app.py

import streamlit as st
import requests
import json
import time
import os
api_url = os.getenv("API_URL")
auth_token = os.getenv("AUTH_TOKEN")


# Set page config
st.set_page_config(
    page_title="Product Hunt Thread Summarizer",
    layout="wide",
    initial_sidebar_state="collapsed"
)

# Custom CSS for header and banners
st.markdown(
    """
    <style>
    /* Main header with Product Hunt icon */
    #main-header {
        display: flex;
        align-items: center;
        margin-bottom: 10px;
    }
    #main-header img {
        width: 50px;
        height: 50px;
        margin-right: 15px;
        border-radius: 4px;
    }
    #main-header h1 {
        font-size: 32px;
        margin: 0;
        color: #333;
    }
    /* Inferless banner without border */
    #inferless-banner {
        display: flex;
        align-items: center;
        background-color: #ffffff;
        padding: 10px 15px;
        margin-bottom: 20px;
        border-radius: 8px;
    }
    #inferless-banner img {
        width: 40px;
        height: 40px;
        margin-right: 10px;
        border-radius: 4px;
    }
    #inferless-banner .inferless-text {
        font-size: 18px;
        font-weight: 600;
        color: #333;
    }
    </style>
    """,
    unsafe_allow_html=True
)

# Main header: Product Hunt Thread Summarizer with Product Hunt icon
st.markdown(
    """
    <div id="main-header">
        <img src="https://i.tracxn.com/logo/company/588f54924f2a60b6aae128ac436d95a4?format=webp&height=120&width=120" alt="Product Hunt Logo">
        <h1>Product Hunt Thread Summarizer</h1>
    </div>
    """,
    unsafe_allow_html=True
)

# Powered by Inferless banner (without border)
st.markdown(
    """
    <div id="inferless-banner">
        <img src="https://i.tracxn.com/logo/company/1678863153264_9e6a9a4d-b955-42b3-895e-b94ade13c997.jpeg?format=webp&height=120&width=120" alt="Inferless Logo">
        <div class="inferless-text">Powered by Inferless</div>
    </div>
    """,
    unsafe_allow_html=True
)

# Input field for thread URL
thread_url = st.text_input(
    label="Enter  URL",
    placeholder="https://www.producthunt.com/p/graphite/you-re-doing-code-reviews-wrong-ama-w-ceo-of-graphite",
    help="Paste the URL you want to summarize"
)

# Button to call your local inference API
if st.button("Summarize"):
    if thread_url.strip():
        with st.spinner("Analyzing thread..."):
            # Build request payload
            headers = {
                'Content-Type': 'application/json',
                'Authorization': f'Bearer {auth_token}'
            }

            payload = {
                "inputs": [
                    {
                        "name": "url",
                        "shape": [1],
                        "data": [thread_url],
                        "datatype": "BYTES"
                    },
                    {
                        "name": "temperature",
                        "optional": True,
                        "shape": [1],
                        "data": [0.15],
                        "datatype": "FP64"
                    },
                    {
                        "name": "top_p",
                        "optional": True,
                        "shape": [1],
                        "data": [1],
                        "datatype": "FP64"
                    },
                    {
                        "name": "repetition_penalty",
                        "optional": True,
                        "shape": [1],
                        "data": [1],
                        "datatype": "FP64"
                    },
                    {
                        "name": "top_k",
                        "optional": True,
                        "shape": [1],
                        "data": [-1],
                        "datatype": "INT32"
                    },
                    {
                        "name": "max_tokens",
                        "optional": True,
                        "shape": [1],
                        "data": [1024],
                        "datatype": "INT32"
                    },
                    {
                        "name": "seed",
                        "optional": True,
                        "shape": [1],
                        "data": [4424234],
                        "datatype": "INT32"
                    }
                ]
            }

            
            
            
            try:
                # Send POST request to your local model server
                response = requests.post(api_url, headers=headers, json=payload,timeout=300)
                response.raise_for_status()  # Raise HTTPError if status != 200

                # Parse JSON response
                data = response.json()
                summary_text = data["outputs"][0]["data"][0]

                # Display the result in Streamlit
                st.markdown("### Summary")
                st.write(summary_text)

            except requests.exceptions.RequestException as e:
                st.error(f"Error calling the model API: {e}")
    else:
        st.error("Please enter a valid URL.")