Delete app (3).py

app (3).py

@@ -1,154 +0,0 @@
-# Configure page settings (MUST BE FIRST STREAMLIT COMMAND)
-import streamlit as st
-from streamlit_option_menu import option_menu
-from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
-from PyPDF2 import PdfReader
-
-# Set page config
-st.set_page_config(
-    page_title="Disease Analysis GPT",
-    layout="wide",
-    initial_sidebar_state="expanded"
-)
-
-# Load Hugging Face models and tokenizer for text generation
-@st.cache_resource
-def load_model():
-    tokenizer = AutoTokenizer.from_pretrained("harishussain12/Disease_Managment")
-    model = AutoModelForCausalLM.from_pretrained("harishussain12/Disease_Managment")
-    return tokenizer, model
-
-# Function to create a text generation pipeline
-@st.cache_resource
-def create_pipeline():
-    tokenizer, model = load_model()
-    return pipeline("text-generation", model=model, tokenizer=tokenizer)
-
-# Function to extract text from PDF file
-def read_pdf(file):
-    try:
-        reader = PdfReader(file)
-        text = ""
-        for page in reader.pages:
-            text += page.extract_text()
-        return text
-    except Exception as e:
-        return f"Error reading PDF: {e}"
-
-# Load pipelines
-text_pipeline = create_pipeline()
-
-# Custom CSS for styling
-st.markdown(
-    """
-    <style>
-    body {
-        font-family: 'Arial', sans-serif;
-    }
-    .stButton button {
-        background-color: #0b2545;
-        color: white;
-        border: none;
-        border-radius: 25px;
-        padding: 8px 20px;
-        font-size: 14px;
-        font-weight: bold;
-        cursor: pointer;
-    }
-    .stButton button:hover {
-        background-color: #0a1b35;
-    }
-    .search-box {
-        border-radius: 20px;
-        border: 1px solid #ccc;
-        padding: 10px;
-        width: 100%;
-        font-size: 16px;
-        background-color: #ffffff;
-    }
-    .info-box {
-        background-color: #f8f9fa;
-        border-left: 5px solid #0b2545;
-        padding: 15px;
-        border-radius: 5px;
-        font-size: 14px;
-    }
-    </style>
-    """,
-    unsafe_allow_html=True
-)
-
-# Sidebar
-with st.sidebar:
-    new_chat_button = st.button("New Chat", key="new_chat", help="Start a new chat to ask a different question.")
-    if new_chat_button:
-        st.session_state.clear()  # Clear session state to simulate a new chat
-
-    selected = option_menu(
-        menu_title=None,
-        options=[" Home", " Discover"],
-        icons=["house", "search"],
-        menu_icon="cast",
-        default_index=0,
-        styles={
-            "container": {"padding": "0!important", "background-color": "#1a1a1a"},
-            "icon": {"color": "#ffffff", "font-size": "16px"},
-            "nav-link": {
-                "font-size": "15px", 
-                "text-align": "left", 
-                "margin": "0px", 
-                "color": "#ffffff",
-                "font-weight": "bold",
-                "padding": "10px 20px",
-            },
-            "nav-link-selected": {"background-color": "#1a1a1a", "color": "white"},
-        }
-    )
-
-# Main content
-col1, col2, col3 = st.columns([1, 2, 1])
-
-with col2:
-    st.markdown("<h1 style='text-align: center;'>poonawala dermatologist</h1>", unsafe_allow_html=True)
-    st.markdown("<h3 style='text-align: center;'>How can I help you?</h3>", unsafe_allow_html=True)
-
-    # Model selection (now including Document Analysis)
-    model_selection = st.selectbox(
-        "Select a model", 
-        options=["Disease Analysis", "Document Analysis"], 
-        index=0
-    )
-
-    # If the user selects Document Analysis, show an error and prompt them to switch to Disease Analysis
-    if model_selection == "Document Analysis":
-        st.error("Please switch to 'Disease Analysis' model for generating responses. Document Analysis is not available in this version.")
-
-    # Search box
-    search_input = st.text_input(
-        "", 
-        placeholder="Type your question here...", 
-        label_visibility="collapsed",
-        help="Ask anything related to disease management."
-    )
-
-    # File upload below search box
-    uploaded_file = st.file_uploader("Upload a PDF file", type="pdf", help="Attach relevant files or documents to your query.")
-
-    if search_input:
-        with st.spinner("Generating response..."):
-            try:
-                if model_selection == "Disease Analysis":
-                    context = ""
-                    if uploaded_file is not None:
-                        file_content = read_pdf(uploaded_file)
-                        if "Error" in file_content:
-                            st.error(file_content)
-                        else:
-                            context = file_content
-
-                    query_input = search_input + (f"\n\nContext:\n{context}" if context else "")
-                    response = text_pipeline(query_input, max_length=200, num_return_sequences=1)
-                    st.markdown(f"### Response:\n{response[0]['generated_text']}")
-
-            except Exception as e:
-                st.error(f"Error generating response: {str(e)}")