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import streamlit as st
import requests
import json
import base64
from PIL import Image
import io
# Function to encode the image
def encode_image(image_file):
return base64.b64encode(image_file.getvalue()).decode('utf-8')
# Set up the Streamlit page
st.set_page_config(page_title="LLM Chat Interface", page_icon="🤖")
st.title("LLM Chat Interface")
# Input for API endpoint and token
api_endpoint = st.sidebar.text_input("API Endpoint", "http://209.222.10.17:8000/v1/chat/completions")
api_token = st.sidebar.text_input("API Token", type="password")
# File uploader for image
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
# Text input for user message
user_input = st.text_area("Enter your message:", height=100)
if st.button("Send"):
if not api_token:
st.error("Please enter an API token.")
elif not user_input:
st.error("Please enter a message.")
else:
# Prepare the message content
content = [{"type": "text", "text": user_input}]
# If an image is uploaded, add it to the content
if uploaded_file is not None:
# Encode and add the image
image_base64 = encode_image(uploaded_file)
content.append({
"type": "image_url",
"image_url": {"url": f"data:image/jpeg;base64,{image_base64}"}
})
# Prepare the request payload
payload = {
"model": "mistralai/Pixtral-12B-2409",
"messages": [{"role": "user", "content": content}]
}
# Send the request to the API
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {api_token}"
}
with st.spinner("Waiting for response..."):
try:
response = requests.post(api_endpoint, headers=headers, json=payload)
response.raise_for_status()
result = response.json()
# Display the response
st.subheader("Response:")
st.write(result['choices'][0]['message']['content'])
except requests.exceptions.RequestException as e:
st.error(f"An error occurred: {str(e)}")
# Display the uploaded image
if uploaded_file is not None:
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image", use_column_width=True)
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