chore: initial snapshot for gitea/github upload
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"""
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Dynamic configuration class generator for JSON-based providers.
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"""
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from typing import Any, Coroutine, List, Literal, Optional, Tuple, Union, overload
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from litellm._logging import verbose_logger
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from litellm.litellm_core_utils.prompt_templates.common_utils import (
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handle_messages_with_content_list_to_str_conversion,
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)
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from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig
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from litellm.llms.openai_like.chat.transformation import OpenAILikeChatConfig
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from litellm.secret_managers.main import get_secret_str
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from litellm.types.llms.openai import AllMessageValues
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from .json_loader import SimpleProviderConfig
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def create_config_class(provider: SimpleProviderConfig):
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"""Generate config class dynamically from JSON configuration"""
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# Choose base class
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base_class: type = (
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OpenAIGPTConfig if provider.base_class == "openai_gpt" else OpenAILikeChatConfig
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)
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class JSONProviderConfig(base_class): # type: ignore[valid-type,misc]
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@overload
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def _transform_messages(
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self, messages: List[AllMessageValues], model: str, is_async: Literal[True]
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) -> Coroutine[Any, Any, List[AllMessageValues]]:
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...
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@overload
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def _transform_messages(
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self,
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messages: List[AllMessageValues],
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model: str,
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is_async: Literal[False] = False,
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) -> List[AllMessageValues]:
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...
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def _transform_messages(
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self, messages: List[AllMessageValues], model: str, is_async: bool = False
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) -> Union[List[AllMessageValues], Coroutine[Any, Any, List[AllMessageValues]]]:
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"""Transform messages based on special_handling config"""
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# Handle content list to string conversion if configured
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if provider.special_handling.get("convert_content_list_to_string"):
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messages = handle_messages_with_content_list_to_str_conversion(messages)
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if is_async:
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return super()._transform_messages(
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messages=messages, model=model, is_async=True
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)
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else:
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return super()._transform_messages(
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messages=messages, model=model, is_async=False
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)
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def _get_openai_compatible_provider_info(
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self, api_base: Optional[str], api_key: Optional[str]
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) -> Tuple[Optional[str], Optional[str]]:
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"""Get API base and key from JSON config"""
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# Resolve base URL
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resolved_base = api_base
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if not resolved_base and provider.api_base_env:
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resolved_base = get_secret_str(provider.api_base_env)
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if not resolved_base:
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resolved_base = provider.base_url
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# Resolve API key
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resolved_key = api_key or get_secret_str(provider.api_key_env)
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return resolved_base, resolved_key
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def get_complete_url(
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self,
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api_base: Optional[str],
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api_key: Optional[str],
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model: str,
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optional_params: dict,
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litellm_params: dict,
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stream: Optional[bool] = None,
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) -> str:
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"""Build complete URL for the API endpoint"""
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if not api_base:
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api_base = provider.base_url
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if api_base is None:
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raise ValueError(f"api_base is required for provider {provider.slug}")
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if not api_base.endswith("/chat/completions"):
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api_base = f"{api_base}/chat/completions"
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return api_base
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def get_supported_openai_params(self, model: str) -> list:
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"""Get supported OpenAI params, excluding tool-related params for models
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that don't support function calling."""
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from litellm.utils import supports_function_calling
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supported_params = super().get_supported_openai_params(model=model)
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_supports_fc = supports_function_calling(
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model=model, custom_llm_provider=provider.slug
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)
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if not _supports_fc:
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tool_params = [
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"tools",
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"tool_choice",
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"function_call",
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"functions",
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"parallel_tool_calls",
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]
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for param in tool_params:
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if param in supported_params:
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supported_params.remove(param)
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verbose_logger.debug(
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f"Model {model} on provider {provider.slug} does not support "
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f"function calling — removed tool-related params from supported params."
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)
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return supported_params
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def map_openai_params(
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self,
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non_default_params: dict,
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optional_params: dict,
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model: str,
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drop_params: bool,
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) -> dict:
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"""Apply parameter mappings and constraints"""
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supported_params = self.get_supported_openai_params(model)
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# Apply supported params
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for param, value in non_default_params.items():
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# Check parameter mappings first
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if param in provider.param_mappings:
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optional_params[provider.param_mappings[param]] = value
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elif param in supported_params:
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optional_params[param] = value
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# Apply temperature constraints if present
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if "temperature" in optional_params:
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temp = optional_params["temperature"]
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constraints = provider.constraints
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# Clamp to max
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if "temperature_max" in constraints:
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temp = min(temp, constraints["temperature_max"])
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# Clamp to min
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if "temperature_min" in constraints:
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temp = max(temp, constraints["temperature_min"])
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# Special case: temperature_min_with_n_gt_1
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if "temperature_min_with_n_gt_1" in constraints:
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n = optional_params.get("n", 1)
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if n > 1 and temp < constraints["temperature_min_with_n_gt_1"]:
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temp = constraints["temperature_min_with_n_gt_1"]
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optional_params["temperature"] = temp
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return optional_params
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@property
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def custom_llm_provider(self) -> Optional[str]:
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return provider.slug
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return JSONProviderConfig
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_responses_config_cache: dict = {}
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def create_responses_config_class(provider: SimpleProviderConfig):
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"""Generate a Responses API config class dynamically from JSON configuration.
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Parallel to create_config_class() but for /v1/responses endpoints.
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Classes are cached per provider slug to avoid regeneration on every request.
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"""
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if provider.slug in _responses_config_cache:
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return _responses_config_cache[provider.slug]
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from litellm.llms.openai_like.responses.transformation import (
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OpenAILikeResponsesConfig,
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)
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from litellm.types.router import GenericLiteLLMParams
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class JSONProviderResponsesConfig(OpenAILikeResponsesConfig):
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@property
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def custom_llm_provider(self): # type: ignore[override]
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return provider.slug
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def validate_environment(
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self,
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headers: dict,
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model: str,
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litellm_params: Optional[GenericLiteLLMParams],
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) -> dict:
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litellm_params = litellm_params or GenericLiteLLMParams()
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api_key = litellm_params.api_key or get_secret_str(provider.api_key_env)
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if api_key:
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headers["Authorization"] = f"Bearer {api_key}"
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return headers
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def get_complete_url(
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self,
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api_base: Optional[str],
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litellm_params: dict,
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) -> str:
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if not api_base:
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if provider.api_base_env:
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api_base = get_secret_str(provider.api_base_env)
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if not api_base:
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api_base = provider.base_url
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if api_base is None:
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raise ValueError(f"api_base is required for provider {provider.slug}")
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api_base = api_base.rstrip("/")
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return f"{api_base}/responses"
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_responses_config_cache[provider.slug] = JSONProviderResponsesConfig
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return JSONProviderResponsesConfig
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