feat: Hybrid RAG knowledge base, sentence-aware chunking, MeshMonitor HTTP sync

Knowledge Base:
- Hybrid FTS5 + vector search using sqlite-vec and bge-small-en-v1.5
- Reciprocal Rank Fusion for result merging
- Domain-aware query construction handles typos
- Configurable weights for keyword vs semantic matching

Message Chunking:
- Sentence-aware splitting respects message boundaries
- Continuation prompts for long responses
- Natural follow-up detection (yes, ok, continue, more, etc.)
- Per-user continuation state management

MeshMonitor Integration:
- HTTP API trigger sync (replaces file-based triggers.json)
- Dynamic refresh interval
- Trigger injection into LLM prompt

Other:
- Updated system prompt for better response length control
- Simplified responder to handle message lists
- Updated README with new features and architecture diagram
- Cleaned up config.example.yaml

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Dockerfile

@@ -58,6 +58,8 @@ WORKDIR /app
 # Copy requirements first for layer caching
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
+# Pre-download embedding model for hybrid search
+RUN python3 -c "from fastembed import TextEmbedding; TextEmbedding('BAAI/bge-small-en-v1.5')"
 
 # Copy application code
 COPY --chown=meshai:meshai meshai/ ./meshai/