add content block enum

flowllm/core/enumeration/__init__.py

@@ -1,12 +1,14 @@
 """Core enumeration module."""
 
 from .chunk_enum import ChunkEnum
+from .content_block_type import ContentBlockType
 from .http_enum import HttpEnum
 from .registry_enum import RegistryEnum
 from .role import Role
 
 __all__ = [
     "ChunkEnum",
+    "ContentBlockType",
     "HttpEnum",
     "RegistryEnum",
     "Role",

flowllm/core/enumeration/content_block_type.py

@@ -0,0 +1,12 @@
+"""Content block type enumeration for multimodal content."""
+
+from enum import Enum
+
+
+class ContentBlockType(str, Enum):
+    """Enumeration of content block types in multimodal responses."""
+
+    TEXT = "text"
+    IMAGE_URL = "image_url"
+    AUDIO = "audio"
+    VIDEO = "video"

flowllm/core/llm/lite_llm.py

@@ -110,7 +110,8 @@ def stream_chat(
             **self.kwargs,
             **kwargs,
         }
-        logger.info(f"LiteLLM.stream_chat: {chat_kwargs}")
+        log_kwargs = {k: v for k, v in chat_kwargs.items() if k != "messages"}
+        logger.info(f"LiteLLM.stream_chat: {log_kwargs}")
 
         for i in range(self.max_retries):
             try:
@@ -216,7 +217,8 @@ async def astream_chat(
             **self.kwargs,
             **kwargs,
         }
-        logger.info(f"LiteLLM.astream_chat: {chat_kwargs}")
+        log_kwargs = {k: v for k, v in chat_kwargs.items() if k != "messages"}
+        logger.info(f"LiteLLM.astream_chat: {log_kwargs}")
 
         for i in range(self.max_retries):
             try:

flowllm/core/llm/openai_compatible_llm.py

@@ -106,7 +106,8 @@ def stream_chat(
             **self.kwargs,
             **kwargs,
         }
-        logger.info(f"OpenAICompatibleLLM.stream_chat: {chat_kwargs}")
+        log_kwargs = {k: v for k, v in chat_kwargs.items() if k != "messages"}
+        logger.info(f"OpenAICompatibleLLM.stream_chat: {log_kwargs}")
 
         for i in range(self.max_retries):
             try:
@@ -207,7 +208,8 @@ async def astream_chat(
             **self.kwargs,
             **kwargs,
         }
-        logger.info(f"OpenAICompatibleLLM.astream_chat: {chat_kwargs}")
+        log_kwargs = {k: v for k, v in chat_kwargs.items() if k != "messages"}
+        logger.info(f"OpenAICompatibleLLM.astream_chat: {log_kwargs}")
 
         for i in range(self.max_retries):
             try:

flowllm/core/schema/message.py

@@ -6,7 +6,7 @@
 from pydantic import BaseModel, ConfigDict, Field, model_validator
 
 from .tool_call import ToolCall
-from ..enumeration import Role
+from ..enumeration import Role, ContentBlockType
 
 
 class ContentBlock(BaseModel):
@@ -35,7 +35,7 @@ class ContentBlock(BaseModel):
 
     model_config = ConfigDict(extra="allow")
 
-    type: str = Field(default="")
+    type: ContentBlockType = Field(default="")
     content: str | dict | list = Field(default="")
 
     @model_validator(mode="before")
@@ -44,14 +44,15 @@ def init_block(cls, data: dict):
         """Initialize content block by extracting content based on type field."""
         result = data.copy()
         content_type = data.get("type", "")
-        result["content"] = data[content_type]
+        if content_type and content_type in data:
+            result["content"] = data[content_type]
         return result
 
     def simple_dump(self) -> dict:
         """Convert ContentBlock to a simple dictionary format."""
         result = {
-            "type": self.type,
-            self.type: self.content,
+            "type": self.type.value,
+            self.type.value: self.content,
             **self.model_extra,
         }
 

tests/test_vision_audio.py

@@ -14,7 +14,7 @@ def encode_image(image_path):
             return base64.b64encode(image_file.read()).decode("utf-8")
 
     # 将xxxx/eagle.png替换为你本地图像的绝对路径
-    base64_image = encode_image("/Users/yuli/workspace/ReMe/20251128144329.jpg")
+    base64_image = encode_image("/Users/yuli/Documents/20251128144329.jpg")
 
     llm = OpenAICompatibleLLM(model_name="qwen3-vl-plus")
     messages = [
@@ -50,7 +50,7 @@ def encode_audio(audio_path):
             return base64.b64encode(audio_file.read()).decode("utf-8")
 
     # 请将 ABSOLUTE_PATH/welcome.mp3 替换为本地音频的绝对路径
-    audio_file_path = "/Users/yuli/workspace/ReMe/recordings/111.wav"
+    audio_file_path = "/Users/yuli/Documents/111.wav"
     base64_audio = encode_audio(audio_file_path)
 
     messages = [