Merge branch 'refs/heads/master' into feature/streamlit

# Conflicts:
#	apps/datascience_assistant/README.md
#	apps/datascience_assistant/app.py
#	resources/data_science_assistant_streamlit_1.png

docs/source/index.rst

@@ -52,6 +52,14 @@ Modelscope-Agent DOCUMENTATION
    deployment/local_deploy.md
 
 
+.. toctree::
+   :maxdepth: 2
+   :caption: Agents
+
+   agents/data_science_assistant.md
+
+
+
 
 Indices and tables
 ==================

docs/source_en/index.rst

@@ -50,6 +50,11 @@ Modelscope-Agent DOCUMENTATION
    use_cases/openAPI_for_agent.md
    deployment/local_deploy.md
 
+.. toctree::
+   :maxdepth: 2
+   :caption: Agents
+
+   agents/data_science_assistant.md
 
 
 Indices and tables

modelscope_agent/llm/__init__.py

@@ -17,6 +17,7 @@ def get_chat_model(model: str, model_server: str, **kwargs) -> BaseChatModel:
     """
     model_type = re.split(r'[-/_]', model)[0]  # parser qwen / gpt / ...
     registered_model_id = f'{model_server}_{model_type}'
+
     if registered_model_id in LLM_REGISTRY:  # specific model from specific source
         return LLM_REGISTRY[registered_model_id](model, model_server, **kwargs)
     elif model_server in LLM_REGISTRY:  # specific source

modelscope_agent/llm/openai.py

@@ -4,28 +4,55 @@
 from modelscope_agent.llm.base import BaseChatModel, register_llm
 from modelscope_agent.utils.logger import agent_logger as logger
 from modelscope_agent.utils.retry import retry
-from openai import OpenAI
+from openai import AzureOpenAI, OpenAI
 
 
 @register_llm('openai')
+@register_llm('azure_openai')
 class OpenAi(BaseChatModel):
 
-    def __init__(self,
-                 model: str,
-                 model_server: str,
-                 is_chat: bool = True,
-                 is_function_call: Optional[bool] = None,
-                 support_stream: Optional[bool] = None,
-                 **kwargs):
+    def __init__(
+        self,
+        model: str,
+        model_server: str,
+        is_chat: bool = True,
+        is_function_call: Optional[bool] = None,
+        support_stream: Optional[bool] = None,
+        **kwargs,
+    ):
         super().__init__(model, model_server, is_function_call)
-        default_api_base = os.getenv('OPENAI_API_BASE',
-                                     'https://api.openai.com/v1')
-        api_base = kwargs.get('api_base', default_api_base).strip()
-        api_key = kwargs.get('api_key',
-                             os.getenv('OPENAI_API_KEY',
-                                       default='EMPTY')).strip()
-        logger.info(f'client url {api_base}, client key: {api_key}')
-        self.client = OpenAI(api_key=api_key, base_url=api_base)
+
+        self.is_azure = model_server.lower().startswith('azure')
+        if self.is_azure:
+            default_azure_endpoint = os.getenv(
+                'AZURE_OPENAI_ENDPOINT',
+                'https://docs-test-001.openai.azure.com/')
+            azure_endpoint = kwargs.get('azure_endpoint',
+                                        default_azure_endpoint).strip()
+            api_key = kwargs.get(
+                'api_key', os.getenv('AZURE_OPENAI_API_KEY',
+                                     default='EMPTY')).strip()
+            api_version = kwargs.get('api_version', '2024-06-01').strip()
+            logger.info(
+                f'client url {azure_endpoint}, client key: {api_key}, client version: {api_version}'
+            )
+
+            self.client = AzureOpenAI(
+                azure_endpoint=azure_endpoint,
+                api_key=api_key,
+                api_version=api_version,
+            )
+        else:
+            default_api_base = os.getenv('OPENAI_API_BASE',
+                                         'https://api.openai.com/v1')
+            api_base = kwargs.get('api_base', default_api_base).strip()
+            api_key = kwargs.get('api_key',
+                                 os.getenv('OPENAI_API_KEY',
+                                           default='EMPTY')).strip()
+            logger.info(f'client url {api_base}, client key: {api_key}')
+
+            self.client = OpenAI(api_key=api_key, base_url=api_base)
+
         self.is_function_call = is_function_call
         self.is_chat = is_chat
         self.support_stream = support_stream
@@ -38,21 +65,24 @@ def _chat_stream(self,
         logger.info(
             f'call openai api, model: {self.model}, messages: {str(messages)}, '
             f'stop: {str(stop)}, stream: True, args: {str(kwargs)}')
-        stream_options = {'include_usage': True}
+
+        if not self.is_azure:
+            kwargs['stream_options'] = {'include_usage': True}
+
         response = self.client.chat.completions.create(
             model=self.model,
             messages=messages,
             stop=stop,
             stream=True,
-            stream_options=stream_options,
             **kwargs)
+
         response = self.stat_last_call_token_info_stream(response)
         # TODO: error handling
         for chunk in response:
             # sometimes delta.content is None by vllm, we should not yield None
-            if len(chunk.choices) > 0 and hasattr(
-                    chunk.choices[0].delta,
-                    'content') and chunk.choices[0].delta.content:
+            if (len(chunk.choices) > 0
+                    and hasattr(chunk.choices[0].delta, 'content')
+                    and chunk.choices[0].delta.content):
                 logger.info(
                     f'call openai api success, output: {chunk.choices[0].delta.content}'
                 )
@@ -93,12 +123,14 @@ def support_raw_prompt(self) -> bool:
             return not self.is_chat
 
     @retry(max_retries=3, delay_seconds=0.5)
-    def chat(self,
-             prompt: Optional[str] = None,
-             messages: Optional[List[Dict]] = None,
-             stop: Optional[List[str]] = None,
-             stream: bool = False,
-             **kwargs) -> Union[str, Iterator[str]]:
+    def chat(
+        self,
+        prompt: Optional[str] = None,
+        messages: Optional[List[Dict]] = None,
+        stop: Optional[List[str]] = None,
+        stream: bool = False,
+        **kwargs,
+    ) -> Union[str, Iterator[str]]:
 
         if 'uuid_str' in kwargs:
             kwargs.pop('uuid_str')
@@ -150,7 +182,8 @@ def chat_with_functions(self,
                 messages=messages,
                 tools=functions,
                 tool_choice='auto',
-                **kwargs)
+                **kwargs,
+            )
         else:
             response = self.client.chat.completions.create(
                 model=self.model, messages=messages, **kwargs)
@@ -175,9 +208,9 @@ def _chat_stream(self,
         # TODO: error handling
         for chunk in response:
             # sometimes delta.content is None by vllm, we should not yield None
-            if len(chunk.choices) > 0 and hasattr(
-                    chunk.choices[0].delta,
-                    'content') and chunk.choices[0].delta.content:
+            if (len(chunk.choices) > 0
+                    and hasattr(chunk.choices[0].delta, 'content')
+                    and chunk.choices[0].delta.content):
                 logger.info(
                     f'call openai api success, output: {chunk.choices[0].delta.content}'
                 )