chnaged the model and prompt

app.py

@@ -1,80 +1,82 @@
-# You can find this code for Chainlit python streaming here (https://docs.chainlit.io/concepts/streaming/python)
-
-# OpenAI Chat completion
-import os
-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 helpful assistant who always speaks in a pleasant tone!
-"""
-
-user_template = """{input}
-Think through your response step by step.
-"""
-
-
-@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,
-        "max_tokens": 500,
-        "top_p": 1,
-        "frequency_penalty": 0,
-        "presence_penalty": 0,
-    }
-
-    cl.user_session.set("settings", settings)
-
-
-@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")
-
-    client = AsyncOpenAI()
-
-    print(message.content)
-
-    prompt = Prompt(
-        provider=ChatOpenAI.id,
-        messages=[
-            PromptMessage(
-                role="system",
-                template=system_template,
-                formatted=system_template,
-            ),
-            PromptMessage(
-                role="user",
-                template=user_template,
-                formatted=user_template.format(input=message.content),
-            ),
-        ],
-        inputs={"input": message.content},
-        settings=settings,
-    )
-
-    print([m.to_openai() for m in prompt.messages])
-
-    msg = cl.Message(content="")
-
-    # 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.content
-        if not token:
-            token = ""
-        await msg.stream_token(token)
-
-    # Update the prompt object with the completion
-    prompt.completion = msg.content
-    msg.prompt = prompt
-
-    # Send and close the message stream
-    await msg.send()
+# You can find this code for Chainlit python streaming here (https://docs.chainlit.io/concepts/streaming/python)
+
+# OpenAI Chat completion
+import os
+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 helpful assistant who always speaks in a pleasant tone!
+"""
+
+user_template = """{input}
+1. Think through your response step by step.
+2. Provide clear and conside answer.
+3. Provide answer in bulleted form for text summarization and generation.
+"""
+
+
+@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-4o-mini",
+        "temperature": 0,
+        "max_tokens": 500,
+        "top_p": 1,
+        "frequency_penalty": 0,
+        "presence_penalty": 0,
+    }
+
+    cl.user_session.set("settings", settings)
+
+
+@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")
+
+    client = AsyncOpenAI()
+
+    print(message.content)
+
+    prompt = Prompt(
+        provider=ChatOpenAI.id,
+        messages=[
+            PromptMessage(
+                role="system",
+                template=system_template,
+                formatted=system_template,
+            ),
+            PromptMessage(
+                role="user",
+                template=user_template,
+                formatted=user_template.format(input=message.content),
+            ),
+        ],
+        inputs={"input": message.content},
+        settings=settings,
+    )
+
+    print([m.to_openai() for m in prompt.messages])
+
+    msg = cl.Message(content="")
+
+    # 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.content
+        if not token:
+            token = ""
+        await msg.stream_token(token)
+
+    # Update the prompt object with the completion
+    prompt.completion = msg.content
+    msg.prompt = prompt
+
+    # Send and close the message stream
+    await msg.send()