ninemin.lilulab.ai

litellm.APIConnectionError — LiteLLM mapped a provider error that had no status code

litellm.APIConnectionError: APIConnectionError: <Provider>Exception - <provider message>

(The error as str(e) gives it when it comes from LiteLLM’s generic branch for OpenAI-style providers, assembled by us from two prefixes quoted as source below, with our placeholders in angle brackets. Other raise sites build a different text after litellm.APIConnectionError: .)

In its exception mapper, LiteLLM raises this after the provider call failed: it maps the provider’s exception to its own classes, and in the generic branch, when the exception has no status_code attribute and none of the earlier tests matched, the class it picks is APIConnectionError. Every claim about the library below is read off the Python source of BerriAI/litellm at tag v1.104.2, fetched on 10 October 2026, with the line of each quote given; where we draw a conclusion from those lines rather than quote them, we say so.

The generic raise

In litellm/litellm_core_utils/exception_mapping_utils.py, inside _map_openai_exception (defined at line 275), lines 515–519:

else: # if no status code then it is an APIConnectionError: https://github.com/openai/openai-python#handling-errors # exception_mapping_worked = True raise APIConnectionError( message=f"APIConnectionError: {exception_provider} - {message}",

That else: closes the chain that opens at line 307 with if ExceptionCheckers.is_error_str_rate_limit(; the branch just before it, at line 422, is elif hasattr(original_exception, "status_code"):. So this raise runs when the original exception has no status_code attribute and none of the earlier branches of that chain (lines 307–421) matched (our reading). The raise passes llm_provider=custom_llm_provider,, model=model, and litellm_debug_info=extra_information, (lines 520–522). In the same function, exception_provider is "OpenAI" + "Exception" for openai and otherwise the provider name with its first letter upper-cased plus Exception (lines 302–305). exception_type (line 2349) sends openai, text-completion-openai, custom_openai, mistral, runwayml and the providers in litellm.openai_compatible_providers to this function (the condition at lines 2458–2465).

The other sites in that file

A grep of the file for APIConnectionError( finds 9 lines: the 8 raise APIConnectionError( statements at 518, 1353, 1918, 2040, 2130, 2224, 2673 and 2680, and the construction at 2720. Besides line 518:

• Vertex — in _map_vertex_exception, line 1353, under if original_exception.status_code == 502: (line 1352); the object still reports 500 (our reading, from the class below).
• vLLM — in _map_vllm_exception, line 1918, under if original_exception.status_code == 0: (line 1917).
• Azure — in _map_azure_exception, line 2040, under elif "Connection error" in error_str: (line 2039), and line 2130, the else: (line 2128) after elif hasattr(original_exception, "status_code"): (line 2046), with the same if no status code comment as line 516.
• OpenRouter — in _map_openrouter_exception, line 2224, the else: (line 2222) of if hasattr(original_exception, "status_code"): (line 2149).
• The fallback in exception_type — lines 2673 and 2680, described in the next section.
• The mapper’s own failure — if mapping itself raised something that is not already a LiteLLM type while exception_mapping_worked was still false (lines 2712–2719), the except Exception as e: at line 2700 builds an APIConnectionError at line 2720 with llm_provider="", and model="", and raises it at line 2726.

The fallback for unmapped errors

In exception_type, after the if model or custom_llm_provider: block (line 2376) that holds the provider-specific mapping, line 2649 tests the error for a BadRequestError.__init__() message, and the else: of that test, line 2659, reads else: # ensure generic errors always return APIConnectionError=. Under it, _map_exception_by_status (line 2242) is called first; it returns without raising when the status code is not an int or is below 400, or when status_code_is_synthesized is set (lines 2251–2255). Then, lines 2672–2674:

if hasattr(original_exception, "request"): raise APIConnectionError( message=f"{exception_provider} - {error_str}",

and otherwise line 2680 raises one whose message is the original exception plus its traceback and, when should_report_bug returns true for it, a bug-report notice (lines 2681–2695). Here exception_provider is also the provider name with its first letter upper-cased plus Exception when the provider name is a non-empty string (lines 2402–2403). This message has no second APIConnectionError:, so str(e) reads litellm.APIConnectionError: <Provider>Exception - <error text> (our reading, our placeholders).

When you call a LiteLLM proxy as provider litellm_proxy, exception_type first calls extract_and_raise_litellm_exception (lines 2448–2457), which looks for r"litellm\.\w+Error" in the error text (line 232) and raises the LiteLLM class of that name, when litellm has one, with the whole text as its message (lines 236–245), so a proxy-side APIConnectionError can come back as one on the client too (our reading).

Where completion() sends it

In litellm/main.py, completion (line 5113) ends with, lines 6036–6038:

except Exception as e: ## Map to OpenAI Exception raise exception_type(

passing model, custom_llm_provider and the original exception (lines 6038–6044). acompletion (line 400) does the same at lines 709–717. exception_type returns an exception that is already one of LiteLLM’s types unchanged (lines 2357–2358), so an error mapped once is not mapped again (our reading).

The class

In litellm/exceptions.py, class APIConnectionError(openai.APIConnectionError): is at line 853. Its constructor takes message, llm_provider, model and optional request, litellm_debug_info, max_retries and num_retries (lines 854–863), then sets, lines 864–867:

self.message = f"litellm.APIConnectionError: {message}" self.llm_provider = llm_provider self.model = model self.status_code = 500

Line 869 sets self.request = httpx.Request(method="POST", url="https://api.openai.com/v1"), and line 872 calls the parent with message=self.message, request=self.request. The request argument is not used for self.request (our reading of lines 864–872). Its __str__ (lines 874–880) and __repr__ (lines 882–888) return self.message, plus LiteLLM Retried: {self.num_retries} times when num_retries is set and , LiteLLM Max Retries: {self.max_retries} when max_retries is set. We did not fetch openai.APIConnectionError, the parent in the OpenAI Python SDK.

What it looks like in the field

In stfc/goldilocks-agent#14, an issue about a resumed request losing the selected model, the reporter writes that when the resumed call goes to LiteLLM with Ollama unreachable, the stream yields ⚠️ litellm.APIConnectionError: Ollama_chatException - Cannot connect to host ....

In beenuar/AiSOC#1235, titled Fresh install never calls the bundled model: .env.example ships AISOC_LLM_API_BASE empty, the reporter writes that LiteLLM gets an empty api_base and calls localhost:11434 inside its own container, and lists litellm.APIConnectionError: Ollama_chatException - Cannot connect to host localhost:11434 under Observed.

Both texts have the shape of line 2674, not of line 519, which would add a second APIConnectionError: (our reading). We did not trace which branch Ollama errors take.

What the caller sees and can read

• str(e) and e.message — litellm.APIConnectionError: followed by the message the raise passed (line 864); str(e) adds the retry note when set (lines 874–880).
• e.status_code — 500, set by the class at line 867 for every raise, including the generic branch, where the original exception had no status code, and the Vertex 502 branch. It does not tell you what the provider returned (our reading).
• e.llm_provider, e.model — what the raise passed (lines 865–866); at line 518 the resolved provider name and the model you asked for; empty strings from the construction at line 2720.
• e.litellm_debug_info — what the raise passed, if anything (line 868). Lines 518, 2040, 2130 and 2224 pass extra_information, which exception_type starts as f"\nModel: {model}" (line 2400) and, when litellm.get_api_base returned one (line 2393), extends with f"\nAPI Base: `{_api_base}`" (line 2406).
• e.request — the stub set at line 869, not the request that failed (our reading).

What to do

• Check where the call went. No status code means LiteLLM had no HTTP status to map (our reading of line 516), so confirm the api_base — printed in e.litellm_debug_info when set — is the endpoint you meant; completion() also takes base_url: str | None = None, (main.py line 5155). Both field reports above involve an Ollama server LiteLLM could not connect to.
• Check that the endpoint is up and reachable from the host or container your code runs in — the server process, DNS, proxy and firewall (our reading). We say nothing here about any provider’s reliability.
• Read the provider part of the message. After the prefix comes <Provider>Exception - and the original error text, which says what failed, as Cannot connect to host does in both reports (our reading).
• Do not branch on e.status_code to tell this apart from a real server error; it is always 500 here. Catch the class instead (our reading, from line 867).
• Retrying only helps once the endpoint answers. main.py has completion_with_retries (lines 6047–6070), which wraps completion in tenacity.Retrying with stop_after_attempt(num_retries), num_retries defaulting to 3 (line 6056); neither Retrying call there passes a retry= condition (lines 6063–6069), so it is not specific to this class (our reading).

from litellm import completion from litellm.exceptions import APIConnectionError def call(model: str, messages: list[dict]): # Our sketch: show what LiteLLM knew when it could not map a status. try: return completion(model=model, messages=messages) except APIConnectionError as e: print("provider:", e.llm_provider, "model:", e.model) print("debug info:", e.litellm_debug_info) print(e.message) raise

(Our sketch, not library code, and not run against your version. It re-raises: there is nothing to fix in the request until the endpoint answers.)

What is behind this site

The short version: litellm.APIConnectionError is LiteLLM’s subclass of openai.APIConnectionError, raised by exception_type — in the generic OpenAI-style branch when the provider’s exception has no status_code and matched no earlier test, in Vertex, vLLM, Azure and OpenRouter branches, and as the fallback for unmapped errors. str(e) starts litellm.APIConnectionError: and e.status_code is always 500. Check the api_base and that the endpoint is reachable, and read the provider’s text at the end of the message.

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