openrouter-debug-bundle

OpenRouter Debug Bundle

Current State

!node --version 2>/dev/null || echo 'N/A' !python3 --version 2>/dev/null || echo 'N/A'

Overview

When an OpenRouter request fails or returns unexpected results, you need a structured debug bundle: the exact request, response, headers, generation metadata, and environment info. The generation ID (gen-* prefix in response.id) is the key correlator -- it lets you look up exact cost, provider used, and latency via GET /api/v1/generation?id=.

Quick Debug: curl

# Send a request and capture full response with headers
curl -v https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -H "HTTP-Referer: https://my-app.com" \
  -H "X-Title: debug-test" \
  -d '{
    "model": "openai/gpt-4o-mini",
    "messages": [{"role": "user", "content": "Say hello"}],
    "max_tokens": 50
  }' 2>&1 | tee /tmp/openrouter-debug.txt

# Extract generation ID from response
GEN_ID=$(jq -r '.id' /tmp/openrouter-debug.txt 2>/dev/null)
echo "Generation ID: $GEN_ID"

# Look up generation metadata (exact cost, provider, latency)
curl -s "https://openrouter.ai/api/v1/generation?id=$GEN_ID" \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" | jq '.data | {
    model: .model,
    total_cost: .total_cost,
    tokens_prompt: .tokens_prompt,
    tokens_completion: .tokens_completion,
    generation_time: .generation_time,
    provider: .provider_name
  }'

Python Debug Bundle Generator

import os, json, time, platform, sys
from datetime import datetime, timezone
from dataclasses import dataclass, asdict
from typing import Optional
from openai import OpenAI, APIError
import requests as http_requests

@dataclass
class DebugBundle:
    timestamp: str
    generation_id: Optional[str]
    request_model: str
    request_messages: list
    request_params: dict
    response_status: str
    response_model: Optional[str]
    response_content: Optional[str]
    error_type: Optional[str]
    error_message: Optional[str]
    error_code: Optional[int]
    latency_ms: float
    generation_metadata: Optional[dict]
    environment: dict

    def to_json(self) -> str:
        return json.dumps(asdict(self), indent=2)

    def save(self, path: str = "debug_bundle.json"):
        with open(path, "w") as f:
            f.write(self.to_json())

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key=os.environ["OPENROUTER_API_KEY"],
    default_headers={"HTTP-Referer": "https://my-app.com", "X-Title": "my-app"},
)

def debug_request(
    messages: list[dict],
    model: str = "openai/gpt-4o-mini",
    **kwargs,
) -> DebugBundle:
    """Execute a request and capture everything for debugging."""
    env = {
        "python": sys.version,
        "platform": platform.platform(),
        "openai_sdk": getattr(__import__("openai"), "__version__", "unknown"),
    }

    start = time.monotonic()
    gen_id = None
    response_model = None
    content = None
    error_type = None
    error_msg = None
    error_code = None
    status = "success"
    gen_meta = None

    try:
        response = client.chat.completions.create(
            model=model, messages=messages, **kwargs
        )
        gen_id = response.id
        response_model = response.model
        content = response.choices[0].message.content
    except APIError as e:
        status = "error"
        error_type = type(e).__name__
        error_msg = str(e)
        error_code = e.status_code
    except Exception as e:
        status = "error"
        error_type = type(e).__name__
        error_msg = str(e)

    latency = (time.monotonic() - start) * 1000

    # Fetch generation metadata if we have an ID
    if gen_id:
        try:
            gen = http_requests.get(
                f"https://openrouter.ai/api/v1/generation?id={gen_id}",
                headers={"Authorization": f"Bearer {os.environ['OPENROUTER_API_KEY']}"},
                timeout=5,
            ).json()
            gen_meta = gen.get("data")
        except Exception:
            pass

    return DebugBundle(
        timestamp=datetime.now(timezone.utc).isoformat(),
        generation_id=gen_id,
        request_model=model,
        request_messages=messages,
        request_params={k: v for k, v in kwargs.items() if k != "messages"},
        response_status=status,
        response_model=response_model,
        response_content=content,
        error_type=error_type,
        error_message=error_msg,
        error_code=error_code,
        latency_ms=round(latency, 1),
        generation_metadata=gen_meta,
        environment=env,
    )

# Usage
bundle = debug_request(
    [{"role": "user", "content": "Test"}],
    model="anthropic/claude-3.5-sonnet",
    max_tokens=100,
)
print(bundle.to_json())
bundle.save("debug_bundle.json")

Common Debug Checks

# 1. Verify API key is valid
curl -s https://openrouter.ai/api/v1/auth/key \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" | jq '.data | {label, usage, limit, is_free_tier}'

# 2. Check if model exists
MODEL="anthropic/claude-3.5-sonnet"
curl -s https://openrouter.ai/api/v1/models | jq --arg m "$MODEL" '.data[] | select(.id == $m) | {id, context_length}'

# 3. Check OpenRouter status
curl -s https://status.openrouter.ai/api/v2/status.json | jq '.status'

Error Handling

Error	Cause	Fix
No generation ID in response	Request failed before reaching provider	Check network, verify base URL is https://openrouter.ai/api/v1
Generation metadata missing	Fetched too soon or wrong key	Wait 1-2s; use same API key that made the request
Intermittent 502/503	Upstream provider outage	Check status.openrouter.ai; try different provider
model_not_found	Model ID typo or model removed	Query /api/v1/models to verify model exists
Slow TTFT (>10s)	Model cold start or overload	Use streaming; try :floor variant for different provider

Enterprise Considerations

• Always redact API keys from debug bundles before sharing (sk-or-v1-... -> sk-or-v1-[REDACTED])
• Include the generation ID when contacting OpenRouter support -- it's the primary lookup key
• Log debug bundles to structured storage for post-incident analysis
• Set up automated debug bundle capture on 4xx/5xx responses in production
• Compare failing requests against a known-good baseline to isolate changes

References

• Examples | Errors
• Generation API | Status