00045314f8
Phase 4: Message Bus Viewer
- Backend: get_message_bus_status(), send_bus_message() in agents.py
- Route: GET /api/agents/message-bus, POST /api/agents/{id}/bus-message
- Frontend: Message Bus tab in agent detail overlay
Phase 5: Memory Search (ChromaDB)
- Backend: _search_agent_memory(), _search_all_agents_memory() via ChromaDB rose_memory collection
- Route: GET /api/agents/memory/search, GET /api/agents/{id}/memory/search
- Frontend: Search bar added to Memory tab, renders confidence scores + topics
Phase 6: Token Tracking + Topology Graph
- Backend: get_agent_usage() reads ~/.hermes/agents/{id}/usage.json
- Route: GET /api/agents/{id}/usage
- Frontend: Usage tab with today/week/month token counts and cost
- Frontend: Topology tab with SVG radial graph of agent network
81 lines
2.9 KiB
Python
81 lines
2.9 KiB
Python
"""
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Phase 5 — Memory Search (ChromaDB)
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Appended to agents.py functions for Memory Search.
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"""
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import chromadb
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def _get_chroma_client():
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"""Get or create the shared ChromaDB HTTP client (thread-safe singleton)."""
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if not hasattr(_get_chroma_client, "_client"):
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_get_chroma_client._client = chromadb.HttpClient(host="127.0.0.1", port=8000)
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return _get_chroma_client._client
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def _search_agent_memory(agent_id: str, query: str, limit: int = 10) -> list:
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"""
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Search memory for a specific agent.
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Searches the rose_memory collection filtered by topic matching agent_id.
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"""
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try:
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client = _get_chroma_client()
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coll = client.get_collection(name="rose_memory")
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results = coll.query(
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query_texts=[query],
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n_results=limit,
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include=["metadatas", "documents"],
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)
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matches = []
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for i, doc in enumerate(results.get("documents", [[]])[0] or []):
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meta = (results.get("metadatas", [[{}]])[0] or [{}])[i] or {}
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topic = meta.get("topic", "")
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# Filter: only docs that belong to this agent (topic starts with agent_id)
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if not topic.startswith(agent_id):
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continue
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matches.append({
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"id": (results.get("ids", [["?"]])[0] or ["?"])[i],
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"topic": topic,
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"content": doc,
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"confidence": float(meta.get("confidence", 0.0)),
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"tags": meta.get("tags", ""),
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"vault_path": meta.get("vault_path", ""),
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})
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return matches
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except Exception:
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return []
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def _search_all_agents_memory(query: str, limit: int = 20) -> list:
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"""
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Search across all agent memories in ChromaDB.
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Returns matches with agent attribution from topic.
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Topic format: "agent-name/fact-name" or flat topic name.
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"""
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try:
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client = _get_chroma_client()
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coll = client.get_collection(name="rose_memory")
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results = coll.query(
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query_texts=[query],
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n_results=limit,
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include=["metadatas", "documents"],
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)
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matches = []
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for i, doc in enumerate(results.get("documents", [[]])[0] or []):
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meta = (results.get("metadatas", [[{}]])[0] or [{}])[i] or {}
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topic = meta.get("topic", "")
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# Extract agent from topic: "agent-name/ffact" -> agent
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parts = topic.split("/")
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agent = parts[0] if len(parts) > 1 else topic
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matches.append({
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"id": (results.get("ids", [["?"]])[0] or ["?"])[i],
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"topic": topic,
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"agent": agent,
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"content": doc,
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"confidence": float(meta.get("confidence", 0.0)),
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"tags": meta.get("tags", ""),
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"vault_path": meta.get("vault_path", ""),
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})
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return matches
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except Exception:
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return []
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