Update app.py

app.py

@@ -2,223 +2,85 @@
 
 # OpenAI Chat completion
 import os
-import openai
 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 import message
+from chainlit.prompt import Prompt, PromptMessage  # importing prompt tools
 from chainlit.playground.providers import ChatOpenAI  # importing ChatOpenAI tools
 from dotenv import load_dotenv
 
 
-from chainlit.playground.providers import ChatOpenAI
-import chainlit as cl
-
-
 openai_api_key = os.getenv("OPENAI_API_KEY")
 
-
 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)
+system_template = """You are a helpful assistant who always speaks in a pleasant tone!
+"""
 
-#     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()
-
-
-# template = "Hello, {name}!"
-# variables = {"name": "John"}
-
-# settings = {
-#     "model": "gpt-3.5-turbo",
-#     "temperature": 0,
-#     # ... more settings
-# }
-
-#-------------------------------------------------------------
-
-# @cl.step(type="llm")
-# async def call_llm():
-#     generation = cl.ChatGeneration(
-#         provider=ChatOpenAI.id,
-#         variables=variables,
-#         settings=settings,
-#         messages=[
-#             {
-#                 "content": template.format(**variables),
-#                 "role":"user"
-#             },
-#         ],
-#     )
-
-#     # Make the call to OpenAI
-#     response = await client.chat.completions.create(
-#         messages=generation.messages, **settings
-#     )
-
-#     generation.message_completion = {
-#         "content": response.choices[0].message.content,
-#         "role": "assistant"
-#     }
-
-#     # Add the generation to the current step
-#     cl.context.current_step.generation = generation
-
-#     return generation.message_completion["content"]
-
-
-# @cl.on_chat_start
-# async def start():
-#     await call_llm()
-
-#-------------------------------------------------------------
-#******
-
-# @cl.on_message
-# async def on_message(message: cl.Message):
-#     msg = cl.Message(content="")
-#     await msg.send()
-
-#     # do some work
-#     await cl.sleep(2)
-
-#     msg.content = f"Processed message {message.content}"
-
-#     await msg.update()
-
-
-#------------------------------------
-#**************************
-
-client = AsyncOpenAI(api_key="sk-proj-r0mIMTDm41HXzATQVROcT3BlbkFJjEokAFlqLT2tS0RwBt6O")
-import chainlit as cl
-
-settings = {
-    "model": "gpt-3.5-turbo",
-    "temperature": 0,
-    "max_tokens": 500,
-    "top_p": 1,
-    "frequency_penalty": 0,
-    "presence_penalty": 0,
-}
+user_template = """{input}
+Think through your response step by step.
+"""
 
 
-@cl.on_chat_start
-def start_chat():
-    cl.user_session.set(
-        "message_history",
-        [{"role": "system", "content": "You are a helpful assistant who always speaks in a pleasant tone!."}],
-    )   
-    cl.user_session.set(
-    "user_template",
-    "{input}\nThink through your response step by step.\n"
-    )
-    cl.user_session.set(
-        "settings",
-        settings
-    )
-
+@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.on_message
-async def main(message: cl.Message):
-    message_history = cl.user_session.get("message_history")
-    message_history.append({"role": "user", "content": message.content})
+    cl.user_session.set("settings", settings)
 
-    msg = cl.Message(content="")
-    await msg.send()
 
-    stream = await client.chat.completions.create(
-        messages=message_history, stream=True, **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(api_key=openai_api_key)
+
+    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,
     )
 
-    async for part in stream:
-        if token := part.choices[0].delta.content or "":
-            await msg.stream_token(token)
-
-    message_history.append({"role": "assistant", "content": msg.content})
-    await msg.update()
+    print([m.to_openai() for m in prompt.messages])
 
+    msg = cl.Message(content="")
 
-# import chainlit as cl
-
-#-----------------------------------------------
-# @cl.on_message
-# async def on_message(msg: cl.Message):
-#     if not msg.elements:
-#         await cl.Message(content="No file attached").send()
-#         return
+    # 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)
 
-#     # Processing images exclusively
-#     images = [file for file in msg.elements if "image" in file.mime]
+    # Update the prompt object with the completion
+    prompt.completion = msg.content
+    msg.prompt = prompt
 
-#     # Read the first image
-#     with open(images[0].path, "r") as f:
-#         pass
+    # Send and close the message stream
+    await msg.send()
 
-    # await cl.Message(content=f"Received {len(images)} image(s)").send()