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>
Replace homegrown wrapping math (wrapped_height, wrapped_height_line,
auto_scroll, force_scroll, wrapped_line_count) with ratatui's own
Paragraph::line_count() which exactly matches its rendering. The old
approach used ceiling division that didn't account for word wrapping,
causing bottom content to be clipped.
Also add terminal.clear() on resize to force full redraw — fixes the
TUI rendering at old canvas size after terminal resize.
Requires the unstable-rendered-line-info feature flag on ratatui.
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>
poc-memory now reads from poc-agent's config.json5 as the primary
config source. Memory-specific settings live in a "memory" section;
API credentials are resolved from the shared model/backend config
instead of being duplicated.
- Add "memory" section to ~/.config/poc-agent/config.json5
- poc-memory config.rs: try shared config first, fall back to
legacy JSONL
- API fields (base_url, api_key, model) resolved via
memory.agent_model -> models -> backend lookup
- Add json5 dependency for proper JSON5 parsing
- Update provisioning scripts: hermes -> qwen3_coder tool parser
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- distill.agent: fix {{distill}} → {{nodes}} placeholder so seed
nodes actually resolve
- render: show link strength values in the links section, sorted
by strength descending
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
ROCm-specific setup with:
- AITER attention backends (VLLM_ROCM_USE_AITER=1)
- Reduced cudagraph capture size (DeltaNet cache conflict)
- BF16 model + FP8 KV cache as default (FP8 weights can be
slower on MI300X due to ROCm kernel maturity)
- FP8=1 flag for benchmarking FP8 model weights
Key for training plan: if FP8 matmuls are slow on MI300X,
the quantize-and-expand strategy needs B200 instead.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Config is now stored in RwLock<Arc<Config>> instead of OnceLock<Config>.
get() returns Arc<Config> (cheap clone), and reload() re-reads from disk.
New RPC: "reload-config" — reloads config.jsonl without restarting
the daemon. Logs the change to daemon.log. Useful for switching
between API backends and claude accounts without losing in-flight
tasks.
New CLI: poc-memory agent daemon reload-config
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>
The previous approach scanned ratatui's rendered buffer to find the
cursor position, but couldn't distinguish padding spaces from text
spaces, causing incorrect cursor placement on wrapped lines.
Replace with a word_wrap_breaks() function that computes soft line
break positions by simulating ratatui's Wrap { trim: false } algorithm
(break at word boundaries, fall back to character wrap for long words).
cursor_visual_pos() then maps a character index to (col, row) using
those break positions.
Also fixes the input area height calculation to use word-wrap semantics
instead of character-wrap, matching the actual Paragraph rendering.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
When scanning the buffer for cursor position, also check empty cells.
The cursor might be positioned at an empty cell (e.g., end of line
or after all visible characters).
self.cursor is a byte index into the string. When scanning the buffer,
we need to compare character positions, not byte positions or widths.
Convert self.cursor to a character count before comparing with the
buffer scan. Count each non-empty cell as 1 character (the buffer
already represents visual cells, so width doesn't matter here).
The cursor index is into self.input, but the rendered buffer contains
the prompt prepended to the first line. Need to add prompt.len() to
get the correct character position when scanning the buffer.
Instead of simulating ratatui's word wrapping algorithm, scan the
rendered buffer to find the actual cursor position. This correctly
handles word wrapping, unicode widths, and any other rendering
nuances that ratatui applies.
The old code computed wrapped_height() and cursor position based on
simple character counting, which diverged from ratatui's WordWrapper
that respects word boundaries.
Now we render first, then walk the buffer counting visible characters
until we reach self.cursor. This is O(area) but the input area is
small (typically < 200 cells), so it's negligible.
Use unicode display width (matching ratatui's Wrap behavior) instead
of chars().count() for both wrapped_height calculation and cursor
positioning. The mismatch caused the cursor to drift when input
wrapped to multiple lines.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Always display reasoning tokens regardless of reasoning_effort
setting — Qwen 3.5 thinks natively and the reasoning parser
separates it into its own field
- Remove chat_template_kwargs that disabled thinking when
reasoning_effort was "none"
- Add chat_template_kwargs field to ChatRequest for vllm compat
- Update provision script: qwen3_xml tool parser, qwen3 reasoning
parser, 262K context, 95% GPU memory utilization
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Sets up vllm with Qwen 2.5 27B Instruct, prefix caching enabled,
Hermes tool call parser for function calling support. Configurable
via environment variables (MODEL, PORT, MAX_MODEL_LEN).
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>
jobkit-daemon is now an external git dependency with its own repo.
The local clone was only needed temporarily to fix a broken
Cargo.toml in the remote.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Lists nodes that are currently deleted with no subsequent live version.
Useful for diagnosing accidental deletions in the memory store.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Split poc-agent into lib + bin so its API client, types, and tool
dispatch can be imported by poc-memory. This is the foundation for
replacing claude CLI subprocess calls with direct API calls to
vllm/OpenAI-compatible endpoints.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Move poc-agent (substrate-independent AI agent framework) into the
memory workspace as a step toward using its API client for direct
LLM calls instead of shelling out to claude CLI.
Agent prompt improvements:
- distill: rewrite from hub-focused to knowledge-flow-focused.
Now walks upward from seed nodes to find and refine topic nodes,
instead of only maintaining high-degree hubs.
- distill: remove "don't touch journal entries" restriction
- memory-instructions-core: add "Make it alive" section — write
with creativity and emotional texture, not spreadsheet summaries
- memory-instructions-core: add "Show your reasoning" section —
agents must explain decisions, especially when they do nothing
- linker: already had emotional texture guidance (kept as-is)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Edition 2024 changes:
- gen is reserved: rename variable in query/engine.rs
- set_var is unsafe: wrap in unsafe block in cli/agent.rs
- match ergonomics: add explicit & in spectral.rs filter closure
New --local flag for `poc-memory agent run` bypasses the daemon and
runs the agent directly in-process. Useful for testing agent prompt
changes without waiting in the daemon queue.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The POC_PROVENANCE env var lookup was duplicated in upsert,
delete_node, and rename_node. Extract to a single function.
Co-Authored-By: Kent Overstreet <kent.overstreet@linux.dev>
delete_node and rename_node were cloning the previous node version
for the tombstone/rename entry without updating provenance or
timestamp. This made it impossible to tell who deleted a node or
when — the tombstone just inherited whatever the last write had.
Now both operations derive provenance from POC_PROVENANCE env var
(same as upsert) and set timestamp to now.
Co-Authored-By: Kent Overstreet <kent.overstreet@linux.dev>
cmd_history was silently hiding the deleted flag, making it
impossible to tell from the output that a node had been deleted.
This masked the kernel-patterns deletion — looked like the node
existed in the log but wouldn't load.
Also adds merge-logs and diag-key diagnostic binaries, and makes
Node::to_capnp public for use by external tools.
Co-Authored-By: Kent Overstreet <kent.overstreet@linux.dev>
rewrite_store() used File::create() to truncate and overwrite the
entire nodes.capnp log with only the latest version of each node
from the in-memory store. This destroyed all historical versions
and made no backup. Worse, any node missing from the in-memory
store due to a loading bug would be permanently lost.
strip_md_keys() now appends migrated nodes to the existing log
instead of rewriting it. The dead function is kept with a warning
comment explaining what went wrong.
Co-Authored-By: Kent Overstreet <kent.overstreet@linux.dev>
calibrate.agent: Haiku-based agent that reads a node and all its
neighbors, then assigns appropriate link strengths relative to each
other. Designed for high-volume runs across the whole graph.
graph link-set: Set strength of an existing link (0.0-1.0).
dominating-set query stage: Greedy 3-covering dominating set — finds
the minimum set of nodes such that every node in the input is within
1 hop of at least 3 selected nodes. Use with calibrate agent to
ensure every link gets assessed from multiple perspectives.
Usage: poc-memory query "content ~ 'bcachefs' | dominating-set"
--target and --query now queue individual daemon tasks instead of
running sequentially in the CLI. Each node gets its own choir task
with LLM resource locking. Falls back to local execution if daemon
isn't running.
RPC extended: "run-agent linker 1 target:KEY" spawns a targeted task.
Run an agent on nodes matching a query:
poc-memory agent run linker --query 'key ~ "bcachefs" | limit 10'
Resolves the query to node keys, then passes all as seeds to the agent.
For large batches, should be queued to daemon (future work).
experience_mine and journal_enrich are replaced by the observation
agent. enrich.rs reduced from 465 to 40 lines — only extract_conversation
and split_on_compaction remain (used by observation fragment selection).
-455 lines.
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.
All 12 agents with WRITE_NODE/REFINE/END_NODE output format blocks
now rely on tool calls (poc-memory write/link-add/etc) via the
Bash(poc-memory:*) tool. Guidelines preserved, format sections removed.
Also changed linker query from type:episodic to all nodes — it was
missing semantic nodes entirely, which is why skills-bcachefs-* nodes
were never getting linked to their hubs.
Adds run_one_agent_with_keys() which bypasses the agent's query and
uses explicitly provided node keys. This allows testing agents on
specific graph neighborhoods:
poc-memory agent run linker --target bcachefs --debug
New placeholder resolves to the 20 highest-degree nodes, skipping
neighbors of already-selected hubs so the list covers different
regions of the graph. Gives agents a starting point for linking
new content to the right places.
Added to observation.agent prompt.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Large conversation segments are now split into 50KB chunks with 10KB
overlap, instead of being truncated to 8000 chars (which was broken
anyway — broke after exceeding, not before). Each chunk gets its own
candidate ID for independent mining and dedup.
format_segment simplified: no size limit, added timestamps to output
so observation agent can cross-reference with journal entries.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Consolidate agent logging to one file per run in llm-logs/{agent}/.
Prompt written before LLM call, response appended after. --debug
additionally prints the same content to stdout.
Remove duplicate eprintln! calls and AgentResult.prompt field.
Kill experience_mine and fact_mine job functions from daemon —
observation.agent handles all transcript mining.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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>
Add --debug flag that prints the full prompt and LLM response to
stdout, making it easy to iterate on agent prompts. Also adds
prompt field to AgentResult so callers can inspect what was sent.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Raw agent responses were being stored as nodes in the graph
(_consolidate-*, _knowledge-*), creating thousands of nodes per day
that polluted search results and bloated the store. Now logged to
~/.claude/memory/llm-logs/<agent>/<timestamp>.txt instead.
Node creation should only happen through explicit agent actions
(WRITE_NODE, REFINE) or direct poc-memory write tool calls.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
New command: `poc-memory agent run <agent> [--count N] [--dry-run]`
Runs a single agent by name through the full pipeline (build prompt,
call LLM, apply actions). With --dry-run, sets POC_MEMORY_DRY_RUN=1
so all mutations are no-ops but the agent can still read the graph.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
All mutating commands (write, delete, rename, link-add, journal write,
used, wrong, not-useful, gap) check POC_MEMORY_DRY_RUN after argument
validation but before mutation. If set, process exits silently — agent
tool calls are visible in the LLM output so we can see what it tried
to do without applying changes.
Read commands (render, search, graph link, journal tail) work normally
in dry-run mode so agents can still explore the graph.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Update the observation agent prompt to:
- Check the journal around transcript timestamps before extracting
- Link extractions back to relevant journal entries
- Use poc-memory tools directly (search, render, write, link-add)
- Prefer REFINE over WRITE_NODE
- Simplified and focused prompt
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Wire select_conversation_fragments to use store.is_segment_mined()
instead of scanning _observed-transcripts stub nodes. Segments are
now marked AFTER the agent succeeds (via mark_observation_done),
not before — so failed runs don't lose segments.
Fragment IDs flow through the Resolved.keys → AgentBatch.node_keys
path so run_and_apply_with_log can mark them post-success.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
