Summary

The nf-llm-debugger plugin hooks directly into the Nextflow runtime engine to capture process execution failures (such as non-zero exit codes, out-of-memory events, or command errors). It retrieves the failed task context and log outputs, compiles them into a structured report, and queries an OpenAI-compatible Large Language Model (LLM) API (such as Llamafile, Ollama, OpenAI, or LocalAI) to generate an instantaneous, highly accurate error diagnosis.

Key Features:

• Automatic Runtime Interception: Monitors the task execution lifecycle (TraceObserver) and automatically analyzes errors.
• Universal Compatibility: Works with any local or remote OpenAI-compatible completion endpoint (/v1/chat/completions).
• No-Key Local Defaults: Configured out-of-the-box to use local, offline LLMs running via Llamafile or Ollama.
• Actionable Diagnoses: Translates raw stack traces and OS exit codes (like 126, 127, 137) into human-readable steps.

Get Started

1. Requirements

• Nextflow 24.04.0 or newer
• Java 17 or newer

2. Enable the Plugin

Add the plugin declaration to the plugins block inside your nextflow.config:

plugins {
    id 'nf-llm-debugger@1.0.7'
}

3. Configure Your LLM Endpoint and Context

Define your API parameters inside the params block of your nextflow.config. You can specify a preset provider or configure a custom API URL using a single parameter:

params {
    // Can be a preset: 'gemini', 'claude', 'chatgpt', 'ollama', 'local'
    // Or a custom URL: e.g., 'http://localhost:8080/v1' (auto-detects provider based on URL/model)
    llm_endpoint = 'chatgpt' 

    // Optional: Only needed to customize the model or troubleshooting docs
    llm_model = 'gpt-4o-mini' 
    llm_docs = 'nf-debugger-docs.md' 
}

Example for Gemini preset:

params {
    llm_endpoint = 'gemini'
    // Optional: customize model (defaults to gemini-1.5-flash)
    llm_model = 'gemini-2.5-flash-lite'
    llm_docs = 'nf-debugger-docs.md'                          
}

If your LLM endpoint requires authentication, export the corresponding API key in your shell environment:

• Gemini: export GEMINI_API_KEY="your-gemini-key"
• Claude/Anthropic: export ANTHROPIC_API_KEY="your-anthropic-key"
• ChatGPT/OpenAI: export OPENAI_API_KEY="your-openai-key"
• Other/Local: export LLM_API_KEY="your-api-key"

Examples

1. Deliberately Failing Pipeline

Below is a simple Nextflow pipeline (main.nf) designed to trigger an error by attempting to read a non-existent file:

nextflow.enable.dsl=2

process failProcess {
    script:
    """
    echo "Starting a process that will fail..."
    cat nonexistent_file.txt
    """
}

workflow {
    failProcess()
}

2. Expected Output with LLM Diagnosis

When you run the pipeline above with nf-llm-debugger enabled:

nextflow run main.nf

The plugin automatically intercepts the task failure, sends the context to the configured LLM, and prints a structured diagnosis directly to the console:

executor >  local (1)
[03/4f4d68] failProcess | 0 of 1 ✘
🤖 [nf-llm-debugger] onFlowComplete - Success: false
🤖 [nf-llm-debugger] onFlowComplete - Error: Process `failProcess` terminated with an error exit status (1)
🤖 [nf-llm-debugger] Sending error report to LLM (model: LLaMA_CPP)...

================================================================================
🤖 [nf-llm-debugger] LLM ERROR DIAGNOSIS:
================================================================================
🤖 [DIAGNOSIS] The task 'failProcess' failed because the command tried to execute
'cat nonexistent_file.txt', but the file 'nonexistent_file.txt' does not exist
in the task's working directory.

💡 SUGGESTIONS:
1. Double-check if the file name is spelled correctly in your process script.
2. If this file is an input, make sure you declared it correctly in the `input:`
   block of the process so Nextflow stages it into the work directory.
================================================================================

ERROR ~ Error executing process > 'failProcess'

Caused by:
  Process `failProcess` terminated with an error exit status (1)

License

Licensed under the MIT License.