(feat) add xinference as an embedding provider

litellm/__init__.py

@@ -260,7 +260,13 @@ openai_compatible_endpoints: List = [
 ]
 
 # this is maintained for Exception Mapping
-openai_compatible_providers: List = ["anyscale", "mistral", "deepinfra", "perplexity"]
+openai_compatible_providers: List = [
+    "anyscale",
+    "mistral",
+    "deepinfra",
+    "perplexity",
+    "xinference",
+]
 
 
 # well supported replicate llms
@@ -401,6 +407,7 @@ provider_list: List = [
     "maritalk",
     "voyage",
     "cloudflare",
+    "xinference",
     "custom",  # custom apis
 ]
 

litellm/main.py

@@ -2072,6 +2072,9 @@ async def aembedding(*args, **kwargs):
         if (
             custom_llm_provider == "openai"
             or custom_llm_provider == "azure"
+            or custom_llm_provider == "xinference"
+            or custom_llm_provider == "voyage"
+            or custom_llm_provider == "mistral"
             or custom_llm_provider == "custom_openai"
             or custom_llm_provider == "anyscale"
             or custom_llm_provider == "openrouter"
@@ -2416,6 +2419,31 @@ def embedding(
                 client=client,
                 aembedding=aembedding,
             )
+        elif custom_llm_provider == "xinference":
+            api_key = (
+                api_key
+                or litellm.api_key
+                or get_secret("XINFERENCE_API_KEY")
+                or "stub-xinference-key"
+            )  # xinference does not need an api key, pass a stub key if user did not set one
+            api_base = (
+                api_base
+                or litellm.api_base
+                or get_secret("XINFERENCE_API_BASE")
+                or "http://127.0.0.1:9997/v1"
+            )
+            response = openai_chat_completions.embedding(
+                model=model,
+                input=input,
+                api_base=api_base,
+                api_key=api_key,
+                logging_obj=logging,
+                timeout=timeout,
+                model_response=EmbeddingResponse(),
+                optional_params=optional_params,
+                client=client,
+                aembedding=aembedding,
+            )
         else:
             args = locals()
             raise ValueError(f"No valid embedding model args passed in - {args}")

litellm/utils.py

@@ -3008,7 +3008,11 @@ def get_optional_params_embeddings(
         if (k in default_params and v != default_params[k])
     }
     ## raise exception if non-default value passed for non-openai/azure embedding calls
-    if custom_llm_provider != "openai" and custom_llm_provider != "azure":
+    if (
+        custom_llm_provider != "openai"
+        and custom_llm_provider != "azure"
+        and custom_llm_provider not in litellm.openai_compatible_providers
+    ):
         if len(non_default_params.keys()) > 0:
             if litellm.drop_params is True:  # drop the unsupported non-default values
                 keys = list(non_default_params.keys())