chore: initial snapshot for gitea/github upload

llm-gateway-competitors/litellm-wheel-src/litellm/llms/lm_studio/chat/transformation.py

@@ -0,0 +1,49 @@
+"""
+Translate from OpenAI's `/v1/chat/completions` to LM Studio's `/chat/completions`
+"""
+
+from typing import Optional, Tuple
+
+from litellm.secret_managers.main import get_secret_str
+
+from ...openai.chat.gpt_transformation import OpenAIGPTConfig
+
+
+class LMStudioChatConfig(OpenAIGPTConfig):
+    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("LM_STUDIO_API_BASE")  # type: ignore
+        dynamic_api_key = (
+            api_key or get_secret_str("LM_STUDIO_API_KEY") or "fake-api-key"
+        )  # LM Studio does not require an api key, but OpenAI client requires non-None value
+        return api_base, dynamic_api_key
+
+    def map_openai_params(
+        self,
+        non_default_params: dict,
+        optional_params: dict,
+        model: str,
+        drop_params: bool,
+    ) -> dict:
+        for param, value in list(non_default_params.items()):
+            if param == "response_format" and isinstance(value, dict):
+                if value.get("type") == "json_schema":
+                    if "json_schema" not in value and "schema" in value:
+                        optional_params["response_format"] = {
+                            "type": "json_schema",
+                            "json_schema": {"schema": value.get("schema")},
+                        }
+                    else:
+                        optional_params["response_format"] = value
+                    non_default_params.pop(param, None)
+                elif value.get("type") == "json_object":
+                    optional_params["response_format"] = value
+                    non_default_params.pop(param, None)
+
+        return super().map_openai_params(
+            non_default_params=non_default_params,
+            optional_params=optional_params,
+            model=model,
+            drop_params=drop_params,
+        )

llm-gateway-competitors/litellm-wheel-src/litellm/llms/lm_studio/embed/transformation.py

@@ -0,0 +1,50 @@
+"""
+Transformation logic from OpenAI /v1/embeddings format to LM Studio's  `/v1/embeddings` format. 
+
+Why separate file? Make it easy to see how transformation works
+
+Docs - https://lmstudio.ai/docs/basics/server
+"""
+
+import types
+from typing import List
+
+
+class LmStudioEmbeddingConfig:
+    """
+    Reference: https://lmstudio.ai/docs/basics/server
+    """
+
+    def __init__(
+        self,
+    ) -> None:
+        locals_ = locals().copy()
+        for key, value in locals_.items():
+            if key != "self" and value is not None:
+                setattr(self.__class__, key, value)
+
+    @classmethod
+    def get_config(cls):
+        return {
+            k: v
+            for k, v in cls.__dict__.items()
+            if not k.startswith("__")
+            and not isinstance(
+                v,
+                (
+                    types.FunctionType,
+                    types.BuiltinFunctionType,
+                    classmethod,
+                    staticmethod,
+                ),
+            )
+            and v is not None
+        }
+
+    def get_supported_openai_params(self) -> List[str]:
+        return []
+
+    def map_openai_params(
+        self, non_default_params: dict, optional_params: dict
+    ) -> dict:
+        return optional_params