Add Application File

app.py

@@ -1,41 +1,45 @@
+# You can find this code for Chainlit python streaming here (https://docs.chainlit.io/concepts/streaming/python)
+
 # OpenAI Chat completion
 import os
-import openai
-import chainlit as cl
-from chainlit.prompt import Prompt, PromptMessage
-from chainlit.playground.providers import ChatOpenAI
+from openai import AsyncOpenAI  # importing openai for API usage
+import chainlit as cl  # importing chainlit for our app
+from chainlit.prompt import Prompt, PromptMessage  # importing prompt tools
+from chainlit.playground.providers import ChatOpenAI  # importing ChatOpenAI tools
 from dotenv import load_dotenv
 
 load_dotenv()
 
 # ChatOpenAI Templates
-system_template = """You are a highly analytical assistant who has in-depth knowledge of science! 
+system_template = """You are a helpful assistant who always speaks in a pleasant tone!
 """
 
 user_template = """{input}
 Think through your response step by step.
-Be concise in your responses
-Do not make up stuff. If you don't know something, let the user know.
 """
 
-@cl.on_chat_start
+
+@cl.on_chat_start  # marks a function that will be executed at the start of a user session
 async def start_chat():
     settings = {
         "model": "gpt-3.5-turbo",
-        "temperature": 0.7,  # Adjust to a valid range
+        "temperature": 0,
         "max_tokens": 500,
         "top_p": 1,
         "frequency_penalty": 0,
         "presence_penalty": 0,
     }
+
     cl.user_session.set("settings", settings)
 
-@cl.on_message
+
+@cl.on_message  # marks a function that should be run each time the chatbot receives a message from a user
 async def main(message: cl.Message):
     settings = cl.user_session.get("settings")
 
-    # Set up the OpenAI client with the API key
-    openai.api_key = os.getenv("OPENAI_API_KEY")
+    client = AsyncOpenAI()
+
+    print(message.content)
 
     prompt = Prompt(
         provider=ChatOpenAI.id,
@@ -55,16 +59,17 @@ async def main(message: cl.Message):
         settings=settings,
     )
 
+    print([m.to_openai() for m in prompt.messages])
+
     msg = cl.Message(content="")
 
-    # Call OpenAI and stream response
-    async for stream_resp in await openai.ChatCompletion.acreate(
-        model=settings['model'],
-        messages=[m.to_openai() for m in prompt.messages],
-        stream=True,
-        **settings
+    # Call OpenAI
+    async for stream_resp in await client.chat.completions.create(
+        messages=[m.to_openai() for m in prompt.messages], stream=True, **settings
     ):
-        token = stream_resp.choices[0].delta.get("content", "")
+        token = stream_resp.choices[0].delta.content
+        if not token:
+            token = ""
         await msg.stream_token(token)
 
     # Update the prompt object with the completion
@@ -72,4 +77,4 @@ async def main(message: cl.Message):
     msg.prompt = prompt
 
     # Send and close the message stream
-    await msg.send()
+    await msg.send()