Update app.py

app.py

@@ -3,6 +3,10 @@ import os
 import pickle
 import time
 import g4f
+import tempfile
+import PyPDF2
+from pdf2image import convert_from_path
+import pytesseract
 
 st.set_page_config(page_title="MEDICAL ASSISTANT")
 
@@ -65,6 +69,9 @@ def display_chats_sidebar():
                 st.session_state.conversations = []
                 st.session_state.current_conversation = []
 
+    if st.sidebar.button('Summarize Bills', key="summarize_bills", use_container_width=True):
+        st.session_state.page = "summarize_bills"
+
     with st.sidebar.container():
         st.header('Conversations')
         for idx, conversation in enumerate(st.session_state.conversations):
@@ -75,23 +82,59 @@ def display_chats_sidebar():
                     st.session_state.current_conversation = st.session_state.conversations[idx]
 
 
+def summarize_bill():
+    st.header("Summarize Bills")
+
+    if st.button("Back to Chat"):
+        st.session_state.page = "chat"
+
+    uploaded_file = st.file_uploader("Upload a Bill", type=['pdf'])
+    if uploaded_file is not None:
+        with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
+            tmp_file.write(uploaded_file.read())
+            extracted_text = extract_text_from_pdf(tmp_file.name)
+
+        if st.button('Summarize'):
+            # Assuming g4f.ChatCompletion can be used for summarization
+            # Replace with appropriate summarization logic if needed
+            summary = g4f.ChatCompletion.create(
+                model="gpt-3.5-turbo",
+                messages=[{"role": "user", "content": extracted_text}],
+                temperature=0.5,  # You can adjust parameters as needed
+                max_tokens=150  # Adjust the token limit as needed
+            )
+            st.text_area("Summary", summary, height=400)
+
+
+def extract_text_from_pdf(file_path: str) -> str:
+    try:
+        with open(file_path, 'rb') as file:
+            reader = PyPDF2.PdfReader(file)
+            text = ''
+            for page_number in range(len(reader.pages)):
+                page = reader.pages[page_number]
+                text += page.extract_text()
+        return text
+    except Exception as e:
+        try:
+            images = convert_from_path(file_path)
+            extracted_texts = [pytesseract.image_to_string(image) for image in images]
+            return "\n".join(extracted_texts)
+        except Exception as e:
+            raise ValueError(f"Failed to process {file_path} using PDF Reader and OCR. Error: {e}")
+
+
 def main_app():
     for message in st.session_state.current_conversation:
         with st.chat_message(message["role"]):
             st.write(message["content"])
 
     def generate_response(prompt_input):
-        string_dialogue = '''
-        You are a virtual medical assistant/advisor with extensive knowledge in general health, medicine, and wellness. 
-        Your role is to provide helpful, informative, and non-diagnostic advice on general health questions, such as tips for maintaining a healthy lifestyle,
-        explanations of medical conditions in layman's terms, and general information about medications and treatments. 
-        You do not provide personal medical consultations, diagnoses, or treatment recommendations.
-        You are programmed to refrain from answering any queries that are not related to general medical knowledge or advice.
-        '''
+        string_dialogue = "You are a helpful Medical Assistant. You will Only respond to Medical related Queries. Say Sorry to any other Type of Queries."
         for dict_message in st.session_state.current_conversation:
             string_dialogue += dict_message["role"].capitalize() + ": " + dict_message["content"] + "\\n\\n"
 
-        prompt = f"{string_dialogue}\n  QUESTION:  {prompt_input} Assistant: "
+        prompt = f"{string_dialogue}\n  {prompt_input} Assistant: "
         response_generator = g4f.ChatCompletion.create(
             model="gpt-3.5-turbo",
             messages=[{"role": "user", "content": prompt}],
@@ -119,4 +162,10 @@ def main_app():
 
 
 display_chats_sidebar()
-main_app()
+if st.session_state.get('page') == "summarize_bills":
+    summarize_bill()
+elif st.session_state.get('page') == "chat":
+    main_app()
+else:
+    # Default page when the app starts or when the state is not set
+    main_app()