Update app.py

app.py

@@ -1,2 +1,161 @@
-import os
-exec(os.environ.get('APP'))
+import streamlit as st
+import PyPDF2
+from huggingface_hub import InferenceClient
+
+# Initialize the Inference Client
+client = InferenceClient("meta-llama/Llama-3.2-3B-Instruct")
+
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+    uploaded_pdf=None
+):
+    messages = [{"role": "system", "content": system_message}]
+
+    # Add previous conversation history to the messages
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    # If a new message is entered, add it to the conversation history
+    messages.append({"role": "user", "content": message})
+
+    # If a PDF is uploaded, process its content
+    if uploaded_pdf is not None:
+        file_content = extract_pdf_text(uploaded_pdf)
+        if file_content:
+            messages.append({"role": "user", "content": f"Document Content: {file_content}"})
+
+    # Get response from the model
+    response = ""
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+    ):
+        token = message.choices[0].delta.content
+        response += token
+        yield response
+
+
+def extract_pdf_text(file):
+    """Extract text from a PDF file."""
+    try:
+        reader = PyPDF2.PdfReader(file)
+        text = ""
+        for page in reader.pages:
+            text += page.extract_text()
+        return text
+    except Exception as e:
+        return f"Error extracting text from PDF: {str(e)}"
+
+
+# Streamlit UI
+st.set_page_config(page_title="Health Assistant", layout="wide")
+
+# Custom CSS for Streamlit app
+st.markdown(
+    """
+    <style>
+    body {
+        background-color: #1e2a38; /* Dark blue background */
+        color: #ffffff; /* White text for readability */
+        font-family: 'Arial', sans-serif; /* Clean and modern font */
+    }
+    .stButton button {
+        background-color: #42B3CE !important; /* Light blue button */
+        color: #2e3b4e !important; /* Dark text for contrast */
+        border: none !important;
+        padding: 10px 20px !important;
+        border-radius: 8px !important;
+        font-size: 16px;
+        font-weight: bold;
+        transition: background-color 0.3s ease, transform 0.2s ease;
+    }
+    .stButton button:hover {
+        background-color: #3189A2 !important; /* Darker blue on hover */
+        transform: scale(1.05);
+    }
+    .stTextInput input {
+        background-color: #2f3b4d;
+        color: white;
+        border: 2px solid #42B3CE;
+        padding: 12px;
+        border-radius: 8px;
+        font-size: 16px;
+        transition: border 0.3s ease;
+    }
+    .stTextInput input:focus {
+        border-color: #3189A2;
+    }
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
+
+# Title and description
+st.title("Health Assistant Chat")
+st.subheader("Chat with your health assistant and upload a document for analysis")
+
+# System message for health-related responses
+system_message = (
+    "You are a virtual health assistant designed to provide accurate and reliable information "
+    "related to health, wellness, and medical topics. Your primary goal is to assist users with "
+    "their health-related queries, offer general guidance, and suggest when to consult a licensed "
+    "medical professional. If a user asks a question that is unrelated to health, wellness, or medical "
+    "topics, respond politely but firmly with: 'I'm sorry, I can't help with that because I am a virtual "
+    "health assistant designed to assist with health-related needs. Please let me know if you have any health-related questions.'"
+)
+
+# Upload a PDF file
+uploaded_pdf = st.file_uploader("Upload a PDF file (Optional)", type="pdf")
+
+# User input message
+message = st.text_input("Type your health-related question:")
+
+# History for conversation tracking
+if 'history' not in st.session_state:
+    st.session_state['history'] = []
+
+# Collect and display previous conversation history
+history = st.session_state['history']
+for user_message, assistant_message in history:
+    st.markdown(f"**You:** {user_message}")
+    st.markdown(f"**Assistant:** {assistant_message}")
+
+# Max tokens, temperature, and top-p sliders
+max_tokens = st.slider("Max new tokens", min_value=1, max_value=2048, value=512)
+temperature = st.slider("Temperature", min_value=0.1, max_value=4.0, value=0.7, step=0.1)
+top_p = st.slider("Top-p (nucleus sampling)", min_value=0.1, max_value=1.0, value=0.95, step=0.05)
+
+# Button to generate response
+if st.button("Generate Response"):
+    if message:
+        # Append the user's question to the conversation history
+        st.session_state.history.append((message, ""))
+        # Generate the response based on the user's input and any uploaded document
+        response = respond(
+            message,
+            st.session_state.history,
+            system_message,
+            max_tokens,
+            temperature,
+            top_p,
+            uploaded_pdf
+        )
+        # Display the response
+        for resp in response:
+            st.markdown(f"**Assistant:** {resp}")
+        # Update the conversation history with the assistant's response
+        st.session_state.history[-1] = (message, resp)
+    else:
+        st.error("Please enter a question to proceed.")