Add clarifai as Inference provider

src/huggingface_hub/inference/_client.py

@@ -104,7 +104,6 @@
 from huggingface_hub.utils import build_hf_headers, get_session, hf_raise_for_status
 from huggingface_hub.utils._auth import get_token
 
-
 if TYPE_CHECKING:
     import numpy as np
     from PIL.Image import Image
@@ -130,7 +129,7 @@ class InferenceClient:
             Note: for better compatibility with OpenAI's client, `model` has been aliased as `base_url`. Those 2
             arguments are mutually exclusive. If a URL is passed as `model` or `base_url` for chat completion, the `(/v1)/chat/completions` suffix path will be appended to the URL.
         provider (`str`, *optional*):
-            Name of the provider to use for inference. Can be `"black-forest-labs"`, `"cerebras"`, `"cohere"`, `"fal-ai"`, `"featherless-ai"`, `"fireworks-ai"`, `"groq"`, `"hf-inference"`, `"hyperbolic"`, `"nebius"`, `"novita"`, `"nscale"`, `"openai"`, `publicai`, `"replicate"`, `"sambanova"`, `"scaleway"`, `"together"` or `"zai-org"`.
+            Name of the provider to use for inference. Can be `"black-forest-labs"`, `"cerebras"`, `"clarifai"`, `"cohere"`, `"fal-ai"`, `"featherless-ai"`, `"fireworks-ai"`, `"groq"`, `"hf-inference"`, `"hyperbolic"`, `"nebius"`, `"novita"`, `"nscale"`, `"openai"`, `publicai`, `"replicate"`, `"sambanova"`, `"scaleway"`, `"together"` or `"zai-org"`.
             Defaults to "auto" i.e. the first of the providers available for the model, sorted by the user's order in https://hf.co/settings/inference-providers.
             If model is a URL or `base_url` is passed, then `provider` is not used.
         token (`str`, *optional*):

src/huggingface_hub/inference/_generated/_async_client.py

@@ -91,7 +91,6 @@
 
 from .._common import _async_yield_from, _import_aiohttp
 
-
 if TYPE_CHECKING:
     import numpy as np
     from aiohttp import ClientResponse, ClientSession
@@ -118,7 +117,7 @@ class AsyncInferenceClient:
             Note: for better compatibility with OpenAI's client, `model` has been aliased as `base_url`. Those 2
             arguments are mutually exclusive. If a URL is passed as `model` or `base_url` for chat completion, the `(/v1)/chat/completions` suffix path will be appended to the URL.
         provider (`str`, *optional*):
-            Name of the provider to use for inference. Can be `"black-forest-labs"`, `"cerebras"`, `"cohere"`, `"fal-ai"`, `"featherless-ai"`, `"fireworks-ai"`, `"groq"`, `"hf-inference"`, `"hyperbolic"`, `"nebius"`, `"novita"`, `"nscale"`, `"openai"`, `publicai`, `"replicate"`, `"sambanova"`, `"scaleway"`, `"together"` or `"zai-org"`.
+            Name of the provider to use for inference. Can be `"black-forest-labs"`, `"cerebras"`, `"clarifai"`, `"cohere"`, `"fal-ai"`, `"featherless-ai"`, `"fireworks-ai"`, `"groq"`, `"hf-inference"`, `"hyperbolic"`, `"nebius"`, `"novita"`, `"nscale"`, `"openai"`, `publicai`, `"replicate"`, `"sambanova"`, `"scaleway"`, `"together"` or `"zai-org"`.
             Defaults to "auto" i.e. the first of the providers available for the model, sorted by the user's order in https://hf.co/settings/inference-providers.
             If model is a URL or `base_url` is passed, then `provider` is not used.
         token (`str`, *optional*):

src/huggingface_hub/inference/_providers/__init__.py

@@ -9,6 +9,7 @@
 from ._common import TaskProviderHelper, _fetch_inference_provider_mapping
 from .black_forest_labs import BlackForestLabsTextToImageTask
 from .cerebras import CerebrasConversationalTask
+from .clarifai import ClarifaiConversationalTask
 from .cohere import CohereConversationalTask
 from .fal_ai import (
     FalAIAutomaticSpeechRecognitionTask,
@@ -43,13 +44,13 @@
 from .together import TogetherConversationalTask, TogetherTextGenerationTask, TogetherTextToImageTask
 from .zai_org import ZaiConversationalTask
 
-
 logger = logging.get_logger(__name__)
 
 
 PROVIDER_T = Literal[
     "black-forest-labs",
     "cerebras",
+    "clarifai",
     "cohere",
     "fal-ai",
     "featherless-ai",
@@ -78,6 +79,9 @@
     "cerebras": {
         "conversational": CerebrasConversationalTask(),
     },
+    "clarifai": {
+        "conversational": ClarifaiConversationalTask(),
+    },
     "cohere": {
         "conversational": CohereConversationalTask(),
     },

src/huggingface_hub/inference/_providers/_common.py

@@ -7,7 +7,6 @@
 from huggingface_hub.inference._generated.types.chat_completion import ChatCompletionInputMessage
 from huggingface_hub.utils import build_hf_headers, get_token, logging
 
-
 logger = logging.get_logger(__name__)
 
 
@@ -24,6 +23,7 @@
     #                                    status="live")
     "cerebras": {},
     "cohere": {},
+    "clarifai": {},
     "fal-ai": {},
     "fireworks-ai": {},
     "groq": {},

src/huggingface_hub/inference/_providers/clarifai.py

@@ -0,0 +1,30 @@
+from typing import Any, Dict, Optional
+
+from huggingface_hub.hf_api import InferenceProviderMapping
+
+from ._common import BaseConversationalTask
+
+_PROVIDER = "clarifai"
+_BASE_URL = "https://api.clarifai.com"
+
+class ClarifaiConversationalTask(BaseConversationalTask):
+    def __init__(self):
+        super().__init__(provider=_PROVIDER, base_url=_BASE_URL)
+
+    def _prepare_route(self, mapped_model: str, api_key: str) -> str:
+        return "/v2/ext/openai/v1/chat/completions"
+
+    def _prepare_payload_as_dict(
+        self, inputs: Any, parameters: Dict, provider_mapping_info: InferenceProviderMapping
+    ) -> Optional[Dict]:
+        payload = super()._prepare_payload_as_dict(inputs, parameters, provider_mapping_info)
+        response_format = parameters.get("response_format")
+        if isinstance(response_format, dict) and response_format.get("type") == "json_schema":
+            json_schema_details = response_format.get("json_schema")
+            if isinstance(json_schema_details, dict) and "schema" in json_schema_details:
+                payload["response_format"] = {  # type: ignore [index]
+                    "type": "json_object",
+                    "schema": json_schema_details["schema"],
+                }
+        return payload
+

tests/test_inference_providers.py

@@ -17,6 +17,7 @@
     recursive_merge,
 )
 from huggingface_hub.inference._providers.black_forest_labs import BlackForestLabsTextToImageTask
+from huggingface_hub.inference._providers.clarifai import ClarifaiConversationalTask
 from huggingface_hub.inference._providers.cohere import CohereConversationalTask
 from huggingface_hub.inference._providers.fal_ai import (
     _POLLING_INTERVAL,
@@ -293,6 +294,31 @@ def test_prepare_payload_as_dict(self):
         }
 
 
+class TestClarifaiProvider:
+    def test_prepare_url(self):
+        helper = ClarifaiConversationalTask()
+        assert helper._prepare_url("clarifai_api_key", "username/repo_name") == "https://api.clarifai.com/v2/ext/openai/v1/chat/completions"
+
+    def test_prepare_payload_as_dict(self):
+        helper = ClarifaiConversationalTask()
+        payload = helper._prepare_payload_as_dict(
+            [{"role": "user", "content": "Hello!"}],
+            {},
+            InferenceProviderMapping(
+                provider="clarifai",
+                hf_model_id="meta-llama/llama-3.1-8B-Instruct",
+                providerId="meta-llama/llama-3.1-8B-Instruct",
+                task="conversational",
+                status="live",
+            ),
+        )
+
+        assert payload == {
+            "messages": [{"role": "user", "content": "Hello!"}],
+            "model": "meta-llama/llama-3.1-8B-Instruct",
+        }
+
+
 class TestFalAIProvider:
     def test_prepare_headers_fal_ai_key(self):
         """When using direct call, must use Key authorization."""