Implement LLM chat application

Dockerfile

@@ -1,13 +1,24 @@
-FROM python:3.9
+FROM python:3.10-slim
 
+# Add user - this is the user that will run the app
 RUN useradd -m -u 1000 user
 USER user
 ENV PATH="/home/user/.local/bin:$PATH"
 
+# Set the working directory
 WORKDIR /app
 
+# Copy the requirements file
 COPY --chown=user ./requirements.txt requirements.txt
+
+# Install the dependencies
 RUN pip install --no-cache-dir --upgrade -r requirements.txt
 
+# Copy the app to the container
 COPY --chown=user . /app
-CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
+
+# Expose the port
+EXPOSE 7860
+
+# Run the app
+CMD ["chainlit", "run", "app.py", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -1,7 +1,26 @@
-from fastapi import FastAPI
+import os
+import chainlit as cl
+from openai import OpenAI
 
-app = FastAPI()
+# Initialize the OpenAI client
+client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
 
-@app.get("/")
-def greet_json():
-    return {"Hello": "World!"}
+@cl.on_message
+async def main(message: cl.Message):
+    # Get user's message
+    user_message = message.content
+    
+    # Call OpenAI API
+    response = client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": user_message}
+        ],
+        temperature=0.7,
+    )
+    
+    # Send response back to user
+    await cl.Message(
+        content=response.choices[0].message.content,
+    ).send()

chainlit.md

@@ -0,0 +1,11 @@
+# Welcome to My LLM App! 👋
+
+This is a simple LLM application built with Chainlit.
+
+## How to use
+
+1. Type your message in the chat box below
+2. Press Enter or click the Send button
+3. Wait for the AI to respond
+
+Feel free to ask me anything!

requirements.txt

@@ -1,2 +1,5 @@
-fastapi
-uvicorn[standard]
+chainlit==0.7.501
+openai
+tiktoken
+langchain
+python-dotenv