Upload app.py

app.py

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+# 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": "#3e4a5b"},
+            "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": "#0b2545", "color": "white"},
+        }
+    )
+
+# Main content
+col1, col2, col3 = st.columns([1, 2, 1])
+
+with col2:
+    st.markdown("<h1 style='text-align: center;'>Disease Analysis GPT</h1>", unsafe_allow_html=True)
+    st.markdown("<h3 style='text-align: center;'>What do you want to know?</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)}")