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fix(honcho): move context injection from system prompt to prefetch, fix honcho_context crash
- system_prompt_block() now returns static header only (matching ABC contract) All other providers already did this; Honcho was the only one baking live user data into system prompt, freezing it on turn 1 forever - prefetch() assembles two layers: Layer 1: base context (representation + card) from peer.context(), cached and refreshed on context_cadence (not frozen) Layer 2: dialectic supplement, refreshed on dialectic_cadence - Context and dialectic cadence now checked independently in queue_prefetch() Previously context refresh was gated behind dialectic cadence - Fix honcho_context tool crash: Honcho SDK Message objects use .peer_id not .role — was silently returning 'No context available yet' due to AttributeError caught by broad except
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Erosika
parent
af5bbda7d2
commit
ef7f31562b
2 changed files with 64 additions and 36 deletions
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@ -196,9 +196,9 @@ class HonchoMemoryProvider(MemoryProvider):
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# B1: recall_mode — set during initialize from config
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self._recall_mode = "hybrid" # "context", "tools", or "hybrid"
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# B4: First-turn context baking
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self._first_turn_context: Optional[str] = None
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self._first_turn_lock = threading.Lock()
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# Base context cache — refreshed on context_cadence, not frozen
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self._base_context_cache: Optional[str] = None
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self._base_context_lock = threading.Lock()
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# B5: Cost-awareness turn counting and cadence
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self._turn_count = 0
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@ -447,9 +447,9 @@ class HonchoMemoryProvider(MemoryProvider):
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def system_prompt_block(self) -> str:
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"""Return system prompt text, adapted by recall_mode.
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B4: On the FIRST call, fetch and bake the full Honcho context
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(user representation, peer card, AI representation, continuity synthesis).
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Subsequent calls return the cached block for prompt caching stability.
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Returns only the mode header and tool instructions — static text
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that doesn't change between turns (prompt-cache friendly).
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Live context (representation, card) is injected via prefetch().
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"""
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if self._cron_skipped:
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return ""
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@ -463,20 +463,6 @@ class HonchoMemoryProvider(MemoryProvider):
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)
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return ""
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# ----- B4: First-turn context baking -----
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first_turn_block = ""
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if self._recall_mode in ("context", "hybrid"):
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with self._first_turn_lock:
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if self._first_turn_context is None:
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# First call — fetch and cache
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try:
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ctx = self._manager.get_prefetch_context(self._session_key)
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self._first_turn_context = self._format_first_turn_context(ctx) if ctx else ""
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except Exception as e:
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logger.debug("Honcho first-turn context fetch failed: %s", e)
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self._first_turn_context = ""
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first_turn_block = self._first_turn_context
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# ----- B1: adapt text based on recall_mode -----
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if self._recall_mode == "context":
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header = (
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@ -504,12 +490,14 @@ class HonchoMemoryProvider(MemoryProvider):
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"honcho_conclude to save facts about the user."
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)
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if first_turn_block:
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return f"{header}\n\n{first_turn_block}"
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return header
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def prefetch(self, query: str, *, session_id: str = "") -> str:
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"""Return prefetched dialectic context from background thread.
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"""Return base context (representation + card) plus dialectic supplement.
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Assembles two layers:
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1. Base context from peer.context() — cached, refreshed on context_cadence
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2. Dialectic supplement — cached, refreshed on dialectic_cadence
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B1: Returns empty when recall_mode is "tools" (no injection).
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B5: Respects injection_frequency — "first-turn" returns cached/empty after turn 0.
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@ -526,14 +514,51 @@ class HonchoMemoryProvider(MemoryProvider):
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if self._injection_frequency == "first-turn" and self._turn_count > 0:
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return ""
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parts = []
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# ----- Layer 1: Base context (representation + card) -----
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# On first call, fetch synchronously so turn 1 isn't empty.
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# After that, serve from cache and refresh in background on cadence.
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with self._base_context_lock:
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if self._base_context_cache is None:
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# First call — synchronous fetch
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try:
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ctx = self._manager.get_prefetch_context(self._session_key)
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self._base_context_cache = self._format_first_turn_context(ctx) if ctx else ""
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self._last_context_turn = self._turn_count
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except Exception as e:
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logger.debug("Honcho base context fetch failed: %s", e)
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self._base_context_cache = ""
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base_context = self._base_context_cache
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# Check if background context prefetch has a fresher result
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if self._manager:
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fresh_ctx = self._manager.pop_context_result(self._session_key)
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if fresh_ctx:
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formatted = self._format_first_turn_context(fresh_ctx)
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if formatted:
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with self._base_context_lock:
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self._base_context_cache = formatted
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base_context = formatted
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if base_context:
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parts.append(base_context)
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# ----- Layer 2: Dialectic supplement -----
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if self._prefetch_thread and self._prefetch_thread.is_alive():
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self._prefetch_thread.join(timeout=3.0)
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with self._prefetch_lock:
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result = self._prefetch_result
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dialectic_result = self._prefetch_result
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self._prefetch_result = ""
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if not result:
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if dialectic_result and dialectic_result.strip():
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parts.append(dialectic_result)
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if not parts:
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return ""
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result = "\n\n".join(parts)
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# ----- Port #3265: token budget enforcement -----
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result = self._truncate_to_budget(result)
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@ -554,9 +579,11 @@ class HonchoMemoryProvider(MemoryProvider):
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return truncated + " …"
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def queue_prefetch(self, query: str, *, session_id: str = "") -> None:
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"""Fire a background dialectic query for the upcoming turn.
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"""Fire background prefetch threads for the upcoming turn.
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B5: Checks cadence before firing background threads.
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B5: Checks cadence independently for dialectic and context refresh.
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Context refresh updates the base layer (representation + card).
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Dialectic fires the LLM reasoning supplement.
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"""
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if self._cron_skipped:
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return
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@ -567,6 +594,15 @@ class HonchoMemoryProvider(MemoryProvider):
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if self._recall_mode == "tools":
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return
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# ----- Context refresh (base layer) — independent cadence -----
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if self._context_cadence <= 1 or (self._turn_count - self._last_context_turn) >= self._context_cadence:
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self._last_context_turn = self._turn_count
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try:
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self._manager.prefetch_context(self._session_key, query)
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except Exception as e:
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logger.debug("Honcho context prefetch failed: %s", e)
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# ----- Dialectic prefetch (supplement layer) -----
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# B5: cadence check — skip if too soon since last dialectic call
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if self._dialectic_cadence > 1:
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if (self._turn_count - self._last_dialectic_turn) < self._dialectic_cadence:
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@ -592,14 +628,6 @@ class HonchoMemoryProvider(MemoryProvider):
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)
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self._prefetch_thread.start()
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# Also fire context prefetch if cadence allows
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if self._context_cadence <= 1 or (self._turn_count - self._last_context_turn) >= self._context_cadence:
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self._last_context_turn = self._turn_count
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try:
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self._manager.prefetch_context(self._session_key, query)
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except Exception as e:
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logger.debug("Honcho context prefetch failed: %s", e)
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def on_turn_start(self, turn_number: int, message: str, **kwargs) -> None:
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"""Track turn count for cadence and injection_frequency logic."""
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self._turn_count = turn_number
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@ -942,7 +942,7 @@ class HonchoSessionManager:
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if ctx.messages:
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recent = ctx.messages[-10:] # last 10 messages
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result["recent_messages"] = [
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{"role": m.role, "content": m.content[:500]}
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{"role": getattr(m, "peer_id", "unknown"), "content": (m.content or "")[:500]}
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for m in recent
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]
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