feat:use xinference tts stream mode (#8616)

api/core/model_runtime/model_providers/xinference/llm/llm.py

 from openai.types.completion import Completion
 from xinference_client.client.restful.restful_client import (
     Client,
-    RESTfulChatglmCppChatModelHandle,
     RESTfulChatModelHandle,
     RESTfulGenerateModelHandle,
 )
         if tools and len(tools) > 0:
             generate_config["tools"] = [{"type": "function", "function": helper.dump_model(tool)} for tool in tools]
         vision = credentials.get("support_vision", False)
-        if isinstance(xinference_model, RESTfulChatModelHandle | RESTfulChatglmCppChatModelHandle):
+        if isinstance(xinference_model, RESTfulChatModelHandle):
             resp = client.chat.completions.create(
                 model=credentials["model_uid"],
                 messages=[self._convert_prompt_message_to_dict(message) for message in prompt_messages],

api/core/model_runtime/model_providers/xinference/tts/tts.py

                 executor = concurrent.futures.ThreadPoolExecutor(max_workers=min(3, len(sentences)))
                 futures = [
                     executor.submit(
-                        handle.speech, input=sentences[i], voice=voice, response_format="mp3", speed=1.0, stream=False
+                        handle.speech, input=sentences[i], voice=voice, response_format="mp3", speed=1.0, stream=True
                     )
                     for i in range(len(sentences))
                 ]
 
                 for future in futures:
                     response = future.result()
-                    for i in range(0, len(response), 1024):
-                        yield response[i : i + 1024]
+                    for chunk in response:
+                        yield chunk
             else:
                 response = handle.speech(
-                    input=content_text.strip(), voice=voice, response_format="mp3", speed=1.0, stream=False
+                    input=content_text.strip(), voice=voice, response_format="mp3", speed=1.0, stream=True
                 )
 
-                for i in range(0, len(response), 1024):
-                    yield response[i : i + 1024]
+                for chunk in response:
+                    yield chunk
         except Exception as ex:
             raise InvokeBadRequestError(str(ex))

api/poetry.lock

 
 [[package]]
 name = "xinference-client"
-version = "0.13.3"
+version = "0.15.2"
 description = "Client for Xinference"
 optional = false
 python-versions = "*"
 files = [
-    {file = "xinference-client-0.13.3.tar.gz", hash = "sha256:822b722100affdff049c27760be7d62ac92de58c87a40d3361066df446ba648f"},
-    {file = "xinference_client-0.13.3-py3-none-any.whl", hash = "sha256:f0eff3858b1ebcef2129726f82b09259c177e11db466a7ca23def3d4849c419f"},
+    {file = "xinference-client-0.15.2.tar.gz", hash = "sha256:5c2259bb133148d1cc9bd2b8ec6eb8b5bbeba7f11d6252959f4e6cd79baa53ed"},
+    {file = "xinference_client-0.15.2-py3-none-any.whl", hash = "sha256:b6275adab695e75e75a33e21e0ad212488fc2d5a4d0f693d544c0e78469abbe3"},
 ]
 
 [package.dependencies]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "18924ae12a00bde4438a46168bc167ed69613ab1ab0c387f193cd47ac24379b2"
+content-hash = "85aa4be7defee8fe6622cf95ba03e81895121502ebf6d666d6ce376ff019fac7"

api/pyproject.toml

 unstructured = { version = "~0.10.27", extras = ["docx", "epub", "md", "msg", "ppt", "pptx"] }
 websocket-client = "~1.7.0"
 werkzeug = "~3.0.1"
-xinference-client = "0.13.3"
+xinference-client = "0.15.2"
 yarl = "~1.9.4"
 zhipuai = "1.0.7"
 # Before adding new dependency, consider place it in alphabet order (a-z) and suitable group.

api/tests/integration_tests/model_runtime/__mock/xinference.py

 from requests.sessions import Session
 from xinference_client.client.restful.restful_client import (
     Client,
-    RESTfulChatglmCppChatModelHandle,
     RESTfulChatModelHandle,
     RESTfulEmbeddingModelHandle,
     RESTfulGenerateModelHandle,
 
 
 class MockXinferenceClass:
-    def get_chat_model(
-        self: Client, model_uid: str
-    ) -> Union[RESTfulChatglmCppChatModelHandle, RESTfulGenerateModelHandle, RESTfulChatModelHandle]:
+    def get_chat_model(self: Client, model_uid: str) -> Union[RESTfulGenerateModelHandle, RESTfulChatModelHandle]:
         if not re.match(r"https?:\/\/[^\s\/$.?#].[^\s]*$", self.base_url):
             raise RuntimeError("404 Not Found")