add client using OpenAI library

Author: ks6088ts

backend/internals/azure_openai.py

@@ -2,9 +2,7 @@
 from collections.abc import AsyncIterable
 from logging import getLogger
 
-from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate
-from langchain_core.messages import HumanMessage, SystemMessage
-from langchain_openai import AzureChatOpenAI
+from openai import AzureOpenAI
 
 from backend.settings.azure_openai import Settings
 
@@ -15,40 +13,39 @@ class Client:
     def __init__(self, settings: Settings) -> None:
         self.settings = settings
 
-    def get_client(self) -> AzureChatOpenAI:
-        return AzureChatOpenAI(
+    def get_client(self) -> AzureOpenAI:
+        return AzureOpenAI(
             api_key=self.settings.azure_openai_api_key,
             api_version=self.settings.azure_openai_api_version,
             azure_endpoint=self.settings.azure_openai_endpoint,
-            azure_deployment=self.settings.azure_openai_gpt_model,
         )
 
     def create_chat_completions(
         self,
         content: str,
     ) -> str:
-        response = self.get_client().invoke(
-            [
-                HumanMessage(
-                    content=content,
-                ),
-            ]
+        response = self.get_client().chat.completions.create(
+            model=self.settings.azure_openai_gpt_model,
+            messages=[
+                {"role": "user", "content": content},
+            ],
+            stream=False,
         )
         logger.info(response)
-        return response.content
+        return response.choices[0].message.content
 
     async def create_chat_completions_stream(
         self,
         content: str,
     ) -> AsyncIterable[str]:
-        llm = self.get_client()
-        messages = [HumanMessagePromptTemplate.from_template(template="{message}")]
-        prompt = ChatPromptTemplate.from_messages(messages)
-        chain = prompt | llm
-        res = chain.astream({"message": content})
-        async for msg in res:
-            logger.info(msg)
-            yield msg.content
+        _ = self.get_client().chat.completions.create(
+            model=self.settings.azure_openai_gpt_model,
+            messages=[
+                {"role": "user", "content": content},
+            ],
+            stream=True,
+        )
+        assert False, "Yet to be implemented."
 
     def create_chat_completions_with_vision(
         self,
@@ -58,24 +55,19 @@ def create_chat_completions_with_vision(
     ) -> str:
         encoded_image = b64encode(image).decode("ascii")
 
-        response = self.get_client().invoke(
-            [
-                SystemMessage(
-                    content=system_prompt,
-                ),
-                HumanMessage(
-                    content=[
-                        {
-                            "type": "text",
-                            "text": user_prompt,
-                        },
-                        {
-                            "type": "image_url",
-                            "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"},
-                        },
+        response = self.get_client().chat.completions.create(
+            model=self.settings.azure_openai_gpt_model,
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": user_prompt},
+                        {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"}},
                     ],
-                ),
-            ]
+                },
+            ],
+            stream=False,
         )
         logger.info(response)
-        return response.content
+        return response.choices[0].message.content

backend/internals/azure_openai_langchain.py

@@ -0,0 +1,81 @@
+from base64 import b64encode
+from collections.abc import AsyncIterable
+from logging import getLogger
+
+from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate
+from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_openai import AzureChatOpenAI
+
+from backend.settings.azure_openai import Settings
+
+logger = getLogger(__name__)
+
+
+class Client:
+    def __init__(self, settings: Settings) -> None:
+        self.settings = settings
+
+    def get_client(self) -> AzureChatOpenAI:
+        return AzureChatOpenAI(
+            api_key=self.settings.azure_openai_api_key,
+            api_version=self.settings.azure_openai_api_version,
+            azure_endpoint=self.settings.azure_openai_endpoint,
+            azure_deployment=self.settings.azure_openai_gpt_model,
+        )
+
+    def create_chat_completions(
+        self,
+        content: str,
+    ) -> str:
+        response = self.get_client().invoke(
+            [
+                HumanMessage(
+                    content=content,
+                ),
+            ]
+        )
+        logger.info(response)
+        return response.content
+
+    async def create_chat_completions_stream(
+        self,
+        content: str,
+    ) -> AsyncIterable[str]:
+        llm = self.get_client()
+        messages = [HumanMessagePromptTemplate.from_template(template="{message}")]
+        prompt = ChatPromptTemplate.from_messages(messages)
+        chain = prompt | llm
+        res = chain.astream({"message": content})
+        async for msg in res:
+            logger.info(msg)
+            yield msg.content
+
+    def create_chat_completions_with_vision(
+        self,
+        system_prompt: str,
+        user_prompt: str,
+        image: bytes,
+    ) -> str:
+        encoded_image = b64encode(image).decode("ascii")
+
+        response = self.get_client().invoke(
+            [
+                SystemMessage(
+                    content=system_prompt,
+                ),
+                HumanMessage(
+                    content=[
+                        {
+                            "type": "text",
+                            "text": user_prompt,
+                        },
+                        {
+                            "type": "image_url",
+                            "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"},
+                        },
+                    ],
+                ),
+            ]
+        )
+        logger.info(response)
+        return response.content

backend/routers/azure_openai.py

@@ -3,7 +3,7 @@
 from fastapi import APIRouter, UploadFile
 from fastapi.responses import StreamingResponse
 
-from backend.internals.azure_openai import Client
+from backend.internals.azure_openai_langchain import Client
 from backend.schemas import azure_openai as azure_openai_schemas
 from backend.settings.azure_openai import Settings