Update api response

src/api/models/bedrock.py

@@ -2,6 +2,7 @@ import base64
 import json
 import logging
 import re
+import time
 from abc import ABC
 from typing import AsyncIterable, Iterable, Literal
 
@@ -403,12 +404,14 @@ class BedrockModel(BaseChatModel):
                     message.tool_calls = [
                         ToolCall(
                             id=tool["toolUseId"],
+                            type="function",
                             function=ResponseFunction(
                                 name=tool["name"],
                                 arguments=json.dumps(tool["input"]),
                             ),
                         )
                     ]
+                    message.content = None
         else:
             message.content = content[0]["text"]
 
@@ -417,8 +420,10 @@ class BedrockModel(BaseChatModel):
             model=model,
             choices=[
                 Choice(
+                    index=0,
                     message=message,
-                    finish_reason=finish_reason,
+                    finish_reason=self._convert_finish_reason(finish_reason),
+                    logprobs=None,
                 )
             ],
             usage=Usage(
@@ -427,6 +432,9 @@ class BedrockModel(BaseChatModel):
                 total_tokens=input_tokens + output_tokens,
             ),
         )
+        response.system_fingerprint = "fp"
+        response.object = "chat.completion"
+        response.created = int(time.time())
         return response
 
     def _create_response_stream(
@@ -455,6 +463,7 @@ class BedrockModel(BaseChatModel):
                 message = ChatResponseMessage(
                     tool_calls=[
                         ToolCall(
+                            type="function",
                             id=delta["toolUse"]["toolUseId"],
                             function=ResponseFunction(
                                 name=delta["toolUse"]["name"],
@@ -475,6 +484,7 @@ class BedrockModel(BaseChatModel):
                 message = ChatResponseMessage(
                     tool_calls=[
                         ToolCall(
+                            type="function",
                             function=ResponseFunction(
                                 arguments=delta["toolUse"]["input"],
                             )
@@ -509,7 +519,7 @@ class BedrockModel(BaseChatModel):
                         index=0,
                         delta=message,
                         logprobs=None,
-                        finish_reason=finish_reason,
+                        finish_reason=self._convert_finish_reason(finish_reason),
                     )
                 ],
                 usage=usage,
@@ -615,6 +625,28 @@ class BedrockModel(BaseChatModel):
             }
         }
 
+    def _convert_finish_reason(self, finish_reason: str | None) -> str | None:
+        """
+        Below is a list of finish reason according to OpenAI doc:
+
+        - stop: if the model hit a natural stop point or a provided stop sequence,
+        - length: if the maximum number of tokens specified in the request was reached,
+        - content_filter: if content was omitted due to a flag from our content filters,
+        - tool_calls: if the model called a tool
+        """
+        if finish_reason:
+            finish_reason_mapping = {
+                "tool_use": "tool_calls",
+                "finished": "stop",
+                "end_turn": "stop",
+                "max_tokens": "length",
+                "stop_sequence": "stop",
+                "complete": "stop",
+                "content_filtered": "content_filter"
+            }
+            return finish_reason_mapping.get(finish_reason.lower(), finish_reason.lower())
+        return None
+
 
 class BedrockEmbeddingsModel(BaseEmbeddingsModel, ABC):
     accept = "application/json"

src/api/routers/chat.py

@@ -15,7 +15,7 @@ router = APIRouter(
 )
 
 
-@router.post("/completions", response_model=ChatResponse | ChatStreamResponse, response_model_exclude_none=True)
+@router.post("/completions", response_model=ChatResponse | ChatStreamResponse, response_model_exclude_unset=True)
 async def chat_completions(
         chat_request: Annotated[
             ChatRequest,