add modelscope endpoint

libs/community/langchain_community/chat_models/__init__.py

@@ -122,6 +122,9 @@
     from langchain_community.chat_models.mlx import (
         ChatMLX,
     )
+    from langchain_community.chat_models.modelscope_endpoint import (
+        ModelscopeChatEndpoint,
+    )
     from langchain_community.chat_models.moonshot import (
         MoonshotChat,
     )
@@ -251,6 +254,7 @@
     "JinaChat",
     "LlamaEdgeChatService",
     "MiniMaxChat",
+    "ModelscopeChatEndpoint",
     "MoonshotChat",
     "PaiEasChatEndpoint",
     "PromptLayerChatOpenAI",
@@ -316,6 +320,7 @@
     "JinaChat": "langchain_community.chat_models.jinachat",
     "LlamaEdgeChatService": "langchain_community.chat_models.llama_edge",
     "MiniMaxChat": "langchain_community.chat_models.minimax",
+    "ModelscopeChatEndpoint": "langchain_community.chat_models.modelscope_endpoint",
     "MoonshotChat": "langchain_community.chat_models.moonshot",
     "PaiEasChatEndpoint": "langchain_community.chat_models.pai_eas_endpoint",
     "PromptLayerChatOpenAI": "langchain_community.chat_models.promptlayer_openai",

libs/community/langchain_community/chat_models/modelscope_endpoint.py

@@ -0,0 +1,128 @@
+"""Wrapper around modelscope chat endpoint models."""
+
+from typing import Dict
+
+from langchain_core.utils import (
+    convert_to_secret_str,
+    get_from_dict_or_env,
+    pre_init,
+)
+
+from langchain_community.chat_models import ChatOpenAI
+from langchain_community.llms.modelscope_endpoint import (
+    MODELSCOPE_SERVICE_URL_BASE,
+    ModelscopeCommon,
+)
+
+
+class ModelscopeChatEndpoint(ModelscopeCommon, ChatOpenAI):  # type: ignore[misc, override, override]
+    """Modelscope chat model inference api integration. To use, must have a modelscope account and a modelscope sdk token.
+    Refer to https://modelscope.cn/docs/model-service/API-Inference/intro for more details.
+
+    Setup:
+        Install ``openai`` and set environment variables ``MODELSCOPE_SDK_TOKEN``.
+
+        .. code-block:: bash
+
+            pip install openai
+            export MODELSCOPE_SDK_TOKEN="your-modelscope-sdk-token"
+
+    Key init args — completion params:
+        model: str
+            Name of Modelscope model to use. Refer to https://modelscope.cn/docs/model-service/API-Inference/intro for available models.
+        temperature: Optional[float]
+            Sampling temperature, defaults to 0.3.
+        max_tokens: Optional[int]
+            Max number of tokens to generate, defaults to 1024.
+
+    Key init args — client params:
+        modelscope_sdk_token: Optional[str]
+            Modelscope SDK Token. If not passed in will be read from env var MODELSCOPE_SDK_TOKEN.
+        api_base: Optional[str]
+            Base URL for API requests.
+
+    See full list of supported init args and their descriptions in the params section.
+
+    Instantiate:
+        .. code-block:: python
+
+            from langchain_community.chat_models import ModelscopeChatEndpoint
+
+            chat = ModelscopeChatEndpoint(
+                modelscope_sdk_token="your-modelscope-sdk-token",
+                model="Qwen/Qwen2.5-Coder-32B-Instruct",
+                temperature=0.5,
+                # api_base="...",
+                # other params...
+            )
+
+    Invoke:
+        .. code-block:: python
+
+            messages = [
+                ("system", "你擅长编程"),
+                ("human", "写一个快速排序的代码"),
+            ]
+            chat.invoke(messages)
+
+        .. code-block:: python
+
+            AIMessage(
+                content='def quick_sort(arr): ...',
+                additional_kwargs={},
+                response_metadata={
+                    'token_usage': {
+                        'completion_tokens': 312,
+                        'prompt_tokens': 27,
+                        'total_tokens': 339
+                    },
+                    'model_name': 'Qwen/Qwen2.5-Coder-32B-Instruct',
+                    'system_fingerprint': None,
+                    'finish_reason': 'stop',
+                    'logprobs': None
+                },
+                id='run-71c03f4e-6628-41d5-beb6-d2559ae68266-0'
+            )
+    Stream:
+        .. code-block:: python
+
+            for chunk in chat.stream(messages):
+                print(chunk)
+
+    """  # noqa: E501
+
+    @pre_init
+    def validate_environment(cls, values: Dict) -> Dict:
+        """Validate that the environment is set up correctly."""
+        values["modelscope_sdk_token"] = convert_to_secret_str(
+            get_from_dict_or_env(
+                values,
+                ["modelscope_sdk_token", "api_key"],
+                "MODELSCOPE_SDK_TOKEN",
+            )
+        )
+
+        try:
+            import openai
+
+        except ImportError:
+            raise ImportError(
+                "Could not import openai python package. "
+                "Please install it with `pip install openai`."
+            )
+
+        client_params = {
+            "api_key": values["modelscope_sdk_token"].get_secret_value(),
+            "base_url": values["base_url"]
+            if "base_url" in values
+            else MODELSCOPE_SERVICE_URL_BASE,
+        }
+
+        if not values.get("client"):
+            values["client"] = openai.OpenAI(**client_params).chat.completions
+        if not values.get("async_client"):
+            values["async_client"] = openai.AsyncOpenAI(
+                **client_params
+            ).chat.completions
+
+        return values

libs/community/langchain_community/llms/__init__.py

@@ -368,6 +368,12 @@ def _import_modal() -> Type[BaseLLM]:
     return Modal
 
 
+def _import_modelscope_endpoint() -> Type[BaseLLM]:
+    from langchain_community.llms.modelscope_endpoint import ModelscopeEndpoint
+
+    return ModelscopeEndpoint
+
+
 def _import_mosaicml() -> Type[BaseLLM]:
     from langchain_community.llms.mosaicml import MosaicML
 
@@ -785,6 +791,8 @@ def __getattr__(name: str) -> Any:
         return _import_mlx_pipeline()
     elif name == "Modal":
         return _import_modal()
+    elif name == "ModelscopeEndpoint":
+        return _import_modelscope_endpoint()
     elif name == "MosaicML":
         return _import_mosaicml()
     elif name == "NLPCloud":
@@ -947,6 +955,7 @@ def __getattr__(name: str) -> Any:
     "MlflowAIGateway",
     "MLXPipeline",
     "Modal",
+    "ModelscopeEndpoint",
     "MosaicML",
     "NIBittensorLLM",
     "NLPCloud",
@@ -1052,6 +1061,7 @@ def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
         "mlflow-ai-gateway": _import_mlflow_ai_gateway,
         "mlx_pipeline": _import_mlx_pipeline,
         "modal": _import_modal,
+        "modelscope_endpoint": _import_modelscope_endpoint,
         "mosaic": _import_mosaicml,
         "nebula": _import_symblai_nebula,
         "nibittensor": _import_bittensor,