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33cf1bc4c3
- Unified flush + context injection into a single async LLM call (flush_from_messages accepts context_summary_callback) - Fixed response parsing bug: handle generator returns and Claude-format dicts from bot.call_with_tools, which previously caused all LLM summaries to silently fail (falling back to rule-based extraction) - Removed standalone context summary prompts and methods; reuse the existing [DAILY]/[MEMORY] summarization pipeline - Updated docs (zh/en/ja) to reflect the new injection behavior
82 lines
3.6 KiB
Plaintext
82 lines
3.6 KiB
Plaintext
---
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title: Short-term Memory
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description: Conversation context — message management, compression strategies, and context operations
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---
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Conversation context is the Agent's short-term memory, containing all messages in the current session (user input, Agent replies, tool calls and results). Proper context management is critical for the Agent's reasoning quality and cost control.
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## Context Structure
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Each conversation turn consists of:
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```
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User message → Agent thinking → Tool call → Tool result → ... → Agent final reply
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```
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A single turn may include multiple tool calls (controlled by `agent_max_steps`). All tool calls and results are retained in context until compressed or trimmed.
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## Key Configuration
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| Parameter | Description | Default |
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| --- | --- | --- |
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| `agent_max_context_tokens` | Maximum context token budget | `50000` |
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| `agent_max_context_turns` | Maximum conversation turns in context | `20` |
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| `agent_max_steps` | Maximum decision steps per turn (tool call count) | `15` |
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Configurable via `config.json` or the `/config` chat command.
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## Compression Strategy
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When context exceeds limits, the system automatically compresses to free space. The process has multiple stages:
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### 1. Tool Result Truncation
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Before each decision loop, the system checks tool call results in historical turns. Results exceeding **20,000 characters** are truncated, keeping only the beginning and end with a truncation notice. Current turn results are not affected.
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### 2. Turn Trimming
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When conversation turns exceed `agent_max_context_turns`:
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- The **oldest half** of complete turns is trimmed (preserving tool call chain integrity)
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- Trimmed messages are summarized by LLM and **written to the daily memory file**
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- Once the LLM summary is ready, it is also **injected into the first user message** of the retained context, helping the model maintain conversational continuity
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- Summary injection runs asynchronously in the background and takes effect from the next turn onward
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### 3. Token Budget Trimming
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After turn trimming, if tokens still exceed the budget:
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- **Fewer than 5 turns**: All turns undergo **text compression** — each turn keeps only the first user text and last Agent reply, removing intermediate tool call chains
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- **5 or more turns**: The **first half** of turns is trimmed again, with discarded content written to memory and a context summary injected
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### 4. Overflow Emergency Handling
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When the model API returns a context overflow error:
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1. All current messages are summarized and written to memory
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2. Aggressive trimming is applied (tool results limited to 10K chars, user text to 10K, max 5 turns)
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3. If still overflowing, the entire conversation context is cleared
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## Session Persistence
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Conversation messages are persisted to a local database, automatically restored after service restart. Restore strategy:
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- Restores the most recent **`max(3, max_context_turns / 6)`** turns
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- Only retains each turn's **user text and Agent final reply**, not intermediate tool call chains
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- Sessions older than **30 days** are automatically cleaned up
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## Commands
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Use these commands in chat to manage context:
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| Command | Description |
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| --- | --- |
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| `/context` | View current context statistics (message count, role distribution, total characters) |
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| `/context clear` | Clear current session context |
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| `/config agent_max_context_tokens 80000` | Adjust context token budget |
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| `/config agent_max_context_turns 30` | Adjust context turn limit |
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<Tip>
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After clearing context, the Agent "forgets" previous conversation content. Content that was already written to long-term memory can still be retrieved via memory search.
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</Tip>
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