{"record":{"id":"3af7a23f2a3162cc","repo":"Fosowl/agenticSeek","slug":"empty-content-in-lm-studio-response-result","errorCode":null,"errorMessage":"Empty content in LM Studio response: {result}","messagePattern":"Empty content in LM Studio response: (.+?)","errorType":"exception","errorClass":"Exception","httpStatus":null,"severity":"error","filePath":"sources/llm_provider.py","lineNumber":404,"sourceCode":"            if response.status_code != 200:\n                raise Exception(f\"LM Studio returned status {response.status_code}: {response.text}\")\n            if not response.text.strip():\n                raise Exception(\"LM Studio returned empty response\")\n            try:\n                result = response.json()\n            except ValueError as json_err:\n                raise Exception(f\"Invalid JSON from LM Studio: {response.text[:200]}\") from json_err\n\n            if verbose:\n                print(\"Response from LM Studio:\", result)\n            choices = result.get(\"choices\", [])\n            if not choices:\n                raise Exception(f\"No choices in LM Studio response: {result}\")\n\n            message = choices[0].get(\"message\", {})\n            content = message.get(\"content\", \"\")\n            if not content:\n                raise Exception(f\"Empty content in LM Studio response: {result}\")\n            return content\n\n        except requests.exceptions.Timeout:\n            raise Exception(\"LM Studio request timed out - check if server is responsive\")\n        except requests.exceptions.ConnectionError:\n            raise Exception(f\"Cannot connect to LM Studio at {route_start} - check if server is running\")\n        except requests.exceptions.RequestException as e:\n            raise Exception(f\"HTTP request failed: {str(e)}\") from e\n        except Exception as e:\n            if \"LM Studio\" in str(e):\n                raise  # Re-raise our custom exceptions\n            raise Exception(f\"Unexpected error: {str(e)}\") from e\n\n    def openrouter_fn(self, history, verbose=False):\n        \"\"\"\n        Use OpenRouter API to generate text.\n        \"\"\"\n        client = OpenAI(api_key=self.api_key, base_url=\"https://openrouter.ai/api/v1\")","sourceCodeStart":386,"sourceCodeEnd":422,"githubUrl":"https://github.com/Fosowl/agenticSeek/blob/ae57a2357745a9706cb12d0fd76d954c84d166fa/sources/llm_provider.py#L386-L422","documentation":"lm_studio_fn extracts choices[0].message.content and raises this when the content string is empty, including the whole result. The response shape is valid but the model produced no text (e.g. it emitted only a tool call, or generation was cut off).","triggerScenarios":"choices[0].message.content is '' or missing: model returned only reasoning/tool-call fields, stop token hit immediately, or the loaded template's chat template mismatch produced no text.","commonSituations":"Using a chat template/model whose prompt format doesn't match history messages; max_tokens too small (all budget consumed by reasoning); LM Studio model loaded with an incompatible template; tool-calling enabled consuming the content field.","solutions":["Print the embedded `result` and inspect message fields (tool_calls, reasoning_content) for output placed elsewhere","Increase max_tokens in the payload and check finish_reason — 'length' means generation was truncated","Re-load the model in LM Studio with the correct chat template/preset","Ensure `history` messages use proper roles (system/user/assistant) for the loaded model","Retry with a different model to rule out a template/format incompatibility"],"exampleFix":"// before\npayload = {\"messages\": history, \"max_tokens\": 16}\n// after\npayload = {\"messages\": history, \"max_tokens\": 1024, \"temperature\": 0.7}","handlingStrategy":"validation","validationCode":"def validate_history(history):\n    assert history, \"history must not be empty\"\n    assert all(isinstance(m, dict) and m.get(\"role\") in (\"system\", \"user\", \"assistant\") and isinstance(m.get(\"content\"), str) for m in history), \"Malformed chat messages for LM Studio\"","typeGuard":"def content_is_nonempty(result) -> bool:\n    try:\n        return bool(result[\"choices\"][0][\"message\"][\"content\"])\n    except (KeyError, IndexError, TypeError):\n        return False","tryCatchPattern":"try:\n    content = provider.lm_studio_fn(history)\nexcept Exception as e:\n    if \"Empty content\" in str(e):\n        result = json.loads(str(e).split(\": \", 1)[-1])\n        tool_calls = result.get(\"choices\", [{}])[0].get(\"message\", {}).get(\"tool_calls\")\n        if tool_calls:\n            handle_tool_calls(tool_calls)\n        else:\n            raise_model_template_error()\n    else:\n        raise","preventionTips":["Use correct role/content message dicts matched to the loaded model's chat template","Set max_tokens high enough that generation isn't consumed before any text","Check finish_reason in raw responses during debugging","Test the model in LM Studio's playground with the same prompt format"],"tags":["lm-studio","empty-content","prompt","local-server"],"backgroundTag":"empty-llm-completion","analyzedSha":"ae57a2357745a9706cb12d0fd76d954c84d166fa","analyzedAt":"2026-08-30T02:49:05.834Z","schemaVersion":2},"datasetVersion":"2026-08-30T03:17:51.788Z"}