initial commit

Dockerfile

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+FROM python:3.9
+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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+# You can find this code for Chainlit python streaming here (https://docs.chainlit.io/concepts/streaming/python)
+
+# OpenAI Chat completion
+
+import openai #importing openai for API usage
+import chainlit as cl #importing chainlit for our app
+from chainlit.input_widget import Select, Switch, Slider #importing chainlit settings selection tools
+from chainlit.prompt import Prompt, PromptMessage #importing prompt tools 
+from chainlit.playground.providers import ChatOpenAI #importing ChatOpenAI tools
+
+# You only need the api key inserted here if it's not in your .env file
+# openai.api_key = ""
+
+# 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: 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.Message(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)
+
+    # Update the prompt object with the completion
+    prompt.completion = msg.content
+    msg.prompt = prompt
+
+    # Send and close the message stream
+    await msg.send()

chainlit.md

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+# Simple demo ! 🚀🤖

requirements.txt

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+chainlit
+openai