langchain_stream/views.py

from langchain_openai import AzureChatOpenAI
import os, json
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
from channels.generic.websocket import AsyncWebsocketConsumer
from dotenv import load_dotenv
load_dotenv()
os.environ["AZURE_OPENAI_API_KEY"] = os.getenv("AZURE_OPENAI_API_KEY")
os.environ["OPENAI_API_VERSION"] = os.getenv("OPENAI_API_VERSION")
os.environ["AZURE_OPENAI_ENDPOINT"] = os.getenv("AZURE_OPENAI_ENDPOINT")

llm = AzureChatOpenAI(
    azure_deployment="gpt-4o",
    temperature=0,
    max_tokens=None,
    timeout=None,
    max_retries=2,
)
prompt = ChatPromptTemplate.from_messages(
    [("system", "You are a helpful assistant"), ("user", "{input}")]
)
output_parser = StrOutputParser()
chain = (
    prompt
    | llm.with_config({"run_name": "model"})
    | output_parser.with_config({"run_name": "Assistant"})
)


class ChatConsumer(AsyncWebsocketConsumer):
    async def connect(self):
        await self.accept()

    async def disconnect(self, close_code):
        pass

    async def receive(self, text_data):
        text_data_json = json.loads(text_data)
        message = text_data_json["message"]
        try:
            async for chunk in chain.astream_events(
                {"input": message}, version="v1", include_names=["Assistant"]
            ):
                if chunk["event"] in ["on_parser_start", "on_parser_stream"]:
                    await self.send(text_data=json.dumps(chunk))
        except Exception as e:
            await self.send(text_data=json.dumps({"error": str(e)}))