Reliability Issues in Parsing LLM Outputs

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Hello everyone,

I wanted to share an issue I’ve been facing while using Cursor. The primary issue is that the output generated by the LLM often does not follow the required format (I assume) consistently. This becomes problematic because Cursor IDE seems to rely on precise output formatting/context to interpret and apply changes accurately. When outputs are incomplete or do not match the expected structure, the local model struggles to identify the correct file segments for editing, leading to errors:

  • Not applying the edit.
  • Duplicating the content.
  • Deleting large portions of the file.

To mitigate this, I’ve been using the following prompt to remind the LLM of formatting expectations:

Prompt for Consistent Output Formatting

During the de interaction:

Unfortunately, your last response did not follow the expected format.

We are interacting through an AI-driven IDE interface that enables a small local model to read your outputs and apply necessary edits to specific files. Therefore, it is essential to follow the instructions regarding the expected output format precisely. 

Including a small excerpt from the current file before and after the changes you suggest is always helpful, as it allows the local model to pinpoint where modifications or additions should be made.

Example:

.```
// ... Previous content remains unchanged

{excerpt; 2 or 3 lines of the existing content immediately before the intended change}

{intended addition or modification}

{excerpt; 2 or 3 lines of the existing content immediately after the intended change}

// ... Following content remains unchanged
.```

Note: The comment format must start with '// ...'

---

Could you please provide your entire output again, ensuring it is in the correct format this time?

Rules or System Prompt:

We are interacting through an AI-driven IDE interface that enables a small local model to read your outputs and apply necessary edits to specific files. Therefore, it is essential to follow the instructions regarding the expected output format precisely. 

Include a small excerpt from the current file before and after the intended changes. This allows the local model to pinpoint where modifications or additions should be made.

Example:
.```
// ... Previous content remains unchanged

{excerpt; 2 or 3 lines of the existing content immediately before the intended change}

{intended addition or modification}

{excerpt; 2 or 3 lines of the existing content immediately after the intended change}

// ... Following content remains unchanged
.```

Note: The comment format must start with '// ...'

This prompt helps ensure clearer communication between the LLM and Cursor IDE. However, relying on reminders or additional prompts shouldn’t be necessary for seamless operation. It would be immensely beneficial if the developers could address this issue by improving the IDE’s ability to parse and interpret LLM outputs more robustly, even when the LLM goes rogue.

Has anyone else encountered similar challenges or found alternative solutions? I’d appreciate any insights or suggestions!

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