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.

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

Background: Request timed out: what client-side request timeouts mean across libraries (Request timed out, TIMED_OUT, APITimeoutError) — this error's family across 39 libraries.

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.

Appendix: 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")

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