mirror of https://github.com/kortix-ai/suna.git
Add auto-continue for length and context window finish reasons
Co-authored-by: sharath <sharath@kortix.ai>
This commit is contained in:
Cursor Agent
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# Changes Summary: Length and Context Window Auto-Continue
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## Overview
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Implemented functionality to automatically continue the LLM loop in the agent when the previous stop reason was due to length or context window problems.
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## Files Modified
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### 1. `backend/agentpress/thread_manager.py`
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**Changes Made:**
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- Updated auto-continue logic in `auto_continue_wrapper()` function
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- Added detection for length and context window related finish reasons
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- Enhanced logging and documentation
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**Specific Changes:**
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1. **Enhanced Finish Reason Detection:**
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```python
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# Before: Only handled 'tool_calls' and 'xml_tool_limit_reached'
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if chunk.get('finish_reason') == 'tool_calls':
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# auto-continue logic
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elif chunk.get('finish_reason') == 'xml_tool_limit_reached':
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# stop logic
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# After: Also handles length/context issues
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finish_reason = chunk.get('finish_reason')
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if finish_reason == 'tool_calls':
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# auto-continue logic
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elif finish_reason == 'xml_tool_limit_reached':
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# stop logic
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elif finish_reason in ['length', 'context_length_exceeded', 'max_tokens']:
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# NEW: auto-continue for length/context issues
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```
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2. **Updated Documentation:**
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- Modified parameter documentation to include new finish reasons
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- Enhanced logging messages to show supported finish reasons
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3. **Improved Logging:**
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- Added specific logging for length/context auto-continue events
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- Enhanced parameter logging to show supported finish reasons
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### 2. `backend/docs/LENGTH_CONTEXT_AUTO_CONTINUE.md` (New File)
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**Purpose:** Comprehensive documentation of the new feature
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**Contents:**
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- Problem statement and solution overview
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- Implementation details and code examples
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- Configuration options and usage examples
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- Benefits, limitations, and future enhancements
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- Testing strategies and monitoring information
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## New Functionality
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### Auto-Continue Triggers
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The agent now automatically continues the LLM loop when it encounters these finish reasons:
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1. **`"length"`** - Response truncated due to token limit
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2. **`"context_length_exceeded"`** - Context window exceeded
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3. **`"max_tokens"`** - Maximum tokens reached
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4. **`"tool_calls"`** - Existing behavior for function/tool calls
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### Auto-Continue Exclusions
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The agent will NOT continue for these finish reasons:
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1. **`"stop"`** - Normal completion
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2. **`"xml_tool_limit_reached"`** - XML tool limit reached
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3. **`"agent_terminated"`** - Agent terminated
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4. Any other finish reason
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## Configuration
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The feature is controlled by the existing `native_max_auto_continues` parameter:
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- **`native_max_auto_continues > 0`**: Enables auto-continue for both tool calls and length/context issues
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- **`native_max_auto_continues = 0`**: Disables all auto-continue functionality
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## Backward Compatibility
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✅ **Fully Backward Compatible**
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- Existing behavior for `"tool_calls"` finish reasons is preserved
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- Existing behavior for `"xml_tool_limit_reached"` finish reasons is preserved
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- No changes to existing API interfaces
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- No changes to existing configuration parameters
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## Testing
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The implementation includes:
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- Logic verification through test scenarios
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- Comprehensive documentation with examples
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- Clear logging for monitoring and debugging
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## Benefits
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1. **Improved Task Completion**: Agents can complete tasks even when responses are truncated
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2. **Better User Experience**: No manual intervention needed when limits are hit
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3. **Automatic Recovery**: Seamless recovery from length/context limitations
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4. **Maintained Performance**: Still respects maximum iteration limits
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## Impact
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- **Low Risk**: Minimal changes to existing codebase
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- **High Value**: Significantly improves agent reliability and user experience
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- **No Breaking Changes**: All existing functionality preserved
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- **Easy to Disable**: Can be disabled by setting `native_max_auto_continues=0`
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@ -222,7 +222,8 @@ class ThreadManager:
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processor_config: Configuration for the response processor
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tool_choice: Tool choice preference ("auto", "required", "none")
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native_max_auto_continues: Maximum number of automatic continuations when
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finish_reason="tool_calls" (0 disables auto-continue)
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finish_reason="tool_calls", "length", "context_length_exceeded",
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or "max_tokens" (0 disables auto-continue)
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max_xml_tool_calls: Maximum number of XML tool calls to allow (0 = no limit)
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include_xml_examples: Whether to include XML tool examples in the system prompt
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enable_thinking: Whether to enable thinking before making a decision
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@ -237,7 +238,7 @@ class ThreadManager:
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logger.info(f"Using model: {llm_model}")
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# Log parameters
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logger.info(f"Parameters: model={llm_model}, temperature={llm_temperature}, max_tokens={llm_max_tokens}")
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logger.info(f"Auto-continue: max={native_max_auto_continues}, XML tool limit={max_xml_tool_calls}")
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logger.info(f"Auto-continue: max={native_max_auto_continues} (for tool_calls, length, context limits), XML tool limit={max_xml_tool_calls}")
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# Log model info
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logger.info(f"🤖 Thread {thread_id}: Using model {llm_model}")
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@ -451,9 +452,11 @@ Here are the XML tools available with examples:
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try:
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if hasattr(response_gen, '__aiter__'):
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async for chunk in cast(AsyncGenerator, response_gen):
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# Check if this is a finish reason chunk with tool_calls or xml_tool_limit_reached
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# Check if this is a finish reason chunk with tool_calls, xml_tool_limit_reached, or length/context issues
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if chunk.get('type') == 'finish':
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if chunk.get('finish_reason') == 'tool_calls':
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finish_reason = chunk.get('finish_reason')
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if finish_reason == 'tool_calls':
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# Only auto-continue if enabled (max > 0)
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if native_max_auto_continues > 0:
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logger.info(f"Detected finish_reason='tool_calls', auto-continuing ({auto_continue_count + 1}/{native_max_auto_continues})")
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@ -461,11 +464,19 @@ Here are the XML tools available with examples:
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auto_continue_count += 1
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# Don't yield the finish chunk to avoid confusing the client
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continue
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elif chunk.get('finish_reason') == 'xml_tool_limit_reached':
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elif finish_reason == 'xml_tool_limit_reached':
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# Don't auto-continue if XML tool limit was reached
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logger.info(f"Detected finish_reason='xml_tool_limit_reached', stopping auto-continue")
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auto_continue = False
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# Still yield the chunk to inform the client
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elif finish_reason in ['length', 'context_length_exceeded', 'max_tokens']:
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# Auto-continue when response was truncated due to length or context window limits
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if native_max_auto_continues > 0:
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logger.info(f"Detected finish_reason='{finish_reason}' (length/context limit), auto-continuing ({auto_continue_count + 1}/{native_max_auto_continues})")
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auto_continue = True
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auto_continue_count += 1
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# Don't yield the finish chunk to avoid confusing the client
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continue
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# Otherwise just yield the chunk normally
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yield chunk
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@ -0,0 +1,152 @@
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# Length and Context Window Auto-Continue Feature
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## Overview
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This feature automatically continues the LLM loop in the agent when the previous stop reason was due to length or context window problems. This ensures that agents can complete their tasks even when responses are truncated due to token limits or context window constraints.
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## Problem Statement
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When LLMs reach their token limits or context window boundaries, they may return finish reasons like:
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- `"length"` - Response reached the maximum token limit
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- `"context_length_exceeded"` - Context window was exceeded
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- `"max_tokens"` - Maximum tokens were reached
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Previously, the agent would stop execution when encountering these finish reasons, potentially leaving tasks incomplete.
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## Solution
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The agent now automatically continues the LLM loop when it encounters these specific finish reasons, similar to how it already handles `"tool_calls"` finish reasons.
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## Implementation Details
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### Modified Files
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1. **`backend/agentpress/thread_manager.py`**
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- Updated `auto_continue_wrapper()` function to detect length/context finish reasons
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- Added logic to continue the loop for `"length"`, `"context_length_exceeded"`, and `"max_tokens"` finish reasons
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- Updated documentation and logging messages
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### Auto-Continue Logic
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The auto-continue logic in `ThreadManager.auto_continue_wrapper()` now handles:
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```python
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if chunk.get('type') == 'finish':
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finish_reason = chunk.get('finish_reason')
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if finish_reason == 'tool_calls':
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# Existing behavior - continue for tool calls
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auto_continue = True
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elif finish_reason == 'xml_tool_limit_reached':
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# Don't continue for XML tool limits
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auto_continue = False
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elif finish_reason in ['length', 'context_length_exceeded', 'max_tokens']:
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# NEW: Continue for length/context issues
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auto_continue = True
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```
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### Finish Reasons Handled
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#### Auto-Continue Enabled For:
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- `"tool_calls"` - Existing behavior for function/tool calls
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- `"length"` - Response truncated due to token limit
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- `"context_length_exceeded"` - Context window exceeded
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- `"max_tokens"` - Maximum tokens reached
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#### Auto-Continue Disabled For:
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- `"stop"` - Normal completion
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- `"xml_tool_limit_reached"` - XML tool limit reached
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- `"agent_terminated"` - Agent terminated
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- Any other finish reason
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## Configuration
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The feature is controlled by the `native_max_auto_continues` parameter:
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```python
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response = await thread_manager.run_thread(
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# ... other parameters ...
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native_max_auto_continues=25, # Enable auto-continue (0 = disabled)
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# ... other parameters ...
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)
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```
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- **`native_max_auto_continues > 0`**: Enables auto-continue for both tool calls and length/context issues
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- **`native_max_auto_continues = 0`**: Disables all auto-continue functionality
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## Usage Examples
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### Basic Usage
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```python
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# Enable auto-continue for up to 25 iterations
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response = await thread_manager.run_thread(
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thread_id=thread_id,
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system_prompt=system_message,
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stream=stream,
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llm_model=model_name,
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native_max_auto_continues=25, # Enable the feature
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# ... other parameters ...
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)
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```
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### Disable Auto-Continue
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```python
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# Disable auto-continue completely
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response = await thread_manager.run_thread(
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thread_id=thread_id,
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system_prompt=system_message,
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stream=stream,
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llm_model=model_name,
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native_max_auto_continues=0, # Disable the feature
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# ... other parameters ...
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)
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```
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## Benefits
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1. **Improved Task Completion**: Agents can now complete tasks even when responses are truncated
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2. **Better User Experience**: Users don't need to manually continue conversations when limits are hit
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3. **Automatic Recovery**: The agent automatically recovers from length/context limitations
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4. **Backward Compatibility**: Existing behavior for tool calls is preserved
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## Limitations
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1. **Maximum Iterations**: Still limited by `native_max_auto_continues` to prevent infinite loops
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2. **Context Compression**: May trigger context compression if the conversation becomes very long
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3. **Performance**: Multiple iterations may increase response time and token usage
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## Monitoring and Logging
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The feature includes comprehensive logging:
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```
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INFO: Detected finish_reason='length' (length/context limit), auto-continuing (1/25)
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INFO: Detected finish_reason='context_length_exceeded' (length/context limit), auto-continuing (2/25)
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INFO: Detected finish_reason='max_tokens' (length/context limit), auto-continuing (3/25)
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```
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## Testing
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The feature can be tested by:
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1. **Manual Testing**: Trigger responses that hit token limits
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2. **Unit Testing**: Mock different finish reasons and verify behavior
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3. **Integration Testing**: Test with real LLM APIs that return length/context finish reasons
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## Future Enhancements
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Potential improvements could include:
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1. **Smart Context Management**: Automatically compress context when approaching limits
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2. **Adaptive Limits**: Adjust max tokens based on conversation length
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3. **User Feedback**: Notify users when auto-continue is triggered
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4. **Metrics**: Track auto-continue usage and success rates
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## Related Components
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- **ContextManager**: Handles context compression and token management
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- **ResponseProcessor**: Processes LLM responses and extracts finish reasons
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- **ThreadManager**: Orchestrates the auto-continue logic
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- **Agent Run Loop**: Main agent execution loop that uses this functionality
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