The /score endpoint was receiving chat-format messages which had to go
through the chat template tokenizer — this was failing with "System
message must be first" errors because the AST structure doesn't map
cleanly to chat message format.
Send raw token IDs via the new `prompt` field instead, matching what
the /completions endpoint already does. The vLLM score endpoint finds
assistant boundaries by scanning for <|im_start|>assistant token
patterns, so no message-level metadata is needed.
Also includes identity and journal sections in the scored context,
matching what the model actually sees during inference.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Scoring calls the /score endpoint directly via HTTP, bypassing the
stream_completion path. These requests had no priority field, so they
could preempt interactive work. Set priority=5 (between subconscious
agents at 2 and unconscious at 10).
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Made StreamToken pub (was pub(crate), needed by context.rs).
Removed dead API_CLIENT, get_client, sampling/priority fields
from oneshot. Suppressed pre-existing SkipIndex warning in learn.rs.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Bulk replaced Arc<Mutex<Agent>> with Arc<Agent> across all files.
Fixed control.rs, memory.rs tool handlers. Fixed oneshot Backend.
Remaining errors are all agent.lock() → agent.state.lock() or
agent.context.lock() in mind/, user/, and a few in mod.rs.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Add agent/tokenizer.rs with global Qwen 3.5 tokenizer that generates
actual token IDs including chat template wrapping. ContextEntry now
stores token_ids: Vec<u32> instead of tokens: usize — the count is
derived from the length.
ContextEntry::new() tokenizes automatically via the global tokenizer.
ContextSection::push_entry() takes a raw ConversationEntry and
tokenizes it. set_message() re-tokenizes without needing an external
tokenizer parameter.
Token IDs include the full chat template: <|im_start|>role\ncontent
<|im_end|>\n — so concatenating token_ids across entries produces a
ready-to-send prompt for vLLM's /v1/completions endpoint.
The old tiktoken CoreBPE is now unused on Agent (will be removed in
a followup). Token counts are now exact for Qwen 3.5 instead of the
~85-90% approximation from cl100k_base.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Use cumulative token position instead of entry index for the scoring
cutoff. This reflects actual context usage — a few large entries
near the end won't skew the boundary.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Signed-off-by: Kent Overstreet <kent.overstreet@linux.dev>
score_memories_incremental now takes an async callback that fires
after each memory is scored. The callback:
- Writes the score to the conversation entry via set_score()
- Persists to memory-scores.json immediately
- Notifies the UI so the context screen updates live
Scoring no longer batches — each score is visible and persisted
as it completes. Does not touch the memory store.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
New types — not yet wired to callers:
- ContextEntry: wraps ConversationEntry with cached token count and
timestamp
- ContextSection: named group of entries with cached token total.
Private entries/tokens, read via entries()/tokens().
Mutation via push(entry), set(index, entry), del(index).
- ContextState: system/identity/journal/conversation sections + working_stack
- ConversationEntry::System variant for system prompt entries
Token counting happens once at push time. Sections maintain their
totals incrementally via push/set/del. No more recomputing from
scratch on every budget check.
Does not compile — callers need updating.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Only Message, Role, MessageContent, ContentPart, ToolCall,
FunctionCall, Usage, ImageUrl are pub-exported from agent::api.
Internal types (ChatRequest, ChatCompletionChunk, ChunkChoice,
Delta, ReasoningConfig, ToolCallDelta, FunctionCallDelta) are
pub(crate) — invisible outside the crate.
All callers updated to import from agent::api:: instead of
agent::api::types::.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
New src/agent/api/http.rs: ~240 lines, supports GET/POST, JSON/form
bodies, SSE streaming via chunk(), TLS via rustls. No tracing dep.
Removes reqwest from the main crate and telegram channel crate.
Cargo.lock drops ~900 lines of transitive dependencies.
tracing now only pulled in by tui-markdown.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Streaming text now goes directly to agent entries via append_streaming().
sync_from_agent diffs the growing entry each tick. The streaming entry
is popped when the response completes; build_response_message pushes
the final version.
All status feedback uses RAII ActivityGuards:
- push_activity() for long-running work (thinking, streaming, scoring)
- notify() for instant feedback (compacted, DMN state changes, commands)
- Guards auto-remove on Drop, appending "(complete)" and lingering 5s
- expire_activities() cleans up timed-out notifications on render tick
UiMessage enum reduced to a single Info variant with zero sends.
The channel infrastructure remains for now (Mind/Agent still take
UiSender in signatures) — mechanical cleanup for a follow-up.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Reasoning tokens: dropped for now, will land in context entries later.
Debug sends: converted to dbglog! macro (writes to debug.log).
Activity: now a field on Agent, set directly, read by UI via try_lock.
score_memories_incremental takes agent Arc for activity writes.
UiMessage down to 2 variants: TextDelta, Info.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Status bar reads directly from Agent and MindState on each render tick.
Activity is now a field on Agent — set by agent code directly, read by
UI via try_lock. DmnAnnotation, ContextInfoUpdate, AgentUpdate were
already dead (no senders).
UiMessage down to 4 variants: TextDelta, Reasoning, Debug, Info.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
