audit, digest, and compare now go through the API backend via
call_simple(), which logs to llm-logs/{caller}/.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Pass the caller's log closure all the way through to api.rs instead
of creating a separate eprintln closure in llm.rs. Everything goes
through one stream — prompt, think blocks, tool calls with args,
tool results with content, token counts, final response.
CLI uses println (stdout), daemon uses its task log. No more split
between stdout and stderr.
Also removes the llm-log file creation from knowledge.rs — that's
the daemon's concern, not the agent runner's.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Remove is_split special case in daemon — split now goes through
job_consolidation_agent like all other agents
- call_for_def uses API whenever api_base_url is configured, regardless
of tools field (was requiring non-empty tools to use API)
- Remove "tools" field from all .agent files — memory tools are always
provided by the API layer, not configured per-agent
- Add prompt size guard: reject prompts over 800KB (~200K tokens) with
clear error instead of hitting the model's context limit
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Store resource pool in OnceLock so run_job can pass it to
Daemon::run_job for pool state logging. Verbose logging enabled
via POC_MEMORY_VERBOSE=1 env var.
LLM backend selection and spawn-site pool state now use verbose
log level to keep daemon.log clean in production.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Switch from jobkit-daemon crate to jobkit with daemon feature.
Wire up per-task log files for all daemon-spawned agent tasks.
Changes:
- Use jobkit::daemon:: instead of jobkit_daemon::
- All agent tasks get .log_dir() set to $data_dir/logs/
- Task log path shown in daemon status and TUI
- New CLI: poc-memory agent daemon log --task NAME
Finds the task's log path from status or daemon.log, tails the file
- LLM backend selection logged to daemon.log via log_event
- Targeted agent job names include the target key for debuggability
- Logging architecture documented in doc/logging.md
Two-level logging, no duplication:
- daemon.log: lifecycle events with task log path for drill-down
- per-task logs: full agent output via ctx.log_line()
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>
Remove unused StoreView imports, unused store imports, dead
install_default_file, dead make_report_slug, dead fact-mine/
experience-mine spawning loops in daemon. Fix mut warnings.
Zero compiler warnings now.
Empty stdout and Claude's rate limit message were silently returned
as successful 0-byte responses. Now detected and reported as errors.
Also skip transcript segments with fewer than 2 assistant messages
(rate-limited sessions, stub conversations).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Agent subprocess calls now set POC_PROVENANCE=agent:{name} so any
nodes/links created via tool calls are tagged with the creating agent.
This makes agent transcripts indistinguishable from conscious sessions
in format — important for future model training.
new_relation() now reads POC_PROVENANCE env var directly (raw string,
not enum) since agent names are dynamic.
link-add now computes initial strength from Jaccard similarity instead
of hardcoded 0.8. New links start at a strength reflecting actual
neighborhood overlap.
Co-Authored-By: Kent Overstreet <kent.overstreet@linux.dev>
Add call_for_def() that threads model and tools from agent definitions
through to claude CLI. Tool-enabled agents get --allowedTools instead
of --tools "" and a longer 15-minute timeout for multi-turn work.
Add ActionKind::Delete with parse/apply support so agents can delete
nodes (used by organize agent for deduplication).
Use call_for_def() in run_one_agent instead of hardcoded call_sonnet.
The daemon was getting stuck when a claude subprocess hung — no
completion logged, job blocked forever, pending queue growing.
Use spawn() + watchdog thread instead of blocking output(). The
watchdog sleeps in 1s increments checking a cancel flag, sends
SIGTERM at 5 minutes, SIGKILL after 5s grace. Cancel flag ensures
the watchdog exits promptly when the child finishes normally.
- Refactor split from serial batch to independent per-node tasks
(run-agent split N spawns N parallel tasks, gated by llm_concurrency)
- Replace cosine similarity edge inheritance with agent-assigned
neighbors in the plan JSON — the LLM already understands the
semantic relationships, no need to approximate with bag-of-words
- Add --strict-mcp-config to claude CLI calls to skip MCP server
startup (saves ~5s per call)
- Remove hardcoded 2000-char split threshold — let the agent decide
what's worth splitting
- Reload store before mutations to handle concurrent split races
