Update app.py

app.py

@@ -1,165 +1,201 @@
-import gradio as gr
-import logging
-
-from config import SHARE_GRADIO_WITH_PUBLIC_URL
-from chains import qa_chain, summarization_chain
-
-logger = logging.getLogger(__name__)
-
-# Translation dictionary
-TRANSLATIONS = {
-    "en": {
-        "title": "# 📚 Study Buddy: AI Learning Assistant",
-        "subtitle": "## 🤖 A smart, user-friendly chatbot for students!",
-        "summary_subtitle": "## 📄 Upload Notes for Summarization",
-        "chat_input_label": "Type your question here:",
-        "chat_placeholder": "e.g., Explain Newton's laws",
-        "chat_button_label": "Get Answer",
-        "summary_button_label": "Summarize Notes",
-        "upload_file_label": "Upload .txt or .pdf file",
-        "summary_output_label": "Summary",
-        "language_label": "Language / Langue",
-        "ai_response_label": "AI Response"
-    },
-    "fr": {
-        "title": "# 📚 Study Buddy: Assistant d'apprentissage IA",
-        "subtitle": "## 🤖 Un chatbot intelligent et convivial pour les étudiants!",
-        "summary_subtitle": "## 📄 Subir notas para resumir",
-        "chat_input_label": "Tapez votre question ici:",
-        "chat_placeholder": "ex : Expliquez les lois de Newton",
-        "chat_button_label": "Obtenir une réponse",
-        "summary_button_label": "Résumer les notes",
-        "upload_file_label": "Téléchargez un fichier .txt ou .pdf",
-        "summary_output_label": "Résumé",
-        "language_label": "Langue / Language",
-        "ai_response_label": "Réponse de l'IA"
-    }
-}
-
-# Function to process user queries
-def chatbot_response(user_input, lang):
-    try:
-        response = qa_chain.invoke({"question": user_input})
-        logger.info("chatbot_response completed")
-        return response
-    except Exception as e:
-        msg = f"Error : {e}"
-        logger.exception(msg)
-        return TRANSLATIONS[lang].get("error_message", "Sorry, an error occurred while processing your request.")
-
-# Function to summarize notes
-def summarize_text(text, lang):
-    try:
-        summary = summarization_chain.invoke({"document_text": text})
-        logger.info("summarize_text completed")
-        return summary
-    except Exception as e:
-        msg = f"Error : {e}"
-        logger.exception(msg)
-        return TRANSLATIONS[lang].get("error_message", "Sorry, an error occurred while summarizing your notes.")
-
-# Function to update UI labels dynamically
-def update_language(lang):
-    return (
-        TRANSLATIONS[lang]["title"],
-        TRANSLATIONS[lang]["subtitle"],
-        TRANSLATIONS[lang]["chat_input_label"],
-        TRANSLATIONS[lang]["chat_placeholder"],
-        TRANSLATIONS[lang]["chat_button_label"],
-        TRANSLATIONS[lang]["upload_file_label"],
-        TRANSLATIONS[lang]["summary_button_label"],
-        TRANSLATIONS[lang]["summary_output_label"],
-        TRANSLATIONS[lang]["ai_response_label"]
-    )
-
-# Gradio UI
-def create_interface():
-    with gr.Blocks(css="body { font-family: sans-serif; background-color: #f9f9f9; }") as study_buddy:
-        
-        # Default to English
-        lang = "en"
-
-        title = gr.Markdown(f"{TRANSLATIONS[lang]['title']}")
-        
-        with gr.Row():
-            with gr.Column():
-                gr.Markdown("", height=4) 
-                
-                language = gr.Radio(
-                    choices=["en", "fr"],
-                    value=lang,
-                    label=TRANSLATIONS[lang]["language_label"]
-                )
-                
-                gr.Markdown("", height=4)
-                               
-                subtitle = gr.Markdown(f"{TRANSLATIONS[lang]['subtitle']}")
-                
-                chat_input = gr.Textbox(
-                    label=TRANSLATIONS[lang]["chat_input_label"],
-                    lines=4,
-                    placeholder=TRANSLATIONS[lang]["chat_placeholder"]
-                )
-
-            with gr.Column():
-                gr.Markdown("", height=4)
-                summary_subtitle = gr.Markdown(f"{TRANSLATIONS[lang]['summary_subtitle']}")
-                file_input = gr.File(file_types=[".pdf", ".txt"])
-                file_label = gr.Markdown(TRANSLATIONS[lang]["upload_file_label"])  # Separate label
-                
-        with gr.Row():
-            with gr.Column():
-                
-                chat_button = gr.Button(TRANSLATIONS[lang]["chat_button_label"], variant="primary")
-                chat_output = gr.Textbox(label=TRANSLATIONS[lang]["ai_response_label"], lines=5, interactive=True)
-
-                # Bind chatbot response function
-                chat_button.click(
-                    chatbot_response, 
-                    inputs=[chat_input, language], 
-                    outputs=chat_output
-                )
-
-            with gr.Column():
-            
-                summary_button = gr.Button(TRANSLATIONS[lang]["summary_button_label"], variant="primary")
-                summary_output = gr.Textbox(label=TRANSLATIONS[lang]["summary_output_label"], lines=5, interactive=True)
-
-                # Bind summarization function
-                summary_button.click(
-                    summarize_text, 
-                    inputs=[file_input, language], 
-                    outputs=summary_output
-                )
-
-        # Update labels dynamically when the language changes
-        def update_labels(lang):
-            return (
-                TRANSLATIONS[lang]["title"],
-                TRANSLATIONS[lang]["subtitle"],
-                TRANSLATIONS[lang]["summary_subtitle"],
-                TRANSLATIONS[lang]["chat_input_label"],
-                TRANSLATIONS[lang]["chat_placeholder"],
-                TRANSLATIONS[lang]["chat_button_label"],
-                TRANSLATIONS[lang]["summary_button_label"],
-                TRANSLATIONS[lang]["summary_output_label"],
-                TRANSLATIONS[lang]["ai_response_label"],
-                TRANSLATIONS[lang]["upload_file_label"]
-            )
-
-        language.change(
-            update_labels, 
-            inputs=[language], 
-            outputs=[
-                title, subtitle, summary_subtitle, 
-                chat_input, chat_input, 
-                chat_button, 
-                summary_button, summary_output, chat_output, file_label  # Update file label separately
-            ]
-        )
-
-    return study_buddy
-
-if __name__ == "__main__":
-    study_buddy = create_interface()
-    study_buddy.launch(share=SHARE_GRADIO_WITH_PUBLIC_URL)
+import gradio as gr
+import logging
+import PyPDF2
+
+from config import SHARE_GRADIO_WITH_PUBLIC_URL
+from chains import qa_chain, summarization_chain
+
+logger = logging.getLogger(__name__)
+
+# Translation dictionary
+TRANSLATIONS = {
+    "en": {
+        "title": "# 📚 Study Buddy: AI Learning Assistant",
+        "subtitle": "## 🤖 A smart, user-friendly chatbot for students!",
+        "summary_subtitle": "## 📄 Upload Notes for Summarization",
+        "chat_input_label": "Type your question here:",
+        "chat_placeholder": "e.g., Explain Newton's laws",
+        "chat_button_label": "Get Answer",
+        "summary_button_label": "Summarize Notes",
+        "upload_file_label": "Upload .txt or .pdf file",
+        "summary_output_label": "Summary",
+        "language_label": "Language / Langue",
+        "ai_response_label": "AI Response"
+    },
+    "fr": {
+        "title": "# 📚 Study Buddy: Assistant d'apprentissage IA",
+        "subtitle": "## 🤖 Un chatbot intelligent et convivial pour les étudiants!",
+        "summary_subtitle": "## 📄 Subir notas para resumir",
+        "chat_input_label": "Tapez votre question ici:",
+        "chat_placeholder": "ex : Expliquez les lois de Newton",
+        "chat_button_label": "Obtenir une réponse",
+        "summary_button_label": "Résumer les notes",
+        "upload_file_label": "Téléchargez un fichier .txt ou .pdf",
+        "summary_output_label": "Résumé",
+        "language_label": "Langue / Language",
+        "ai_response_label": "Réponse de l'IA"
+    }
+}
+
+# Function to process user queries
+def chatbot_response(user_input, lang):
+    try:
+        response_output = qa_chain.invoke({"question": user_input})
+        response = response_output.content
+        logger.info("chatbot_response completed")
+        print("> chatbot_response completed")
+        return response
+    except Exception as e:
+        msg = f"Error : {e}"
+        logger.exception(msg)
+        print(msg)
+        return TRANSLATIONS[lang].get("error_message", "Sorry, an error occurred while processing your request.")
+
+# Function to summarize notes
+def summarize_pdf(pdf, lang):
+    try:
+        with open(pdf, "rb") as file:
+            reader = PyPDF2.PdfReader(file)
+            page = reader.pages[0]  # Get the first page
+            text = page.extract_text()
+            print(text)
+        summary = summarize_text(text, lang)
+        logger.info("summarize_pdf completed")
+        print("> summarize_pdf completed")
+        return summary
+    except Exception as e:
+        msg = f"Error : {e}"
+        logger.exception(msg)
+        print(msg)
+        return TRANSLATIONS[lang].get("error_message", "Sorry, an error occurred while summarizing your notes.")
+    
+# Function to summarize notes
+def summarize_text(text, lang):
+    try:
+        summary_output = summarization_chain.invoke({"document_text": text})
+        print(summary_output)
+        summary = summary_output.content
+        logger.info("summarize_text completed")
+        print("> summarize_text completed")
+        return summary
+    except Exception as e:
+        msg = f"Error : {e}"
+        logger.exception(msg)
+        print(msg)
+        return TRANSLATIONS[lang].get("error_message", "Sorry, an error occurred while summarizing your notes.")
+
+# Function to update UI labels dynamically
+def update_language(lang):
+    return (
+        TRANSLATIONS[lang]["title"],
+        TRANSLATIONS[lang]["subtitle"],
+        TRANSLATIONS[lang]["chat_input_label"],
+        TRANSLATIONS[lang]["chat_placeholder"],
+        TRANSLATIONS[lang]["chat_button_label"],
+        TRANSLATIONS[lang]["upload_file_label"],
+        TRANSLATIONS[lang]["summary_button_label"],
+        TRANSLATIONS[lang]["summary_output_label"],
+        TRANSLATIONS[lang]["ai_response_label"]
+    )
+
+# Gradio UI
+def create_interface():
+    with gr.Blocks(css="body { font-family: sans-serif; background-color: #f9f9f9; }") as study_buddy:
+        
+        # Default to English
+        lang = "en"
+
+        title = gr.Markdown(f"{TRANSLATIONS[lang]['title']}")
+        
+        with gr.Row():
+            with gr.Column():
+                gr.Markdown("", height=4) 
+                
+                language = gr.Radio(
+                    choices=["en", "fr"],
+                    value=lang,
+                    label=TRANSLATIONS[lang]["language_label"]
+                )
+                
+                gr.Markdown("", height=4)
+                               
+                subtitle = gr.Markdown(f"{TRANSLATIONS[lang]['subtitle']}")
+                
+                chat_input = gr.Textbox(
+                    # label=TRANSLATIONS[lang]["chat_input_label"]
+                    label= "Type your question here: / Tapez votre question ici:",
+                    lines=4,
+                    placeholder=TRANSLATIONS[lang]["chat_placeholder"]
+                )
+
+            with gr.Column():
+                gr.Markdown("", height=4)
+                summary_subtitle = gr.Markdown(f"{TRANSLATIONS[lang]['summary_subtitle']}")
+                file_input = gr.File(label="File / Fichier",file_types=[".pdf", ".txt"])
+                file_label = gr.Markdown(TRANSLATIONS[lang]["upload_file_label"])  # Separate label
+                
+        with gr.Row():
+            with gr.Column():
+                
+                chat_button = gr.Button(TRANSLATIONS[lang]["chat_button_label"], variant="primary")
+                chat_output = gr.Textbox(
+                    # label=TRANSLATIONS[lang]["ai_response_label"], 
+                    label = "AI Response / Réponse de l'IA",
+                    lines=5, interactive=True
+                )
+
+                # Bind chatbot response function
+                chat_button.click(
+                    chatbot_response, 
+                    inputs=[chat_input, language], 
+                    outputs=chat_output
+                )
+
+            with gr.Column():
+            
+                summary_button = gr.Button(TRANSLATIONS[lang]["summary_button_label"], variant="primary")
+                summary_output = gr.Textbox(
+                    # label=TRANSLATIONS[lang]["summary_output_label"],
+                    label="Summary / Résumé",
+                    lines=5, 
+                    interactive=True
+                )
+
+                # Bind summarization function
+                summary_button.click(
+                    summarize_pdf, 
+                    inputs=[file_input, language], 
+                    outputs=summary_output
+                )
+
+        # Update labels dynamically when the language changes
+        def update_labels(lang):
+            return (
+                TRANSLATIONS[lang]["title"],
+                TRANSLATIONS[lang]["subtitle"],
+                TRANSLATIONS[lang]["summary_subtitle"],
+                TRANSLATIONS[lang]["chat_input_label"],
+                TRANSLATIONS[lang]["chat_placeholder"],
+                TRANSLATIONS[lang]["chat_button_label"],
+                TRANSLATIONS[lang]["summary_button_label"],
+                TRANSLATIONS[lang]["summary_output_label"],
+                TRANSLATIONS[lang]["ai_response_label"],
+                TRANSLATIONS[lang]["upload_file_label"]
+            )
+
+        language.change(
+            update_labels, 
+            inputs=[language], 
+            outputs=[
+                title, subtitle, summary_subtitle, 
+                chat_input, chat_input, 
+                chat_button, 
+                summary_button, summary_output, chat_output, file_label  # Update file label separately
+            ]
+        )
+
+    return study_buddy
+
+if __name__ == "__main__":
+    study_buddy = create_interface()
+    study_buddy.launch(share=SHARE_GRADIO_WITH_PUBLIC_URL)