structure saas with tools

.venv/lib/python3.10/site-packages/litellm/llms/azure_ai/chat/handler.py

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+"""
+LLM Calling done in `openai/openai.py`
+"""

.venv/lib/python3.10/site-packages/litellm/llms/azure_ai/chat/transformation.py

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+import enum
+from typing import Any, List, Optional, Tuple, cast
+from urllib.parse import urlparse
+
+import httpx
+from httpx import Response
+
+import litellm
+from litellm._logging import verbose_logger
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    _audio_or_image_in_message_content,
+    convert_content_list_to_str,
+)
+from litellm.llms.base_llm.chat.transformation import LiteLLMLoggingObj
+from litellm.llms.openai.common_utils import drop_params_from_unprocessable_entity_error
+from litellm.llms.openai.openai import OpenAIConfig
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllMessageValues
+from litellm.types.utils import ModelResponse, ProviderField
+from litellm.utils import _add_path_to_api_base, supports_tool_choice
+
+
+class AzureFoundryErrorStrings(str, enum.Enum):
+    SET_EXTRA_PARAMETERS_TO_PASS_THROUGH = "Set extra-parameters to 'pass-through'"
+
+
+class AzureAIStudioConfig(OpenAIConfig):
+    def get_supported_openai_params(self, model: str) -> List:
+        model_supports_tool_choice = True  # azure ai supports this by default
+        if not supports_tool_choice(model=f"azure_ai/{model}"):
+            model_supports_tool_choice = False
+        supported_params = super().get_supported_openai_params(model)
+        if not model_supports_tool_choice:
+            filtered_supported_params = []
+            for param in supported_params:
+                if param != "tool_choice":
+                    filtered_supported_params.append(param)
+            return filtered_supported_params
+        return supported_params
+
+    def validate_environment(
+        self,
+        headers: dict,
+        model: str,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+    ) -> dict:
+        if api_base and self._should_use_api_key_header(api_base):
+            headers["api-key"] = api_key
+        else:
+            headers["Authorization"] = f"Bearer {api_key}"
+
+        return headers
+
+    def _should_use_api_key_header(self, api_base: str) -> bool:
+        """
+        Returns True if the request should use `api-key` header for authentication.
+        """
+        parsed_url = urlparse(api_base)
+        host = parsed_url.hostname
+        if host and (
+            host.endswith(".services.ai.azure.com")
+            or host.endswith(".openai.azure.com")
+        ):
+            return True
+        return False
+
+    def get_complete_url(
+        self,
+        api_base: Optional[str],
+        api_key: Optional[str],
+        model: str,
+        optional_params: dict,
+        litellm_params: dict,
+        stream: Optional[bool] = None,
+    ) -> str:
+        """
+        Constructs a complete URL for the API request.
+
+        Args:
+        - api_base: Base URL, e.g.,
+            "https://litellm8397336933.services.ai.azure.com"
+            OR
+            "https://litellm8397336933.services.ai.azure.com/models/chat/completions?api-version=2024-05-01-preview"
+        - model: Model name.
+        - optional_params: Additional query parameters, including "api_version".
+        - stream: If streaming is required (optional).
+
+        Returns:
+        - A complete URL string, e.g.,
+        "https://litellm8397336933.services.ai.azure.com/models/chat/completions?api-version=2024-05-01-preview"
+        """
+        if api_base is None:
+            raise ValueError(
+                f"api_base is required for Azure AI Studio. Please set the api_base parameter. Passed `api_base={api_base}`"
+            )
+        original_url = httpx.URL(api_base)
+
+        # Extract api_version or use default
+        api_version = cast(Optional[str], litellm_params.get("api_version"))
+
+        # Create a new dictionary with existing params
+        query_params = dict(original_url.params)
+
+        # Add api_version if needed
+        if "api-version" not in query_params and api_version:
+            query_params["api-version"] = api_version
+
+        # Add the path to the base URL
+        if "services.ai.azure.com" in api_base:
+            new_url = _add_path_to_api_base(
+                api_base=api_base, ending_path="/models/chat/completions"
+            )
+        else:
+            new_url = _add_path_to_api_base(
+                api_base=api_base, ending_path="/chat/completions"
+            )
+
+        # Use the new query_params dictionary
+        final_url = httpx.URL(new_url).copy_with(params=query_params)
+
+        return str(final_url)
+
+    def get_required_params(self) -> List[ProviderField]:
+        """For a given provider, return it's required fields with a description"""
+        return [
+            ProviderField(
+                field_name="api_key",
+                field_type="string",
+                field_description="Your Azure AI Studio API Key.",
+                field_value="zEJ...",
+            ),
+            ProviderField(
+                field_name="api_base",
+                field_type="string",
+                field_description="Your Azure AI Studio API Base.",
+                field_value="https://Mistral-serverless.",
+            ),
+        ]
+
+    def _transform_messages(
+        self,
+        messages: List[AllMessageValues],
+        model: str,
+    ) -> List:
+        """
+        - Azure AI Studio doesn't support content as a list. This handles:
+            1. Transforms list content to a string.
+            2. If message contains an image or audio, send as is (user-intended)
+        """
+        for message in messages:
+            # Do nothing if the message contains an image or audio
+            if _audio_or_image_in_message_content(message):
+                continue
+
+            texts = convert_content_list_to_str(message=message)
+            if texts:
+                message["content"] = texts
+        return messages
+
+    def _is_azure_openai_model(self, model: str, api_base: Optional[str]) -> bool:
+        try:
+            if "/" in model:
+                model = model.split("/", 1)[1]
+            if (
+                model in litellm.open_ai_chat_completion_models
+                or model in litellm.open_ai_text_completion_models
+                or model in litellm.open_ai_embedding_models
+            ):
+                return True
+
+        except Exception:
+            return False
+        return False
+
+    def _get_openai_compatible_provider_info(
+        self,
+        model: str,
+        api_base: Optional[str],
+        api_key: Optional[str],
+        custom_llm_provider: str,
+    ) -> Tuple[Optional[str], Optional[str], str]:
+        api_base = api_base or get_secret_str("AZURE_AI_API_BASE")
+        dynamic_api_key = api_key or get_secret_str("AZURE_AI_API_KEY")
+
+        if self._is_azure_openai_model(model=model, api_base=api_base):
+            verbose_logger.debug(
+                "Model={} is Azure OpenAI model. Setting custom_llm_provider='azure'.".format(
+                    model
+                )
+            )
+            custom_llm_provider = "azure"
+        return api_base, dynamic_api_key, custom_llm_provider
+
+    def transform_request(
+        self,
+        model: str,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        headers: dict,
+    ) -> dict:
+        extra_body = optional_params.pop("extra_body", {})
+        if extra_body and isinstance(extra_body, dict):
+            optional_params.update(extra_body)
+        optional_params.pop("max_retries", None)
+        return super().transform_request(
+            model, messages, optional_params, litellm_params, headers
+        )
+
+    def transform_response(
+        self,
+        model: str,
+        raw_response: Response,
+        model_response: ModelResponse,
+        logging_obj: LiteLLMLoggingObj,
+        request_data: dict,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        encoding: Any,
+        api_key: Optional[str] = None,
+        json_mode: Optional[bool] = None,
+    ) -> ModelResponse:
+        model_response.model = f"azure_ai/{model}"
+        return super().transform_response(
+            model=model,
+            raw_response=raw_response,
+            model_response=model_response,
+            logging_obj=logging_obj,
+            request_data=request_data,
+            messages=messages,
+            optional_params=optional_params,
+            litellm_params=litellm_params,
+            encoding=encoding,
+            api_key=api_key,
+            json_mode=json_mode,
+        )
+
+    def should_retry_llm_api_inside_llm_translation_on_http_error(
+        self, e: httpx.HTTPStatusError, litellm_params: dict
+    ) -> bool:
+        should_drop_params = litellm_params.get("drop_params") or litellm.drop_params
+        error_text = e.response.text
+
+        if should_drop_params and "Extra inputs are not permitted" in error_text:
+            return True
+        elif (
+            "unknown field: parameter index is not a valid field" in error_text
+        ):  # remove index from tool calls
+            return True
+        elif (
+            AzureFoundryErrorStrings.SET_EXTRA_PARAMETERS_TO_PASS_THROUGH.value
+            in error_text
+        ):  # remove extra-parameters from tool calls
+            return True
+        return super().should_retry_llm_api_inside_llm_translation_on_http_error(
+            e=e, litellm_params=litellm_params
+        )
+
+    @property
+    def max_retry_on_unprocessable_entity_error(self) -> int:
+        return 2
+
+    def transform_request_on_unprocessable_entity_error(
+        self, e: httpx.HTTPStatusError, request_data: dict
+    ) -> dict:
+        _messages = cast(Optional[List[AllMessageValues]], request_data.get("messages"))
+        if (
+            "unknown field: parameter index is not a valid field" in e.response.text
+            and _messages is not None
+        ):
+            litellm.remove_index_from_tool_calls(
+                messages=_messages,
+            )
+        elif (
+            AzureFoundryErrorStrings.SET_EXTRA_PARAMETERS_TO_PASS_THROUGH.value
+            in e.response.text
+        ):
+            request_data = self._drop_extra_params_from_request_data(
+                request_data, e.response.text
+            )
+        data = drop_params_from_unprocessable_entity_error(e=e, data=request_data)
+        return data
+
+    def _drop_extra_params_from_request_data(
+        self, request_data: dict, error_text: str
+    ) -> dict:
+        params_to_drop = self._extract_params_to_drop_from_error_text(error_text)
+        if params_to_drop:
+            for param in params_to_drop:
+                if param in request_data:
+                    request_data.pop(param, None)
+        return request_data
+
+    def _extract_params_to_drop_from_error_text(
+        self, error_text: str
+    ) -> Optional[List[str]]:
+        """
+        Error text looks like this"
+            "Extra parameters ['stream_options', 'extra-parameters'] are not allowed when extra-parameters is not set or set to be 'error'.
+        """
+        import re
+
+        # Extract parameters within square brackets
+        match = re.search(r"\[(.*?)\]", error_text)
+        if not match:
+            return []
+
+        # Parse the extracted string into a list of parameter names
+        params_str = match.group(1)
+        params = []
+        for param in params_str.split(","):
+            # Clean up the parameter name (remove quotes, spaces)
+            clean_param = param.strip().strip("'").strip('"')
+            if clean_param:
+                params.append(clean_param)
+        return params