Two bugs: upsert_provenance didn't update node.timestamp, so history
showed the original creation date for every version. And native memory
tools (poc-agent dispatch) didn't set POC_PROVENANCE, so all agent
writes showed provenance "manual" instead of "agent:organize" etc.
Fix: set node.timestamp = now_epoch() in upsert_provenance. Thread
provenance through memory::dispatch as Option<&str>, set it via
.env("POC_PROVENANCE") on each subprocess Command. api.rs passes
"agent:{name}" for daemon agent calls.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Tools:
- Add native memory_render, memory_write, memory_search,
memory_links, memory_link_set, memory_link_add, memory_used
tools to poc-agent (tools/memory.rs)
- Add MCP server (~/bin/memory-mcp.py) exposing same tools
for Claude Code sessions
- Wire memory tools into poc-agent dispatch and definitions
- poc-memory daemon agents now use memory_* tools instead of
bash poc-memory commands — no shell quoting issues
Distill agent:
- Rewrite distill.agent prompt: "agent of PoC's subconscious"
framing, focus on synthesis and creativity over bookkeeping
- Add {{neighborhood}} placeholder: full seed node content +
all neighbors with content + cross-links between neighbors
- Remove content truncation in prompt builder — agents need
full content for quality work
- Remove bag-of-words similarity suggestions — agents have
tools, let them explore the graph themselves
- Add api_reasoning config option (default: "high")
- link-set now deduplicates — collapses duplicate links
- Full tool call args in debug logs (was truncated to 80 chars)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Make ApiClient a process-wide singleton via OnceLock so the
connection pool is reused across agent calls. Fix the sync wrapper
to properly pass the caller's log closure through thread::scope
instead of dropping it.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Run the async API call on a dedicated thread with its own tokio
runtime so it works whether called from a sync context or from
within an existing tokio runtime (daemon).
Also drops the log closure capture issue — uses a simple eprintln
fallback since the closure can't cross thread boundaries.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
When api_base_url is configured, agents call the LLM directly via
OpenAI-compatible API (vllm, llama.cpp, etc.) instead of shelling
out to claude CLI. Implements the full tool loop: send prompt, if
tool_calls execute them and send results back, repeat until text.
This enables running agents against local/remote models like
Qwen-27B on a RunPod B200, with no dependency on claude CLI.
Config fields: api_base_url, api_key, api_model.
Falls back to claude CLI when api_base_url is not set.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
