langchain - 💡(How to fix) Fix Progress-aware termination: detect no-progress loops in agent tool execution [4 comments, 3 participants]

langchain2026-03-21 08:10:09

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langchain-ai/langchain#36139•Fetched 2026-04-08 01:08:00

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Error Message

Add an optional progress-aware termination guard that detects when an agent is not making progress (e.g., repeating the same tool call + same error) and stops execution early.

same tool + same args + same error

Root Cause

Iteration limits: stop late, not early
Fix root causes: incomplete; failures still recur
Tool call limits: count-based, not pattern-based

Code Example

search_db({invalid_args}) → ValidationError
search_db({invalid_args}) → ValidationError
search_db({invalid_args}) → ValidationError

RAW_BUFFERClick to expand / collapse

Checked other resources

This is a feature request, not a bug report or usage question.
I added a clear and descriptive title that summarizes the feature request.
I used the GitHub search to find a similar feature request and didn't find it.
I checked the LangChain documentation and API reference to see if this feature already exists.
This is not related to the langchain-community package.

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Feature Description

Add an optional progress-aware termination guard that detects when an agent is not making progress (e.g., repeating the same tool call + same error) and stops execution early.

Current safeguards (recursion/tool-call limits) only cap total steps. They do not detect stuck states.

Use Case

Observed patterns in existing issues:

repeated invalid tool calls (#7440, #22545)
repeated validation failures (#35514)
repeated tool use without new results (#26019, #20693)

Example:

search_db({invalid_args}) → ValidationError
search_db({invalid_args}) → ValidationError
search_db({invalid_args}) → ValidationError

The agent makes no progress but continues until max_iterations.

Proposed Solution

Introduce a middleware (e.g., ProgressGuardMiddleware) that:

Detects no-progress patterns:

same tool + same args + same error
repeated identical actions or outputs
no new intermediate state

Behavior:

track last N steps
if no change for K steps → terminate early
return reason: no_progress_detected

Config:

window size (N)
threshold (K)
strategy: terminate / fallback / message

Alternatives Considered

Alternatives Considered

Iteration limits: stop late, not early
Fix root causes: incomplete; failures still recur
Tool call limits: count-based, not pattern-based

Additional Context

Related issues:

#7440, #22545, #35514 → repeated failures
#26019, #20693 → repeated non-productive calls

Common pattern: agent continues despite no progress

This adds a pattern-based guard to complement existing limits.

extent analysis

Fix Plan

To implement the progress-aware termination guard, we will introduce a ProgressGuardMiddleware that detects no-progress patterns and terminates the agent early.

Step-by-Step Solution

Create the ProgressGuardMiddleware class:

class ProgressGuardMiddleware: def init(self, window_size, threshold, strategy): self.window_size = window_size self.threshold = threshold self.strategy = strategy self.step_history = []

2. **Implement the `detect_no_progress` method**:
```python
def detect_no_progress(self, current_step):
 self.step_history.append(current_step)
 if len(self.step_history) > self.window_size:
     self.step_history.pop(0)
 if len(self.step_history) >= self.threshold:
     last_steps = self.step_history[-self.threshold:]
     if all(step == current_step for step in last_steps):
         return True
 return False

Integrate the ProgressGuardMiddleware with the agent:

def execute_agent(agent, max_iterations): progress_guard = ProgressGuardMiddleware(window_size=5, threshold=3, strategy="terminate") for i in range(max_iterations): current_step = agent.execute() if progress_guard.detect_no_progress(current_step): # Terminate the agent early return "no_progress_detected" return "max_iterations_reached"

4. **Configure the `ProgressGuardMiddleware`**:
* Set the `window_size` to control the number of previous steps to track.
* Set the `threshold` to determine the number of consecutive identical steps required to detect no progress.
* Set the `strategy` to choose the behavior when no progress is detected (e.g., "terminate", "fallback", or "message").

### Verification
To verify that the fix worked, you can test the `ProgressGuardMiddleware` with different scenarios, such as:

* Repeated invalid tool calls with the same error.
* Repeated validation failures.
* Repeated tool use without new results.

Check that the agent terminates early and returns the "no_progress_detected" reason when no progress is detected.

### Extra Tips
* Adjust the `window_size` and `threshold` parameters to balance between detecting no-progress patterns and allowing the agent to explore different solutions.
* Consider adding additional strategies for handling no-progress situations, such as falling back to a previous state or sending a message to the user.
* Monitor the agent's behavior and adjust the `ProgressGuardMiddleware` configuration as needed to ensure optimal performance.

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#api #ssr #installation #tensor shape #autograd error #mixed precision #training loop #device allocation

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langchain - 💡(How to fix) Fix Progress-aware termination: detect no-progress loops in agent tool execution [4 comments, 3 participants]

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langchain - 💡(How to fix) Fix Progress-aware termination: detect no-progress loops in agent tool execution [4 comments, 3 participants]

Recommended Tools

GitHub issue graph ai analysis

Error Message

Root Cause

Code Example

Checked other resources

Package (Required)

Feature Description

Use Case

Proposed Solution

Alternatives Considered

Additional Context

extent analysis

Fix Plan

Step-by-Step Solution

Still need to ship something?

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TRENDING