BerriAI/litellm · error · ValueError

Error compiling prompt '{prompt_id}': {e}, prompt_spec: {pro

Error message

Error compiling prompt '{prompt_id}': {e}, prompt_spec: {prompt_spec}

What it means

Raised by GenericPromptManager.async_compile_prompt_helper (async path) as the catch-all wrapper: any Exception during the async fetch, parse, cache, or variable-application steps becomes a ValueError that also embeds the full prompt_spec in the message for diagnostics. Like the sync variant it only fires on cache misses.

Source

Thrown at litellm/integrations/generic_prompt_management/generic_prompt_manager.py:347

        try:
            # Fetch from API

            api_response: Final = await self.async_fetch_prompt_from_api(prompt_id=prompt_id, prompt_spec=prompt_spec)

            # Parse the response
            prompt_client = self._parse_api_response(prompt_id, prompt_spec, api_response)

            # Cache the result
            self._prompt_cache[cache_key] = prompt_client

            # Apply variables if provided
            if prompt_variables:
                prompt_client = self._apply_variables(prompt_client, prompt_variables)

            return prompt_client

        except Exception as e:
            raise ValueError(f"Error compiling prompt '{prompt_id}': {e}, prompt_spec: {prompt_spec}")

    def _apply_variables(
        self,
        prompt_client: PromptManagementClient,
        variables: dict[str, Any],
    ) -> PromptManagementClient:
        """
        Apply variables to the prompt template.

        This performs simple string substitution using {variable_name} syntax.

        Args:
            prompt_client: The prompt client structure
            variables: Variables to substitute

        Returns:
            Updated PromptManagementClient with variables applied
        """

View on GitHub (pinned to 6c2dcb801b)

Solutions

Parse the embedded cause between 'Error compiling prompt' and ', prompt_spec:' — it identifies the failing sub-step.
Validate that the prompt API returns the documented schema (the _parse_api_response contract) by curling the endpoint.
Supply all template variables in prompt_variables on the request.
If the prompt_spec dump in the message is too noisy, log/inspect it in your handler rather than printing the whole exception string (it may contain config details).

Defensive patterns

Strategy: try-catch

Validate before calling

async def precheck_prompt_compilation(manager, prompt_id: str, variables: dict | None) -> None:
    await manager.async_compile_prompt_helper(
        prompt_id=prompt_id,
        prompt_variables=variables,
        dynamic_callback_params={},
    )  # fail during startup, not on user requests

Try / catch

try:
    resp = await litellm.acompletion(model="prompt-model", messages=msgs, variables=vars)
except ValueError as e:
    msg = str(e)
    if msg.startswith("Error compiling prompt"):
        # do not log the whole message: it embeds prompt_spec and may be huge / contain config
        log.error("prompt compilation failed for %s", prompt_id)
        raise
    raise

Prevention

Warm/validate prompts at startup with a compile call per configured prompt_id.
Avoid dumping the raw exception string to logs — it includes the serialized prompt_spec.
Pin the prompt-management API version so response schema changes are deliberate.

When it happens

Trigger: Awaiting an async completion with prompt management where the fetch fails (network/HTTP), the API response does not match the expected schema in _parse_api_response, or _apply_variables hits an unresolvable template variable. The message includes prompt_spec, so passing a large spec produces a very long error string.

Common situations: Cold-start requests in the LiteLLM proxy against a misconfigured prompt API; schema drift after upgrading the prompt-management service; callers omitting required prompt variables on their first (uncached) request.

Related errors

AI-assisted analysis of BerriAI/litellm@6c2dcb801b (2026-08-15). Data as JSON: /api/errors/71c89a3516bdd4e2. Report an issue: GitHub.