fix: properly handle tool_use messages in conversation

.gitignore

@@ -160,3 +160,4 @@ cython_debug/
 .idea/
 
 Config
+.vscode/launch.json

src/api/app.py

@@ -45,6 +45,16 @@ async def health():
 
 @app.exception_handler(RequestValidationError)
 async def validation_exception_handler(request, exc):
+    logger = logging.getLogger(__name__)
+    
+    # Log essential info only - avoid sensitive data and performance overhead
+    logger.warning(
+        "Request validation failed: %s %s - %s", 
+        request.method, 
+        request.url.path,
+        str(exc).split('\n')[0]  # First line only
+    )
+    
     return PlainTextResponse(str(exc), status_code=400)
 
 

src/api/models/base.py

@@ -1,3 +1,4 @@
+import logging
 import time
 import uuid
 from abc import ABC, abstractmethod
@@ -14,6 +15,8 @@ from api.schema import (
     Error,
 )
 
+logger = logging.getLogger(__name__)
+
 
 class BaseChatModel(ABC):
     """Represent a basic chat model
@@ -46,6 +49,7 @@ class BaseChatModel(ABC):
     @staticmethod
     def stream_response_to_bytes(response: ChatStreamResponse | Error | None = None) -> bytes:
         if isinstance(response, Error):
+            logger.error("Stream error: %s", response.error.message if response.error else "Unknown error")
             data = response.model_dump_json()
         elif isinstance(response, ChatStreamResponse):
             # to populate other fields when using exclude_unset=True

src/api/models/bedrock.py

@@ -34,6 +34,7 @@ from api.schema import (
     ResponseFunction,
     TextContent,
     ToolCall,
+    ToolContent,
     ToolMessage,
     Usage,
     UserMessage,
@@ -48,7 +49,15 @@ from api.setting import (
 
 logger = logging.getLogger(__name__)
 
-config = Config(connect_timeout=60, read_timeout=120, retries={"max_attempts": 1})
+config = Config(
+            connect_timeout=60,      # Connection timeout: 60 seconds
+            read_timeout=900,        # Read timeout: 15 minutes (suitable for long streaming responses)
+            retries={
+                'max_attempts': 8,   # Maximum retry attempts
+                'mode': 'adaptive'   # Adaptive retry mode
+            },
+            max_pool_connections=50  # Maximum connection pool size
+        )
 
 bedrock_runtime = boto3.client(
     service_name="bedrock-runtime",
@@ -177,6 +186,7 @@ class BedrockModel(BaseChatModel):
         # check if model is supported
         if chat_request.model not in bedrock_model_list.keys():
             error = f"Unsupported model {chat_request.model}, please use models API to get a list of supported models"
+            logger.error("Unsupported model: %s", chat_request.model)
 
         if error:
             raise HTTPException(
@@ -204,13 +214,13 @@ class BedrockModel(BaseChatModel):
                 # Run the blocking boto3 call in a thread pool
                 response = await run_in_threadpool(bedrock_runtime.converse, **args)
         except bedrock_runtime.exceptions.ValidationException as e:
-            logger.error("Validation Error: " + str(e))
+            logger.error("Bedrock validation error for model %s: %s", chat_request.model, str(e))
             raise HTTPException(status_code=400, detail=str(e))
         except bedrock_runtime.exceptions.ThrottlingException as e:
-            logger.error("Throttling Error: " + str(e))
+            logger.warning("Bedrock throttling for model %s: %s", chat_request.model, str(e))
             raise HTTPException(status_code=429, detail=str(e))
         except Exception as e:
-            logger.error(e)
+            logger.error("Bedrock invocation failed for model %s: %s", chat_request.model, str(e))
             raise HTTPException(status_code=500, detail=str(e))
         return response
 
@@ -270,6 +280,7 @@ class BedrockModel(BaseChatModel):
             # return an [DONE] message at the end.
             yield self.stream_response_to_bytes()
         except Exception as e:
+            logger.error("Stream error for model %s: %s", chat_request.model, str(e))
             error_event = Error(error=ErrorMessage(message=str(e)))
             yield self.stream_response_to_bytes(error_event)
 
@@ -317,7 +328,16 @@ class BedrockModel(BaseChatModel):
                     }
                 )
             elif isinstance(message, AssistantMessage):
-                if message.content.strip():
+                # Check if message has content that's not empty
+                has_content = False
+                if isinstance(message.content, str):
+                    has_content = message.content.strip() != ""
+                elif isinstance(message.content, list):
+                    has_content = len(message.content) > 0
+                elif message.content is not None:
+                    has_content = True
+                
+                if has_content:
                     # Text message
                     messages.append(
                         {
@@ -349,6 +369,10 @@ class BedrockModel(BaseChatModel):
                 # Bedrock does not support tool role,
                 # Add toolResult to content
                 # https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_ToolResultBlock.html
+                
+                # Handle different content formats from OpenAI SDK
+                tool_content = self._extract_tool_content(message.content)
+                
                 messages.append(
                     {
                         "role": "user",
@@ -356,7 +380,7 @@ class BedrockModel(BaseChatModel):
                             {
                                 "toolResult": {
                                     "toolUseId": message.tool_call_id,
-                                    "content": [{"text": message.content}],
+                                    "content": [{"text": tool_content}],
                                 }
                             }
                         ],
@@ -368,6 +392,57 @@ class BedrockModel(BaseChatModel):
                 continue
         return self._reframe_multi_payloard(messages)
 
+    def _extract_tool_content(self, content) -> str:
+        """Extract text content from various OpenAI SDK tool message formats.
+        
+        Handles:
+        - String content (legacy format)
+        - List of content objects (OpenAI SDK 1.91.0+)
+        - Nested JSON structures within text content
+        """
+        try:
+            if isinstance(content, str):
+                return content
+            
+            if isinstance(content, list):
+                text_parts = []
+                for i, item in enumerate(content):
+                    if isinstance(item, dict):
+                        # Handle dict with 'text' field
+                        if "text" in item:
+                            item_text = item["text"]
+                            if isinstance(item_text, str):
+                                # Try to parse as JSON if it looks like JSON
+                                if item_text.strip().startswith('{') and item_text.strip().endswith('}'):
+                                    try:
+                                        parsed_json = json.loads(item_text)
+                                        # Convert JSON object to readable text
+                                        text_parts.append(json.dumps(parsed_json, indent=2))
+                                    except json.JSONDecodeError:
+                                        # Silently fallback to original text
+                                        text_parts.append(item_text)
+                                else:
+                                    text_parts.append(item_text)
+                            else:
+                                text_parts.append(str(item_text))
+                        else:
+                            # Handle other dict formats - convert to JSON string
+                            text_parts.append(json.dumps(item, indent=2))
+                    elif hasattr(item, 'text'):
+                        # Handle ToolContent objects
+                        text_parts.append(item.text)
+                    else:
+                        # Convert any other type to string
+                        text_parts.append(str(item))
+                return "\n".join(text_parts)
+            
+            # Fallback for any other type
+            return str(content)
+        except Exception as e:
+            logger.warning("Tool content extraction failed: %s", str(e))
+            # Return a safe fallback
+            return str(content) if content is not None else ""
+
     def _reframe_multi_payloard(self, messages: list) -> list:
         """Receive messages and reformat them to comply with the Claude format
 

src/api/schema.py

@@ -45,6 +45,11 @@ class ImageContent(BaseModel):
     image_url: ImageUrl
 
 
+class ToolContent(BaseModel):
+    type: Literal["text"] = "text"
+    text: str
+
+
 class SystemMessage(BaseModel):
     name: str | None = None
     role: Literal["system"] = "system"
@@ -66,7 +71,7 @@ class AssistantMessage(BaseModel):
 
 class ToolMessage(BaseModel):
     role: Literal["tool"] = "tool"
-    content: str
+    content: str | list[ToolContent] | list[dict]
     tool_call_id: str