增加对xinference的支持。

backend/app/settings.py

@@ -3,6 +3,10 @@ from typing import Dict
 
 from llama_index.core.constants import DEFAULT_TEMPERATURE
 from llama_index.core.settings import Settings
+from llama_index.llms.xinference import Xinference
+from llama_index.llms.xinference.base import DEFAULT_XINFERENCE_TEMP
+
+from app.xinference.base import XinferenceEmbedding
 
 
 def init_settings():
@@ -26,8 +30,9 @@ def init_settings():
             init_azure_openai()
         case "t-systems":
             from .llmhub import init_llmhub
-
             init_llmhub()
+        case "xinference":
+            init_xinference()
         case _:
             raise ValueError(f"Invalid model provider: {model_provider}")
 
@@ -52,6 +57,21 @@ def init_ollama():
     # )
     pass
 
+def init_xinference():
+    base_url = os.getenv("BASE_URL")
+    model = os.getenv("MODEL")
+    max_tokens = int(os.getenv("LLM_MAX_TOKENS")) if os.getenv("LLM_MAX_TOKENS") is not None else None
+    temperature = float(os.getenv("LLM_TEMPERATURE", DEFAULT_XINFERENCE_TEMP))
+
+    Settings.llm = Xinference(model, base_url, temperature, max_tokens)
+
+    embedding_base_url = os.getenv("EMBEDDING_BASE_URL")
+    embedding_base_url = embedding_base_url if embedding_base_url != None and embedding_base_url != "" else base_url
+
+    embed_model_name = os.getenv("EMBEDDING_MODEL")
+    dimensions = os.getenv("EMBEDDING_DIM")
+    dimensions = int(dimensions) if dimensions is not None else None
+    Settings.embed_model = XinferenceEmbedding(embed_model_name, embedding_base_url)
 
 def init_openai():
     from llama_index.core.constants import DEFAULT_TEMPERATURE