adding app file, dockerimage and requirements

Dockerfile

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+FROM python:3.10
+RUN useradd -m -u 1000 user
+USER user
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+WORKDIR $HOME/app
+COPY --chown=user . $HOME/app
+COPY ./requirements.txt ~/app/requirements.txt
+RUN pip install -r requirements.txt
+COPY . .
+CMD ["chainlit", "run", "app.py", "--port", "7860"]

app.py

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+#Importing Libraries
+
+import os
+import openai
+import chainlit as cl
+from chainlit.prompt import Prompt, PromptMessage
+from chainlit.playground.providers import ChatOpenAI
+from dotenv import load_dotenv
+
+load_dotenv()
+openai.api_key = os.environ["OPENAI_API_KEY"]
+
+#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.
+"""
+
+# Runs at the start of the user cession
+@cl.on_chat_start
+async def start_chat():
+    settings = {
+        "model": "gpt-3.5-turbo",# Model that we will be using
+        "temperature": 0, # Randomness in the answer
+        "max_tokens": 500,# Maximum length of tokens as input
+        "top_p": 1, #
+        "frequency_penalty": 0,
+        "presence_penalty": 0,
+    }
+
+    cl.user_session.set("settings", settings)
+
+#Function that will run on each time the bot gets a user input
+@cl.on_message
+async def main(message:str):
+    settings = cl.user_session.get("settings")
+
+    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)
+            ),
+        ],
+        inputs = {"input":message},
+        settings = settings,
+    )
+
+    print([m.to_openai() for m in prompt.messages])
+
+    msg = cl.Messages(content="")
+
+    # Call OpenAI
+    async for stream_resp  in await openai.ChatCompletion.acreate(
+        messages = [m.to_openai() for m in prompt.messages],stream = True, **settings
+    ):
+        token = stream_resp.choices[0]["delta"].get("content","")
+        await msg.stream_token(token)
+    
+    #Updating the prompt answer to the answer generated by the LLM
+    prompt.completion = msg.content
+    #Updating the message to set the context right.
+    msg.prompt = prompt
+
+    await msg.send()

requirements.txt

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+chainlit==0.7.0
+openai==0.28.0
+python-dotenv==1.0.0