Remove unused Python API deps

api-service/agent/smol_agent.py

@@ -108,7 +108,7 @@ async def create(
         # Use default openai api key
         new_config.args["openai_api_key"] = default_openai_api_key
 
-        model = get_model(new_config, callback_manager)
+        model = get_model(new_config, callback_manager, streaming=False)
 
         return cls(
             new_config,

api-service/models/base.py

@@ -1,23 +1,13 @@
 from typing import Dict, Any, List, Literal
 from enum import Enum
-from langchain.chat_models import ChatOpenAI, AzureChatOpenAI
-from langchain.llms import Anthropic
+from langchain.chat_models import ChatOpenAI
 from langchain.schema import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
 from pydantic import BaseModel
 
-from .providers.replicate import ReplicateFix
-from .providers.hugging_face import HuggingFaceHubFix, HuggingFaceEndpointFix
-from .providers.banana import BananaFix
-
 
 class ModelProvider(Enum):
     OpenAI = "OpenAI"
-    AzureOpenAI = "AzureOpenAI"
-    Replicate = "Replicate"
-    Anthropic = "Anthropic"
-    HuggingFace = "HuggingFace"
-    Banana = "Banana"
 
 
 class PromptPart(BaseModel):
@@ -39,74 +29,14 @@ def get_model(
     streaming=True,
 ) -> BaseLanguageModel:
     match config.provider:
-        case ModelProvider.Anthropic.value:
-            return Anthropic(
-                **config.args,
-                verbose=True,
-                streaming=True,
-                callback_manager=callback_manager,
-            )
         case ModelProvider.OpenAI.value:
             return ChatOpenAI(
                 **config.args,
                 request_timeout=3600,
                 verbose=True,
                 # The max time between retries is 1 minute so we set max_retries to 45
                 max_retries=45,
-                streaming=False,
-                callback_manager=callback_manager,
-            )
-        case ModelProvider.AzureOpenAI.value:
-            return AzureChatOpenAI(
-                **config.args,
-                request_timeout=3600,
-                verbose=True,
-                streaming=True,
-                callback_manager=callback_manager,
-            )
-        case ModelProvider.Replicate.value:
-            return ReplicateFix(
-                model=config.args["model"],
-                replicate_api_token=config.args["replicate_api_token"],
-                model_kwargs=config.args,
-                verbose=True,
-                callback_manager=callback_manager,
-            )
-        case ModelProvider.HuggingFace.value:
-            if config.args.get("endpoint_url"):
-                return HuggingFaceEndpointFix(
-                    huggingfacehub_api_token=config.args["huggingfacehub_api_token"],
-                    endpoint_url=config.args["endpoint_url"],
-                    verbose=True,
-                    model_kwargs={
-                        **config.args,
-                        "huggingfacehub_api_token": None,
-                        "endpoint_url": None,
-                    },
-                    callback_manager=callback_manager,
-                    task="text-generation",
-                )
-            elif config.args.get("repo_id"):
-                return HuggingFaceHubFix(
-                    huggingfacehub_api_token=config.args["huggingfacehub_api_token"],
-                    repo_id=config.args["repo_id"],
-                    model_kwargs={
-                        **config.args,
-                        "huggingfacehub_api_token": None,
-                        "repo_id": None,
-                    },
-                    verbose=True,
-                    callback_manager=callback_manager,
-                )  # type: ignore
-            raise ValueError(
-                f"Missing endpoint_url or repo_id for the HuggingFace integration."
-            )
-        case ModelProvider.Banana.value:
-            return BananaFix(
-                model_key=config.args["model_key"],
-                banana_api_key=config.args["banana_api_key"],
-                model_kwargs=config.args,
-                verbose=True,
+                streaming=streaming,
                 callback_manager=callback_manager,
             )
         case _: