {kb_type})")
+ return {
+ "success": True,
+ "name": name,
+ "kb_type": kb_type,
+ "description": description
+ }
+ else:
+ return {
+ "success": False,
+ "error": "Failed to create knowledge base"
+ }
+ except Exception as e:
+ logger.error(f"Failed to create knowledge base {name}: {e}")
return {
+ "success": False,
+ "error": str(e)
+ }
+
+
+async def ingest_agent_os_profile(kb_name: str, profile_path: str) -> dict:
+ """Ingest an Agent OS profile into a knowledge base."""
+ try:
+ pg_manager = get_pg_manager()
+ agent_os_ingestion = AgentOSIngestion(pg_manager)
+
+ stats = agent_os_ingestion.ingest_profile(
+ kb_name=kb_name,
+ profile_path=profile_path
+ )
+
+ logger.info(f"Ingested Agent OS profile from {profile_path} into {kb_name}")
+ return stats
+ except Exception as e:
+ logger.error(f"Failed to ingest Agent OS profile: {e}")
+ return {
+ "success": False,
+ "error": str(e),
+ "documents_processed": 0
+ }
+
+
+async def get_agent_os_stats(kb_name: str) -> dict:
+ """Get statistics about Agent OS content in a knowledge base."""
+ try:
+ pg_manager = get_pg_manager()
+ agent_os_ingestion = AgentOSIngestion(pg_manager)
+
+ stats = agent_os_ingestion.get_profile_stats(kb_name)
+ logger.info(f"Retrieved Agent OS stats for {kb_name}")
+ return stats
+ except Exception as e:
+ logger.error(f"Failed to get Agent OS stats for {kb_name}: {e}")
+ return {
+ "total_documents": 0,
+ "documents_by_type": {},
+ "error": str(e)
+ }
+
+
+async def get_standards(kb_name: str, query: str = "") -> List[dict]:
+ """Get coding standards from an Agent OS knowledge base."""
+ try:
+ pg_manager = get_pg_manager()
+ agent_os_ingestion = AgentOSIngestion(pg_manager)
+
+ results = agent_os_ingestion.search_by_type(
+ kb_name=kb_name,
+ content_type=AgentOSContentType.STANDARD,
+ query=query if query else None,
+ limit=20
+ )
+
+ logger.info(f"Retrieved {len(results)} standards from {kb_name}")
+ return results
+ except Exception as e:
+ logger.error(f"Failed to get standards from {kb_name}: {e}")
+ return []
+
+
+async def get_workflows(kb_name: str, query: str = "") -> List[dict]:
+ """Get development workflows from an Agent OS knowledge base."""
+ try:
+ pg_manager = get_pg_manager()
+ agent_os_ingestion = AgentOSIngestion(pg_manager)
+
+ results = agent_os_ingestion.search_by_type(
+ kb_name=kb_name,
+ content_type=AgentOSContentType.WORKFLOW,
+ query=query if query else None,
+ limit=20
+ )
+
+ logger.info(f"Retrieved {len(results)} workflows from {kb_name}")
+ return results
+ except Exception as e:
+ logger.error(f"Failed to get workflows from {kb_name}: {e}")
+ return []
+
+
+async def get_specs(kb_name: str, query: str = "") -> List[dict]:
+ """Get feature specifications from an Agent OS knowledge base."""
+ try:
+ pg_manager = get_pg_manager()
+ agent_os_ingestion = AgentOSIngestion(pg_manager)
+
+ results = agent_os_ingestion.search_by_type(
+ kb_name=kb_name,
+ content_type=AgentOSContentType.SPEC,
+ query=query if query else None,
+ limit=20
+ )
+
+ logger.info(f"Retrieved {len(results)} specs from {kb_name}")
+ return results
+ except Exception as e:
+ logger.error(f"Failed to get specs from {kb_name}: {e}")
+ return []
+
+
+async def get_product_context(kb_name: str) -> List[dict]:
+ """Get product vision and context from an Agent OS knowledge base."""
+ try:
+ pg_manager = get_pg_manager()
+ agent_os_ingestion = AgentOSIngestion(pg_manager)
+
+ results = agent_os_ingestion.search_by_type(
+ kb_name=kb_name,
+ content_type=AgentOSContentType.PRODUCT,
+ query=None,
+ limit=20
+ )
+
+ logger.info(f"Retrieved {len(results)} product context documents from {kb_name}")
+ return results
+ except Exception as e:
+ logger.error(f"Failed to get product context from {kb_name}: {e}")
+ return []
+
+
+# Pydantic models for REST API
+class CreateKBRequest(BaseModel):
+ name: str
+ kb_type: str = "generic"
+ description: str = ""
+
+class ChatRequest(BaseModel):
+ query: str
+ use_hybrid: bool = False
+ use_rerank: bool = False
+ use_agentic: bool = False
+
+
+# REST API Endpoints for UI
+@app.get("/api/kb")
+async def api_list_knowledge_bases():
+ """REST API: List all knowledge bases."""
+ kbs = await list_knowledge_bases()
+ return {"knowledge_bases": kbs}
+
+
+@app.post("/api/kb")
+async def api_create_knowledge_base(request: CreateKBRequest):
+ """REST API: Create a new knowledge base."""
+ result = await create_knowledge_base(
+ name=request.name,
+ kb_type=request.kb_type,
+ description=request.description
+ )
+ if not result.get("success"):
+ raise HTTPException(status_code=400, detail=result.get("error"))
+ return result
+
+
+@app.delete("/api/kb/{kb_name}")
+async def api_delete_knowledge_base(kb_name: str):
+ """REST API: Delete a knowledge base."""
+ try:
+ pg_manager = get_pg_manager()
+ if not pg_manager.collection_exists(kb_name):
+ raise HTTPException(status_code=404, detail=f"Knowledge base '{kb_name}' not found")
+
+ success = pg_manager.delete_collection(kb_name)
+ if success:
+ return {"success": True, "message": f"Knowledge base '{kb_name}' deleted"}
+ else:
+ raise HTTPException(status_code=500, detail="Failed to delete knowledge base")
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"Failed to delete KB {kb_name}: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.get("/api/kb/{kb_name}/stats")
+async def api_get_kb_stats(kb_name: str):
+ """REST API: Get knowledge base statistics."""
+ stats = await get_kb_stats(kb_name)
+ if "error" in stats:
+ raise HTTPException(status_code=404, detail=stats["error"])
+ return stats
+
+
+@app.get("/api/kb/{kb_name}/documents")
+async def api_list_documents(kb_name: str):
+ """REST API: List documents in a knowledge base."""
+ docs = await list_documents(kb_name)
+ return {"documents": docs}
+
+
+@app.post("/api/kb/{kb_name}/chat")
+async def api_chat(kb_name: str, request: ChatRequest):
+ """REST API: Chat with a knowledge base."""
+ result = await search_knowledge_base(
+ kb_name=kb_name,
+ query=request.query,
+ use_hybrid=request.use_hybrid,
+ use_rerank=request.use_rerank,
+ use_agentic=request.use_agentic
+ )
+ if "error" in result and result["error"]:
+ raise HTTPException(status_code=400, detail=result["error"])
+ return result
+
+
+@app.post("/api/kb/{kb_name}/upload")
+async def api_upload_document(kb_name: str, file: UploadFile = File(...)):
+ """REST API: Upload a single document to a knowledge base."""
+ import tempfile
+ import os
+ from app.core.ingestion import ingest_file
+
+ # Validate KB exists
+ pg_manager = get_pg_manager()
+ kb = pg_manager.get_collection(kb_name)
+ if not kb:
+ raise HTTPException(status_code=404, detail=f"Knowledge base '{kb_name}' not found")
+
+ # Save uploaded file to temp location
+ try:
+ with tempfile.NamedTemporaryFile(delete=False, suffix=Path(file.filename).suffix) as tmp_file:
+ content = await file.read()
+ tmp_file.write(content)
+ tmp_path = tmp_file.name
+
+ # Ingest the file
+ result = ingest_file(tmp_path, kb_name, file.filename)
+
+ # Clean up temp file
+ os.unlink(tmp_path)
+
+ if result["status"] == "error":
+ raise HTTPException(status_code=400, detail=result.get("error", "Upload failed"))
+
+ return {
+ "success": True,
+ "filename": result["filename"],
+ "chunks": result["chunks"],
+ "file_type": result["file_type"]
+ }
+ except HTTPException:
+ raise
+ except Exception as e:
+ logger.error(f"Upload failed: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.post("/api/kb/{kb_name}/import")
+async def api_import_directory(kb_name: str, directory_path: str):
+ """REST API: Import all files from a directory into a knowledge base."""
+ from app.core.ingestion import ingest_directory
+
+ # Validate KB exists
+ pg_manager = get_pg_manager()
+ kb = pg_manager.get_collection(kb_name)
+ if not kb:
+ raise HTTPException(status_code=404, detail=f"Knowledge base '{kb_name}' not found")
+
+ # Validate directory exists
+ if not Path(directory_path).exists():
+ raise HTTPException(status_code=404, detail=f"Directory not found: {directory_path}")
+
+ try:
+ results = ingest_directory(directory_path, kb_name)
+
+ # Count successes and failures
+ successes = [r for r in results if r.get("status") == "success"]
+ failures = [r for r in results if r.get("status") == "error"]
+
+ return {
+ "success": True,
+ "total_files": len(results),
+ "successful": len(successes),
+ "failed": len(failures),
+ "results": results
+ }
+ except Exception as e:
+ logger.error(f"Directory import failed: {e}")
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.get("/api/ollama/models")
+async def api_list_ollama_models():
+ """REST API: List available Ollama models."""
+ try:
+ response = requests.get(f"{Config.OLLAMA_HOST}/api/tags", timeout=2)
+ if response.status_code == 200:
+ models = response.json().get("models", [])
+ return {"models": models}
+ else:
+ raise HTTPException(status_code=503, detail="Ollama service unavailable")
+ except Exception as e:
+ logger.error(f"Failed to list Ollama models: {e}")
+ raise HTTPException(status_code=503, detail=str(e))
+
+
+# Health check endpoint (detailed version at end of file)
+
+
+# MCP Protocol Endpoints
+@app.post("/")
+async def mcp_root(request: Request):
+ """Main MCP endpoint - handles JSON-RPC requests."""
+ return await handle_mcp_request(request)
+
+
+@app.post("/mcp")
+async def mcp_endpoint(request: Request):
+ """Alternative MCP endpoint path."""
+ return await handle_mcp_request(request)
+
+
+async def handle_mcp_request(request: Request) -> JSONResponse:
+ """Handle MCP JSON-RPC requests."""
+ try:
+ body = await request.json()
+ method = body.get("method")
+ params = body.get("params", {})
+ request_id = body.get("id")
+
+ logger.info(f"MCP request: {method}")
+
+ # Handle MCP protocol methods
+ if method == "initialize":
+ return JSONResponse({
+ "jsonrpc": "2.0",
+ "id": request_id,
+ "result": {
+ "protocolVersion": "2024-11-05",
+ "capabilities": {
+ "tools": {}
+ },
+ "serverInfo": {
+ "name": "code-forge",
+ "version": "1.0.0"
+ }
+ }
+ })
+
+ elif method == "tools/list":
+ tools_list = [
+ {"name": name, **info}
+ for name, info in TOOLS.items()
+ ]
+ return JSONResponse({
+ "jsonrpc": "2.0",
+ "id": request_id,
+ "result": {"tools": tools_list}
+ })
+
+ elif method == "tools/call":
+ tool_name = params.get("name")
+ arguments = params.get("arguments", {})
+
+ # Route to appropriate tool function
+ if tool_name == "search_knowledge_base":
+ result = await search_knowledge_base(**arguments)
+ elif tool_name == "list_knowledge_bases":
+ result = await list_knowledge_bases()
+ elif tool_name == "list_knowledge_bases_by_type":
+ result = await list_knowledge_bases_by_type(**arguments)
+ elif tool_name == "create_knowledge_base":
+ result = await create_knowledge_base(**arguments)
+ elif tool_name == "get_kb_stats":
+ result = await get_kb_stats(**arguments)
+ elif tool_name == "list_documents":
+ result = await list_documents(**arguments)
+ elif tool_name == "ingest_agent_os_profile":
+ result = await ingest_agent_os_profile(**arguments)
+ elif tool_name == "get_agent_os_stats":
+ result = await get_agent_os_stats(**arguments)
+ elif tool_name == "get_standards":
+ result = await get_standards(**arguments)
+ elif tool_name == "get_workflows":
+ result = await get_workflows(**arguments)
+ elif tool_name == "get_specs":
+ result = await get_specs(**arguments)
+ elif tool_name == "get_product_context":
+ result = await get_product_context(**arguments)
+ else:
+ return JSONResponse({
+ "jsonrpc": "2.0",
+ "id": request_id,
+ "error": {
+ "code": -32601,
+ "message": f"Unknown tool: {tool_name}"
+ }
+ })
+
+ return JSONResponse({
+ "jsonrpc": "2.0",
+ "id": request_id,
+ "result": {
+ "content": [
+ {
+ "type": "text",
+ "text": str(result)
+ }
+ ]
+ }
+ })
+
+ else:
+ return JSONResponse({
+ "jsonrpc": "2.0",
+ "id": request_id,
+ "error": {
+ "code": -32601,
+ "message": f"Method not found: {method}"
+ }
+ })
+
+ except Exception as e:
+ logger.error(f"MCP request failed: {e}", exc_info=True)
+ return JSONResponse({
"jsonrpc": "2.0",
+ "id": body.get("id") if 'body' in locals() else None,
"error": {
"code": -32603,
"message": str(e)
- },
- "id": request.get("id")
+ }
+ })
+
+
+@app.get("/health")
+async def health_check():
+ """
+ Health check endpoint that verifies all system components.
+ Returns detailed status for monitoring.
+ """
+ health_status = {
+ "status": "healthy",
+ "components": {},
+ "timestamp": None
+ }
+
+ from datetime import datetime
+ health_status["timestamp"] = datetime.utcnow().isoformat()
+
+ # Check PostgreSQL
+ try:
+ pg_manager = get_pg_manager()
+ collections = pg_manager.list_collections()
+
+ # Try to get schema version
+ conn = pg_manager.get_connection()
+ cursor = conn.cursor()
+ cursor.execute("SELECT COUNT(*) FROM information_schema.tables WHERE table_schema='public';")
+ table_count = cursor.fetchone()[0]
+ cursor.close()
+ pg_manager.return_connection(conn)
+
+ health_status["components"]["postgresql"] = {
+ "status": "healthy",
+ "connected": True,
+ "database": "codeforge",
+ "tables": table_count,
+ "knowledge_bases": len(collections)
}
+ except Exception as e:
+ health_status["status"] = "unhealthy"
+ health_status["components"]["postgresql"] = {
+ "status": "unhealthy",
+ "connected": False,
+ "error": str(e)
+ }
+
+ # Check Ollama
+ try:
+ response = requests.get(f"{Config.OLLAMA_HOST}/api/tags", timeout=2)
+ if response.status_code == 200:
+ models = response.json().get("models", [])
+ model_names = [m["name"] for m in models]
+
+ # Check for required models
+ required_models = ["nomic-embed-text:latest", "llama3.2:3b"]
+ missing_models = [m for m in required_models if m not in model_names]
+
+ health_status["components"]["ollama"] = {
+ "status": "healthy" if not missing_models else "degraded",
+ "running": True,
+ "models_installed": len(models),
+ "required_models": required_models,
+ "missing_models": missing_models
+ }
+
+ if missing_models:
+ health_status["status"] = "degraded"
+ else:
+ health_status["status"] = "degraded"
+ health_status["components"]["ollama"] = {
+ "status": "degraded",
+ "running": True,
+ "error": f"Unexpected status code: {response.status_code}"
+ }
+ except Exception as e:
+ health_status["status"] = "unhealthy"
+ health_status["components"]["ollama"] = {
+ "status": "unhealthy",
+ "running": False,
+ "error": str(e)
+ }
+
+ # Check pgvector extension
+ try:
+ pg_manager = get_pg_manager()
+ conn = pg_manager.get_connection()
+ cursor = conn.cursor()
+ cursor.execute("SELECT extversion FROM pg_extension WHERE extname='vector';")
+ result = cursor.fetchone()
+ cursor.close()
+ pg_manager.return_connection(conn)
+
+ if result:
+ health_status["components"]["pgvector"] = {
+ "status": "healthy",
+ "installed": True,
+ "version": result[0]
+ }
+ else:
+ health_status["status"] = "unhealthy"
+ health_status["components"]["pgvector"] = {
+ "status": "unhealthy",
+ "installed": False,
+ "error": "pgvector extension not found"
+ }
+ except Exception as e:
+ health_status["status"] = "unhealthy"
+ health_status["components"]["pgvector"] = {
+ "status": "unhealthy",
+ "installed": False,
+ "error": str(e)
+ }
+
+ # Return appropriate HTTP status code
+ status_code = 200 if health_status["status"] in ["healthy", "degraded"] else 503
+
+ return JSONResponse(content=health_status, status_code=status_code)
def main():
"""Start the MCP server."""
logger.info(f"Starting Code-Forge MCP Server on {Config.MCP_SERVER_HOST}:{Config.MCP_SERVER_PORT}")
logger.info(f"MCP endpoint: http://{Config.MCP_SERVER_HOST}:{Config.MCP_SERVER_PORT}/mcp")
-
+
uvicorn.run(
app,
host=Config.MCP_SERVER_HOST,
diff --git a/requirements.txt b/requirements.txt
index 1140518..7fc1899 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -5,10 +5,13 @@ streamlit>=1.30.0
llama-index>=0.10.0
llama-index-llms-ollama>=0.1.0
llama-index-embeddings-ollama>=0.1.0
-llama-index-vector-stores-chroma>=0.1.0
+llama-index-vector-stores-postgres>=0.1.0
# Vector Database
-chromadb>=0.4.22
+psycopg2-binary>=2.9.9
+pgvector>=0.2.0
+sqlalchemy>=2.0.0
+numpy>=1.24.0
# Document Processing
pymupdf>=1.23.0
diff --git a/setup.sh b/setup.sh
new file mode 100755
index 0000000..96751db
--- /dev/null
+++ b/setup.sh
@@ -0,0 +1,330 @@
+#!/bin/bash
+
+# Code-Forge Setup Script
+# Automated setup for first-time users
+
+set -e # Exit on error
+
+# Colors for output
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+BLUE='\033[0;34m'
+PURPLE='\033[0;35m'
+NC='\033[0m' # No Color
+
+# Archon-inspired banner
+echo -e "${PURPLE}"
+cat << "EOF"
+╔═══════════════════════════════════════════════════════════════╗
+║ ║
+║ ██████╗ ██████╗ ██████╗ ███████╗ ███████╗ ██████╗ ██████╗ ██████╗ ███████╗
+║ ██╔════╝██╔═══██╗██╔══██╗██╔════╝ ██╔════╝██╔═══██╗██╔══██╗██╔════╝ ██╔════╝
+║ ██║ ██║ ██║██║ ██║█████╗ █████╗ ██║ ██║██████╔╝██║ ███╗█████╗
+║ ██║ ██║ ██║██║ ██║██╔══╝ ██╔══╝ ██║ ██║██╔══██╗██║ ██║██╔══╝
+║ ╚██████╗╚██████╔╝██████╔╝███████╗ ██║ ╚██████╔╝██║ ██║╚██████╔╝███████╗
+║ ╚═════╝ ╚═════╝ ╚═════╝ ╚══════╝ ╚═╝ ╚═════╝ ╚═╝ ╚═╝ ╚═════╝ ╚══════╝
+║ ║
+║ Localized Multi-Knowledge-Base RAG System ║
+║ with MCP Integration ║
+║ ║
+╚═══════════════════════════════════════════════════════════════╝
+EOF
+echo -e "${NC}"
+
+echo -e "${BLUE}🚀 Starting Code-Forge setup...${NC}\n"
+
+# Function to print status
+print_status() {
+ echo -e "${BLUE}[INFO]${NC} $1"
+}
+
+print_success() {
+ echo -e "${GREEN}[✓]${NC} $1"
+}
+
+print_warning() {
+ echo -e "${YELLOW}[!]${NC} $1"
+}
+
+print_error() {
+ echo -e "${RED}[✗]${NC} $1"
+}
+
+# Check if running on macOS
+if [[ "$OSTYPE" != "darwin"* ]]; then
+ print_error "This script is designed for macOS. For other platforms, please follow manual setup instructions."
+ exit 1
+fi
+
+print_success "Running on macOS"
+
+# ============================================================================
+# 1. Check Docker
+# ============================================================================
+echo -e "\n${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${PURPLE} Step 1: Docker${NC}"
+echo -e "${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+if command -v docker &> /dev/null; then
+ DOCKER_VERSION=$(docker --version | cut -d ' ' -f3 | cut -d ',' -f1)
+ print_success "Docker installed (version $DOCKER_VERSION)"
+
+ # Check if Docker is running
+ if docker info &> /dev/null; then
+ print_success "Docker daemon is running"
+ else
+ print_error "Docker is installed but not running"
+ print_status "Please start Docker Desktop and run this script again"
+ exit 1
+ fi
+else
+ print_error "Docker not found"
+ print_status "Please install Docker Desktop from: https://www.docker.com/products/docker-desktop"
+ exit 1
+fi
+
+# ============================================================================
+# 2. Check PostgreSQL
+# ============================================================================
+echo -e "\n${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${PURPLE} Step 2: PostgreSQL${NC}"
+echo -e "${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+if command -v psql &> /dev/null; then
+ PG_VERSION=$(psql --version | cut -d ' ' -f3)
+ print_success "PostgreSQL installed (version $PG_VERSION)"
+else
+ print_error "PostgreSQL not found"
+ print_status "Please install PostgreSQL from: https://postgresapp.com/"
+ print_status "Or via Homebrew: brew install postgresql@17"
+ exit 1
+fi
+
+# Test PostgreSQL connection
+print_status "Testing PostgreSQL connection..."
+if psql -c "SELECT version();" &> /dev/null; then
+ print_success "PostgreSQL connection successful"
+else
+ print_error "Cannot connect to PostgreSQL"
+ print_status "Please ensure PostgreSQL is running"
+ print_status "If using Postgres.app, make sure it's started"
+ exit 1
+fi
+
+# ============================================================================
+# 3. Install pgvector Extension
+# ============================================================================
+echo -e "\n${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${PURPLE} Step 3: pgvector Extension${NC}"
+echo -e "${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+print_status "Checking for pgvector extension..."
+
+# Check if pgvector is available
+if psql -c "CREATE EXTENSION IF NOT EXISTS vector;" &> /dev/null; then
+ PGVECTOR_VERSION=$(psql -c "SELECT extversion FROM pg_extension WHERE extname='vector';" -t 2>/dev/null | xargs)
+ if [ -n "$PGVECTOR_VERSION" ]; then
+ print_success "pgvector extension installed (version $PGVECTOR_VERSION)"
+ else
+ print_success "pgvector extension enabled"
+ fi
+else
+ print_error "pgvector extension not available"
+ print_status "Installing pgvector..."
+
+ # Try to install via Homebrew
+ if command -v brew &> /dev/null; then
+ brew install pgvector
+ print_success "pgvector installed via Homebrew"
+ else
+ print_error "Homebrew not found. Please install pgvector manually:"
+ print_status "Visit: https://github.com/pgvector/pgvector"
+ exit 1
+ fi
+fi
+
+# ============================================================================
+# 4. Create Database
+# ============================================================================
+echo -e "\n${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${PURPLE} Step 4: Database Setup${NC}"
+echo -e "${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+print_status "Creating 'codeforge' database..."
+
+# Check if database exists
+if psql -lqt | cut -d \| -f 1 | grep -qw codeforge; then
+ print_warning "Database 'codeforge' already exists"
+ read -p "$(echo -e ${YELLOW}Do you want to recreate it? This will DELETE all existing data! [y/N]: ${NC})" -n 1 -r
+ echo
+ if [[ $REPLY =~ ^[Yy]$ ]]; then
+ print_status "Dropping existing database..."
+ psql -c "DROP DATABASE codeforge;" 2>/dev/null || true
+ psql -c "CREATE DATABASE codeforge;"
+ print_success "Database recreated"
+ else
+ print_status "Keeping existing database"
+ fi
+else
+ psql -c "CREATE DATABASE codeforge;"
+ print_success "Database 'codeforge' created"
+fi
+
+# Enable pgvector extension in the database
+print_status "Enabling pgvector extension in codeforge database..."
+psql -d codeforge -c "CREATE EXTENSION IF NOT EXISTS vector;" &> /dev/null
+print_success "pgvector extension enabled in codeforge database"
+
+# Run schema.sql
+print_status "Creating database schema..."
+if [ -f "app/db/schema.sql" ]; then
+ psql -d codeforge -f app/db/schema.sql &> /dev/null
+ print_success "Database schema created"
+
+ # Verify tables
+ TABLE_COUNT=$(psql -d codeforge -t -c "SELECT COUNT(*) FROM information_schema.tables WHERE table_schema='public';" | xargs)
+ print_success "Created $TABLE_COUNT tables"
+else
+ print_error "Schema file not found: app/db/schema.sql"
+ exit 1
+fi
+
+# ============================================================================
+# 5. Check Ollama
+# ============================================================================
+echo -e "\n${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${PURPLE} Step 5: Ollama${NC}"
+echo -e "${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+if command -v ollama &> /dev/null; then
+ OLLAMA_VERSION=$(ollama --version 2>&1 | head -n1 || echo "unknown")
+ print_success "Ollama installed ($OLLAMA_VERSION)"
+else
+ print_error "Ollama not found"
+ print_status "Installing Ollama..."
+
+ if command -v brew &> /dev/null; then
+ brew install ollama
+ print_success "Ollama installed via Homebrew"
+ else
+ print_status "Please install Ollama from: https://ollama.ai/download"
+ exit 1
+ fi
+fi
+
+# ============================================================================
+# 6. Download Required Models
+# ============================================================================
+echo -e "\n${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${PURPLE} Step 6: Ollama Models${NC}"
+echo -e "${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+print_status "This will download ~7GB of models. This may take a while..."
+
+# Start Ollama service if not running
+if ! pgrep -x "ollama" > /dev/null; then
+ print_status "Starting Ollama service..."
+ ollama serve &> /dev/null &
+ sleep 3
+ print_success "Ollama service started"
+fi
+
+# Download embedding model
+print_status "Downloading nomic-embed-text (274 MB)..."
+ollama pull nomic-embed-text
+print_success "nomic-embed-text downloaded"
+
+# Download LLM model
+print_status "Downloading llama3.2:3b (2.0 GB)..."
+ollama pull llama3.2:3b
+print_success "llama3.2:3b downloaded"
+
+# List installed models
+print_success "Installed models:"
+ollama list
+
+# ============================================================================
+# 7. Create Data Directories
+# ============================================================================
+echo -e "\n${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${PURPLE} Step 7: Data Directories${NC}"
+echo -e "${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+print_status "Creating data directories..."
+mkdir -p data/ollama
+print_success "Created data/ollama/"
+
+# ============================================================================
+# 8. Build Docker Containers
+# ============================================================================
+echo -e "\n${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${PURPLE} Step 8: Docker Containers${NC}"
+echo -e "${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+print_status "Building Docker containers..."
+docker-compose build
+print_success "Docker containers built"
+
+# ============================================================================
+# 9. Start Services
+# ============================================================================
+echo -e "\n${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${PURPLE} Step 9: Start Services${NC}"
+echo -e "${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+print_status "Starting Code-Forge services..."
+docker-compose up -d
+sleep 5
+print_success "Services started"
+
+# ============================================================================
+# 10. Verify Installation
+# ============================================================================
+echo -e "\n${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${PURPLE} Step 10: Verification${NC}"
+echo -e "${PURPLE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+print_status "Verifying installation..."
+
+# Check if services are running
+if docker ps | grep -q code-forge-app; then
+ print_success "Code-Forge app container running"
+else
+ print_error "Code-Forge app container not running"
+fi
+
+if docker ps | grep -q code-forge-ollama; then
+ print_success "Ollama container running"
+else
+ print_error "Ollama container not running"
+fi
+
+# ============================================================================
+# Setup Complete!
+# ============================================================================
+echo -e "\n${GREEN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
+echo -e "${GREEN} ✓ Setup Complete!${NC}"
+echo -e "${GREEN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}\n"
+
+echo -e "${BLUE}🎉 Code-Forge is ready to use!${NC}\n"
+
+echo -e "${YELLOW}Access the application:${NC}"
+echo -e " ${GREEN}•${NC} React UI: ${BLUE}http://localhost:5173${NC} ${PURPLE}(Recommended)${NC}"
+echo -e " ${GREEN}•${NC} Streamlit UI: ${BLUE}http://localhost:8501${NC}"
+echo -e " ${GREEN}•${NC} MCP Server: ${BLUE}http://localhost:8051${NC}"
+echo -e " ${GREEN}•${NC} Ollama API: ${BLUE}http://localhost:11434${NC}\n"
+
+echo -e "${YELLOW}Next steps:${NC}"
+echo -e " ${GREEN}1.${NC} Start the React frontend: ${BLUE}cd frontend && npm install && npm run dev${NC}"
+echo -e " ${GREEN}2.${NC} Open ${BLUE}http://localhost:5173${NC} in your browser"
+echo -e " ${GREEN}3.${NC} Create your first knowledge base"
+echo -e " ${GREEN}4.${NC} Upload documents and start chatting!\n"
+
+echo -e "${YELLOW}Useful commands:${NC}"
+echo -e " ${GREEN}•${NC} View logs: ${BLUE}docker-compose logs -f${NC}"
+echo -e " ${GREEN}•${NC} Stop services: ${BLUE}docker-compose down${NC}"
+echo -e " ${GREEN}•${NC} Restart services: ${BLUE}docker-compose restart${NC}\n"
+
+echo -e "${PURPLE}For more information, see README.md${NC}\n"
+