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>
ResponseParser::run() spawns a task that reads StreamTokens, parses
into the AST (locking context per token), and sends PendingToolCalls
through a channel. Returns (tool_rx, JoinHandle<Result>) — the turn
loop dispatches tool calls and awaits the handle for error checking.
Token IDs from vLLM are accumulated alongside text and stored directly
on AST leaves — no local re-encoding on the response path.
The turn loop no longer matches on individual stream events. It just
reads tool calls and dispatches them.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Agent is now Arc<Agent> (immutable config). ContextState and AgentState
have separate tokio::sync::Mutex locks. The parser locks only context,
tool dispatch locks only state. No contention between the two.
All callers migrated: mind/, user/, tools/, oneshot, dmn, learn.
28 tests pass, zero errors.
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>
Split Agent into immutable Agent (behind Arc) and mutable AgentState
(behind its own Mutex). ContextState has its own Mutex on Agent.
Activities moved to AgentState. new() and fork() rewritten.
All callers need mechanical updates: agent.lock().await.field →
agent.state.lock().await.field or agent.context.lock().await.method.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
API is now two files: mod.rs (430 lines) and http.rs. Contains:
Usage, StreamToken, SamplingParams, ApiClient, stream_completions,
SseReader, send_and_check. Everything else is dead and gone.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Removed all chat completions wire types that are no longer used:
ChatRequest, ReasoningConfig, ChatCompletionChunk, ChunkChoice,
Delta, FunctionCallDelta, ToolCallDelta, append_content, user_with_images.
Remaining types in api/types.rs are transitional (Message, ToolCall, etc.)
— they'll go away as outer callers migrate to AstNode.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Deleted: api/parsing.rs entirely (parsing now in context_new.rs),
stream_events (chat completions path), collect_stream, build_response_message,
log_diagnostics, tools_to_json_str, start_stream, chat_completion_stream_temp.
API layer is now just: stream_completion (token IDs in/out), SseReader,
send_and_check, and types. Zero errors in api/.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Work in progress. New turn loop uses ResponseParser + StreamToken.
Killed StreamEvent, append_streaming, finalize_streaming, streaming_index,
assemble_api_messages, working_stack. Many methods still reference old
types — fixing next.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
The parser takes &mut ContextState on feed()/finish() and pushes
completed children (content, thinking, tool calls) directly into
the assistant branch. Only PendingToolCall handles are returned
to the caller for dispatch — the caller no longer manages AST
mutation.
Tests verify by reading back from ContextState after parsing.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
feed() now returns all completed children (not just tool calls) so the
caller can push them into the AST as they arrive. finish() returns
remaining buffered children. The caller manages the assistant branch.
Added ContextState::push_child() for appending to an existing branch,
PendingToolCall for ephemeral dispatch handles, and len() for section
size queries.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Prep for wiring context_new.rs into the codebase: AstNode, NodeLeaf,
NodeBody, Role all derive Serialize/Deserialize for conversation log
persistence.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
render_into(&mut String) and token_ids_into(&mut Vec<u32>) recurse
the tree extending the output in place. Branches emit their wrapping
(im_start/role/im_end) and recurse into children — same structure in
both methods. token_ids() now composes from cached leaf tokens instead
of re-encoding the full rendered string.
Killed the AstEvent/AstIter iterator experiment — explicit recursion
is cleaner for a tree walk that isn't truly flattening.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Implemented by both AstNode and ContextState, so anything that
needs "give me the prompt" can take impl Ast.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Role is now just System/User/Assistant — maps 1:1 to the grammar.
Leaf types are NodeBody variants: Content, Thinking, ToolCall,
ToolResult, Memory, Dmn, Log. Each variant renders itself; no Role
needed on leaves. AstNode is Leaf(NodeLeaf) | Branch{role, children}.
ContextState holds four Vec<AstNode> sections directly.
Moved tool call XML parsing from api/parsing.rs into context_new.rs
so all grammar knowledge lives in one place.
Tokenizer encode() now returns empty vec when uninitialized instead
of panicking, so tests work without the tokenizer file.
26 tests: XML parsing, incremental streaming (char-by-char feeds
found and fixed a lookahead bug), rendering for all node types,
tokenizer round-trip verification.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
AstNode fields are now private with read-only accessors. All mutation
goes through ContextState methods (push, set_message, set_score, del)
which guarantee token_ids stays in sync with text on every leaf.
Also fix ResponseParser to use AstNode::tool_call() constructor,
widen parsing module visibility to pub(crate).
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
New context_new.rs with the AST-based context window design:
- AstNode: role + NodeBody (Leaf with text+token_ids, or Branch with children)
- Tokens only on leaves, branches walk children
- render() produces UTF-8, tokenize produces token IDs, same path
- ResponseParser state machine for streaming assistant responses
- Role enum covers all node types including sections
Still needs: fix remaining pattern match issues, add ContextState wrapper,
wire into mod.rs, replace old context.rs.
Does not compile yet — this is a design checkpoint.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Entries with empty token_ids (Thinking, Log) are not part of the
prompt and don't have messages. Skip them in streaming_index(),
route_entry(), and sync_from_agent() instead of calling .message()
which panics.
Using token_ids.is_empty() as the guard in streaming_index means
the check is tied to the data, not the type — any entry that
doesn't produce tokens is safely skipped.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
New stream_completions() in openai.rs sends prompt as token IDs to
the completions endpoint instead of JSON messages to chat/completions.
Handles <think> tags in the response (split into Reasoning events)
and stops on <|im_end|> token.
start_stream_completions() on ApiClient provides the same interface
as start_stream() but takes token IDs instead of Messages.
The turn loop in Agent::turn() uses completions when the tokenizer
is initialized, falling back to the chat API otherwise. This allows
gradual migration — consciousness uses completions (Qwen tokenizer),
Claude Code hook still uses chat API (Anthropic).
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Tool definitions are now pushed as a ContextEntry in the system
section at Agent construction time, formatted in the Qwen chat
template style. They're tokenized, scored, and treated like any
other context entry.
assemble_prompt_tokens() no longer takes a tools parameter —
tools are already in the context. This prepares for the switch
to /v1/completions where tools aren't a separate API field.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Remove tiktoken-rs dependency, CoreBPE field on Agent, and the
msg_token_count() function. All tokenization now goes through the
global HuggingFace tokenizer in agent/tokenizer.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>
restore_from_log called .message() on all entries including Thinking
entries, which panic. Filter them out alongside Log entries.
Also fix bail-no-competing.sh: without nullglob, when no pid-* files
exist the glob stays literal and always triggers a false bail.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
The bail-no-competing.sh script expects $1 to be the path to the
current agent's pid file so it can skip it when checking for
competing processes. But the runner wasn't passing any arguments,
so $1 was empty and the script treated every pid file (including
the agent's own) as a competing process — bailing every time.
This caused surface-observe to always bail at step 2, preventing
all memory graph maintenance (organize, observe phases) from
running.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
StreamResult now includes accumulated reasoning text. After each
stream completes, if reasoning was produced, a Thinking entry is
pushed to the conversation before the response message.
Reasoning content is visible in the context tree UI but not sent
back to the API and doesn't count against the token budget.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Thinking/reasoning content is now a first-class entry type:
- Serialized as {"thinking": "..."} in conversation log
- 0 tokens for budgeting (doesn't count against context window)
- Filtered from assemble_api_messages (not sent back to model)
- Displayed in UI with "thinking: ..." label and expandable content
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
lowest_scored_memory() now skips memories with score=None. Unscored
memories haven't been evaluated — dropping them before scored
low-value ones loses potentially important context.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
trim_entries is now a simple loop:
1. Drop duplicate memories and DMN entries
2. While over budget: if memories > 50% of entry tokens, drop
lowest-scored memory; otherwise drop oldest conversation entry
3. Snap to user message boundary
ContextBudget is gone — sections already have cached token totals:
- total_tokens() on ContextState replaces budget.total()
- format_budget() on ContextState replaces budget.format()
- trim() takes fixed_tokens: usize (system + identity + journal)
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Signed-off-by: Kent Overstreet <kent.overstreet@linux.dev>
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>
compact() already computes context_budget() — pass it to trim_entries
so it has access to all budget components without recomputing them.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Scores are saved to memory-scores.json alongside the conversation log
after each scoring run, and loaded on startup — no more re-scoring
on restart.
trim_entries now evicts lowest-scored memories first (instead of
oldest-first) when memories exceed 50% of context. The 50% threshold
stays as a heuristic for memory-vs-conversation balance until we have
a scoring signal for conversation entries too. Unscored memories get
0.0, so they're evicted before scored ones.
save_memory_scores rebuilds from current entries, so evicted memories
are automatically expired from the scores file.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Moved persistent_state from per-agent to a single shared BTreeMap on
Subconscious. All agents read/write the same state — surface's walked
keys are visible to observe and reflect, etc.
- Subconscious.state: shared BTreeMap<String, String>
- walked() derives from state["walked"] instead of separate Vec
- subconscious-state.json is now a flat key-value map
- All agent outputs merge into the shared state on completion
- Loaded on startup, saved after any agent completes
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
- Agent state (outputs) persists across runs in subconscious-state.json,
loaded on startup, saved after each run completes
- Merge semantics: each run's outputs accumulate into persistent_state
rather than replacing
- Walked keys restored from surface agent state on load
- Store::recent_by_provenance() queries nodes by agent provenance for
the store activity view
- Switch outputs from HashMap to BTreeMap for stable display ordering
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
context_state_summary() was used for both compaction decisions (just
needs token counts) and debug screen display (needs full tree with
labels). Split into:
- Agent::context_budget() -> ContextBudget: cheap token counting by
category, used by compact(), restore_from_log(), mind event loop
- ContextBudget::format(): replaces sections_budget_string() which
fragily pattern-matched on section name strings
- context_state_summary(): now UI-only, formatting code stays here
Also extracted entry_sections() as shared helper with include_memories
param — false for context_state_summary (memories have own section),
true for conversation_sections_from() (subconscious screen shows all).
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
Add provenance field to Agent, set to "agent:{name}" for forked
subconscious agents. Memory tools (write, link_add, supersede,
journal_new, journal_update) now read provenance from the Agent
context when available, falling back to "manual" for interactive use.
AutoAgent passes the forked agent to dispatch_with_agent so tools
can access it.
Co-Authored-By: Proof of Concept <poc@bcachefs.org>
The final assistant response in run_with_backend wasn't being pushed
to the backend — only intermediate step responses were. This meant
the subconscious debug screen only showed the prompt, not the full
conversation.
Now push assistant response immediately after receiving it, before
checking for next steps. Remove the duplicate push in the multi-step
path.
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>
