Refactor to use new Converse API

src/api/models/__init__.py

@@ -1,7 +0,0 @@
-from api.models.bedrock import (
-	ClaudeModel,
-	SUPPORTED_BEDROCK_MODELS,
-	SUPPORTED_BEDROCK_EMBEDDING_MODELS,
-	get_model,
-	get_embeddings_model,
-)

src/api/models/base.py

@@ -1,3 +1,4 @@
+import time
 import uuid
 from abc import ABC, abstractmethod
 from typing import AsyncIterable
@@ -19,6 +20,14 @@ class BaseChatModel(ABC):
     Currently, only Bedrock model is supported, but may be used for SageMaker models if needed.
     """
 
+    def list_models(self) -> list[str]:
+        """Return a list of supported models"""
+        return []
+
+    def validate(self, chat_request: ChatRequest):
+        """Validate chat completion requests."""
+        pass
+
     @abstractmethod
     def chat(self, chat_request: ChatRequest) -> ChatResponse:
         """Handle a basic chat completion requests."""
@@ -38,7 +47,11 @@ class BaseChatModel(ABC):
             response: ChatStreamResponse | None = None
     ) -> bytes:
         if response:
-            return "data: {}\n\n".format(response.model_dump_json()).encode("utf-8")
+            # to populate other fields when using exclude_unset=True
+            response.system_fingerprint = "fp"
+            response.object = "chat.completion.chunk"
+            response.created = int(time.time())
+            return "data: {}\n\n".format(response.model_dump_json(exclude_unset=True)).encode("utf-8")
         return "data: [DONE]\n\n".encode("utf-8")
 
 

src/api/routers/chat.py

@@ -4,7 +4,7 @@ from fastapi import APIRouter, Depends, Body
 from fastapi.responses import StreamingResponse
 
 from api.auth import api_key_auth
-from api.models import get_model
+from api.models.bedrock import BedrockModel
 from api.schema import ChatRequest, ChatResponse, ChatStreamResponse
 from api.setting import DEFAULT_MODEL
 
@@ -36,7 +36,8 @@ async def chat_completions(
         chat_request.model = DEFAULT_MODEL
 
     # Exception will be raised if model not supported.
-    model = get_model(chat_request.model)
+    model = BedrockModel()
+    model.validate(chat_request)
     if chat_request.stream:
         return StreamingResponse(
             content=model.chat_stream(chat_request), media_type="text/event-stream"

src/api/routers/embeddings.py

@@ -3,7 +3,7 @@ from typing import Annotated
 from fastapi import APIRouter, Depends, Body
 
 from api.auth import api_key_auth
-from api.models import get_embeddings_model
+from api.models.bedrock import get_embeddings_model
 from api.schema import EmbeddingsRequest, EmbeddingsResponse
 from api.setting import DEFAULT_EMBEDDING_MODEL
 

src/api/routers/model.py

@@ -3,7 +3,7 @@ from typing import Annotated
 from fastapi import APIRouter, Depends, HTTPException, Path
 
 from api.auth import api_key_auth
-from api.models import SUPPORTED_BEDROCK_MODELS, SUPPORTED_BEDROCK_EMBEDDING_MODELS
+from api.models.bedrock import BedrockModel
 from api.schema import Models, Model
 
 router = APIRouter(
@@ -12,16 +12,19 @@ router = APIRouter(
     # responses={404: {"description": "Not found"}},
 )
 
+chat_model = BedrockModel()
+
 
 async def validate_model_id(model_id: str):
-    if model_id not in (SUPPORTED_BEDROCK_MODELS | SUPPORTED_BEDROCK_EMBEDDING_MODELS).keys():
+    if model_id not in chat_model.list_models():
         raise HTTPException(status_code=500, detail="Unsupported Model Id")
 
 
 @router.get("", response_model=Models)
 async def list_models():
-    model_list = [Model(id=model_id) for model_id in
-                  (SUPPORTED_BEDROCK_MODELS | SUPPORTED_BEDROCK_EMBEDDING_MODELS).keys()]
+    model_list = [
+        Model(id=model_id) for model_id in chat_model.list_models()
+    ]
     return Models(data=model_list)
 
 

src/api/schema.py

@@ -1,5 +1,4 @@
 import time
-import uuid
 from typing import Literal, Iterable
 
 from pydantic import BaseModel, Field
@@ -18,12 +17,12 @@ class Models(BaseModel):
 
 
 class ResponseFunction(BaseModel):
-    name: str
+    name: str | None = None
     arguments: str
 
 
 class ToolCall(BaseModel):
-    id: str = Field(default_factory=lambda: str(uuid.uuid4())[:8])
+    id: str | None = None
     type: Literal["function"] = "function"
     function: ResponseFunction
 
@@ -113,8 +112,8 @@ class ChatResponseMessage(BaseModel):
 
 
 class BaseChoice(BaseModel):
-    index: int
-    finish_reason: str | None
+    index: int | None = 0
+    finish_reason: str | None = None
     logprobs: dict | None = None
 
 

src/api/setting.py

@@ -11,27 +11,11 @@ DESCRIPTION = """
 Use OpenAI-Compatible RESTful APIs for Amazon Bedrock models.
 
 List of Amazon Bedrock models currently supported:
-
-# Chat
-- anthropic.claude-instant-v1
-- anthropic.claude-v2:1
-- anthropic.claude-v2
-- anthropic.claude-3-opus-20240229-v1:0
-- anthropic.claude-3-sonnet-20240229-v1:0
-- anthropic.claude-3-haiku-20240307-v1:0
-- meta.llama2-13b-chat-v1
-- meta.llama2-70b-chat-v1
-- meta.llama3-8b-instruct-v1:0
-- meta.llama3-70b-instruct-v1:0
-- mistral.mistral-7b-instruct-v0:2
-- mistral.mixtral-8x7b-instruct-v0:1
-- mistral.mistral-large-2402-v1:0
-- cohere.command-r-v1:0
-- cohere.command-r-plus-v1:0
-
-# Embeddings
-- cohere.embed-multilingual-v3
-- cohere.embed-english-v3
+- Anthropic Claude 2 / 3 (Haiku/Sonnet/Opus)
+- Meta Llama 2 / 3
+- Mistral / Mixtral
+- Cohere Command R / R+
+- Cohere Embedding
 """
 
 DEBUG = os.environ.get("DEBUG", "false").lower() != "false"

src/requirements.txt

@@ -1,7 +1,9 @@
-fastapi==0.110.2
+fastapi==0.111.0
 pydantic==2.7.1
 uvicorn==0.29.0
 mangum==0.17.0
 tiktoken==0.6.0
-requests==2.32.0
+requests==2.32.3
 numpy==1.26.4
+boto3==1.34.117
+botocore==1.34.117