structure saas with tools

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

@@ -0,0 +1,90 @@
+from typing import List, Optional, Tuple
+
+import litellm
+from litellm._logging import verbose_logger
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    strip_name_from_messages,
+)
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllMessageValues
+
+from ...openai.chat.gpt_transformation import OpenAIGPTConfig
+
+XAI_API_BASE = "https://api.x.ai/v1"
+
+
+class XAIChatConfig(OpenAIGPTConfig):
+    @property
+    def custom_llm_provider(self) -> Optional[str]:
+        return "xai"
+
+    def _get_openai_compatible_provider_info(
+        self, api_base: Optional[str], api_key: Optional[str]
+    ) -> Tuple[Optional[str], Optional[str]]:
+        api_base = api_base or get_secret_str("XAI_API_BASE") or XAI_API_BASE  # type: ignore
+        dynamic_api_key = api_key or get_secret_str("XAI_API_KEY")
+        return api_base, dynamic_api_key
+
+    def get_supported_openai_params(self, model: str) -> list:
+        base_openai_params = [
+            "frequency_penalty",
+            "logit_bias",
+            "logprobs",
+            "max_tokens",
+            "n",
+            "presence_penalty",
+            "response_format",
+            "seed",
+            "stop",
+            "stream",
+            "stream_options",
+            "temperature",
+            "tool_choice",
+            "tools",
+            "top_logprobs",
+            "top_p",
+            "user",
+        ]
+        try:
+            if litellm.supports_reasoning(
+                model=model, custom_llm_provider=self.custom_llm_provider
+            ):
+                base_openai_params.append("reasoning_effort")
+        except Exception as e:
+            verbose_logger.debug(f"Error checking if model supports reasoning: {e}")
+
+        return base_openai_params
+
+    def map_openai_params(
+        self,
+        non_default_params: dict,
+        optional_params: dict,
+        model: str,
+        drop_params: bool = False,
+    ) -> dict:
+        supported_openai_params = self.get_supported_openai_params(model=model)
+        for param, value in non_default_params.items():
+            if param == "max_completion_tokens":
+                optional_params["max_tokens"] = value
+            elif param in supported_openai_params:
+                if value is not None:
+                    optional_params[param] = value
+        return optional_params
+
+    def transform_request(
+        self,
+        model: str,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        headers: dict,
+    ) -> dict:
+        """
+        Handle https://github.com/BerriAI/litellm/issues/9720
+
+        Filter out 'name' from messages
+        """
+        messages = strip_name_from_messages(messages)
+        return super().transform_request(
+            model, messages, optional_params, litellm_params, headers
+        )

.venv/lib/python3.10/site-packages/litellm/llms/xai/common_utils.py

@@ -0,0 +1,71 @@
+from typing import List, Optional
+
+import httpx
+
+import litellm
+from litellm.llms.base_llm.base_utils import BaseLLMModelInfo
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllMessageValues
+
+
+class XAIModelInfo(BaseLLMModelInfo):
+    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_key is not None:
+            headers["Authorization"] = f"Bearer {api_key}"
+
+        # Ensure Content-Type is set to application/json
+        if "content-type" not in headers and "Content-Type" not in headers:
+            headers["Content-Type"] = "application/json"
+
+        return headers
+
+    @staticmethod
+    def get_api_base(api_base: Optional[str] = None) -> Optional[str]:
+        return api_base or get_secret_str("XAI_API_BASE") or "https://api.x.ai"
+
+    @staticmethod
+    def get_api_key(api_key: Optional[str] = None) -> Optional[str]:
+        return api_key or get_secret_str("XAI_API_KEY")
+
+    @staticmethod
+    def get_base_model(model: str) -> Optional[str]:
+        return model.replace("xai/", "")
+
+    def get_models(
+        self, api_key: Optional[str] = None, api_base: Optional[str] = None
+    ) -> List[str]:
+        api_base = self.get_api_base(api_base)
+        api_key = self.get_api_key(api_key)
+        if api_base is None or api_key is None:
+            raise ValueError(
+                "XAI_API_BASE or XAI_API_KEY is not set. Please set the environment variable, to query XAI's `/models` endpoint."
+            )
+        response = litellm.module_level_client.get(
+            url=f"{api_base}/v1/models",
+            headers={"Authorization": f"Bearer {api_key}"},
+        )
+
+        try:
+            response.raise_for_status()
+        except httpx.HTTPStatusError:
+            raise Exception(
+                f"Failed to fetch models from XAI. Status code: {response.status_code}, Response: {response.text}"
+            )
+
+        models = response.json()["data"]
+
+        litellm_model_names = []
+        for model in models:
+            stripped_model_name = model["id"]
+            litellm_model_name = "xai/" + stripped_model_name
+            litellm_model_names.append(litellm_model_name)
+        return litellm_model_names