Fosowl/agenticSeek · error · Exception

LM Studio request timed out - check if server is responsive

Error message

LM Studio request timed out - check if server is responsive

What it means

lm_studio_fn catches requests.exceptions.Timeout from the 30-second requests.post and converts it into this explicit message. It means the local LM Studio server accepted the connection but did not complete the request within 30s — the server is slow or hung.

Source

Thrown at sources/llm_provider.py:408

            try:
                result = response.json()
            except ValueError as json_err:
                raise Exception(f"Invalid JSON from LM Studio: {response.text[:200]}") from json_err

            if verbose:
                print("Response from LM Studio:", result)
            choices = result.get("choices", [])
            if not choices:
                raise Exception(f"No choices in LM Studio response: {result}")

            message = choices[0].get("message", {})
            content = message.get("content", "")
            if not content:
                raise Exception(f"Empty content in LM Studio response: {result}")
            return content

        except requests.exceptions.Timeout:
            raise Exception("LM Studio request timed out - check if server is responsive")
        except requests.exceptions.ConnectionError:
            raise Exception(f"Cannot connect to LM Studio at {route_start} - check if server is running")
        except requests.exceptions.RequestException as e:
            raise Exception(f"HTTP request failed: {str(e)}") from e
        except Exception as e:
            if "LM Studio" in str(e):
                raise  # Re-raise our custom exceptions
            raise Exception(f"Unexpected error: {str(e)}") from e

    def openrouter_fn(self, history, verbose=False):
        """
        Use OpenRouter API to generate text.
        """
        client = OpenAI(api_key=self.api_key, base_url="https://openrouter.ai/api/v1")
        if self.is_local:
            # This case should ideally not be reached if unsafe_providers is set correctly
            # and is_local is False in config for openrouter
            raise Exception("OpenRouter is not available for local use. Change config.ini")

View on GitHub (pinned to ae57a23577)

Solutions

Verify the LM Studio server is responsive (curl the /v1/models endpoint) and restart it if hung
Warm up the model with a small request before sending large prompts so first-load latency doesn't hit the 30s cap
Use a smaller/faster quantized model or enable GPU acceleration
Reduce prompt/context size
If legitimately slow, patch the timeout in lm_studio_fn (requests.post(..., timeout=30)) to a higher value

Example fix

// before
response = requests.post(route_start, json=payload, timeout=30)
// after
response = requests.post(route_start, json=payload, timeout=120)

Defensive patterns

Strategy: retry

Validate before calling

import time, requests
def wait_until_lm_studio_ready(url, timeout=120):
    deadline = time.time() + timeout
    while time.time() < deadline:
        try:
            if requests.get(f"{url}/v1/models", timeout=3).ok:
                return True
        except requests.exceptions.Timeout:
            pass
        time.sleep(2)
    return False

Try / catch

try:
    content = provider.lm_studio_fn(history)
except Exception as e:
    if "timed out" in str(e):
        time.sleep(2)
        content = provider.lm_studio_fn(history)  # one retry; server may have been loading
    else:
        raise

Prevention

Warm up the model with a tiny request before real calls (first load is slow)
Prefer GPU-accelerated or smaller quants on CPU-only hosts
Avoid concurrent long generations — LM Studio serializes requests
Raise the 30s timeout in lm_studio_fn for long-context workloads

When it happens

Trigger: requests.post(route_start, json=payload, timeout=30) exceeds 30 seconds: model loading on first request, very long context, CPU-only inference, or the server busy with another long generation.

Common situations: First request after starting LM Studio while the model is still loading; large prompt on a CPU-only machine; server serializing requests behind another slow call; swap thrashing on memory-constrained hosts.

Understand the failure class

Timeouts: ETIMEDOUT, deadlines, and hung requests — what actually expires when a request times out.

Related errors

AI-assisted analysis of Fosowl/agenticSeek@ae57a23577 (2026-08-30). Data as JSON: /api/errors/b0c7d8d1495f70ac. Report an issue: GitHub.