Update file_utils.py

file_utils.py

@@ -1,105 +1,76 @@
-import fitz  # PyMuPDF
-from pptx import Presentation
-from openai import OpenAI
+import gradio as gr
 import os
-
-# === GPT-4 Client Setup ===
-client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
-
-# === Centralized LLM Caller ===
-def call_llm(prompt, system_message="You are a helpful assistant.", temperature=0.7):
-    response = client.chat.completions.create(
-        model="gpt-4",
-        messages=[
-            {"role": "system", "content": system_message},
-            {"role": "user", "content": prompt}
-        ],
-        temperature=temperature
-    )
-    return response.choices[0].message.content
-
-# === File Parsers ===
-def extract_text_from_pdf(pdf_path):
-    text = ""
-    with fitz.open(pdf_path) as doc:
-        for page in doc:
-            text += page.get_text()
-    return text
-
-
-def extract_text_from_txt(file_path):
-    with open(file_path, 'r', encoding='utf-8') as f:
-        return f.read()
-
-
-def extract_text_from_md(file_path):
-    with open(file_path, 'r', encoding='utf-8') as f:
-        return f.read()
-
-
-def extract_text_from_pptx(file_path):
-    text = ""
-    prs = Presentation(file_path)
-    for slide in prs.slides:
-        for shape in slide.shapes:
-            if hasattr(shape, "text"):
-                text += shape.text + "\n"
-    return text
-
-
-def extract_text_from_file(file):
-    if file is None:
-        return ""
-
-    name = file.name.lower()
-    if name.endswith(".pdf"):
-        return extract_text_from_pdf(file.name)
-    elif name.endswith(".txt"):
-        return extract_text_from_txt(file.name)
-    elif name.endswith(".md"):
-        return extract_text_from_md(file.name)
-    elif name.endswith(".pptx"):
-        return extract_text_from_pptx(file.name)
-    else:
-        return "Unsupported file type."
-
-
-# === GPT-4 Powered Content Generators ===
-def generate_summary(text):
-    prompt = f"""Please summarize the following study material in a concise and organized manner:
-
-{text}
-"""
-    return call_llm(prompt, system_message="You are a helpful study assistant.")
-
-
-def generate_flashcards(text):
-    prompt = f"""Based on the content below, create a set of helpful flashcards.
-Each flashcard should be formatted as:
-Q: Question?
-A: Answer.
-
-{text}
-"""
-    return call_llm(prompt, system_message="You are a flashcard generator assistant.")
-
-
-def generate_quiz(text):
-    prompt = f"""Create a short quiz (3-5 questions) based on the content below.
-Include a mix of multiple choice and short answer questions.
-
-{text}
-"""
-    return call_llm(prompt, system_message="You are a quiz generator assistant.")
-
-
-def answer_question(text, question):
-    prompt = f"""You are an AI tutor. Answer the following question based only on the content below.
-
-Content:
-{text}
-
-Question:
-{question}
-"""
-    return call_llm(prompt, system_message="You are a helpful and accurate tutor that stays grounded in provided content.")
+from file_utils import (
+    extract_text_from_file,
+    generate_summary,
+    generate_flashcards,
+    generate_quiz,
+    answer_question
+)
+
+
+def file_dashboard():
+    with gr.Column(elem_classes="file-panel") as file_panel:
+        gr.Markdown("""
+        <div style='text-align: center; margin-bottom: 1rem;'>
+            <img src='file/images/chatter_owl.png' width='100'>
+            <h2 style='margin-top: 0.5rem;'>📄 File-Based Learning with <strong>Chatter the Owl</strong></h2>
+            <p style='margin-bottom: 1rem;'>Upload your notes, textbooks, or slides, and let me turn them into summaries, quizzes, and flashcards!</p>
+        </div>
+        """)
+
+        file_upload = gr.File(label="📁 Upload Your Study Material", file_types=[".pdf", ".txt", ".md", ".pptx"])
+        question_box = gr.Textbox(label="💬 Ask a question about the uploaded file", lines=2)
+
+        with gr.Tabs():
+            with gr.Tab("📚 Summary"):
+                summary_output = gr.Textbox(label="Generated Summary", lines=6, interactive=False)
+
+            with gr.Tab("🧠 Flashcards"):
+                with gr.Accordion("Click to view generated flashcards", open=False):
+                    flashcard_output = gr.Textbox(label=None, lines=6, interactive=False, show_label=False)
+
+            with gr.Tab("❓ Quiz"):
+                with gr.Accordion("Click to view generated quiz questions", open=False):
+                    quiz_output = gr.Textbox(label=None, lines=6, interactive=False, show_label=False)
+
+            with gr.Tab("💬 Answer to Your Question"):
+                answer_output = gr.Textbox(label="Answer", lines=4, interactive=False)
+
+        text_state = gr.State("")
+
+        def handle_file_upload(file):
+            if file is None:
+                return "", "No file uploaded.", "", "", ""
+
+            text = extract_text_from_file(file)
+            if not text or "Unsupported file type" in text:
+                return "", text, "", "", ""
+
+            summary = generate_summary(text)
+            flashcards = generate_flashcards(text)
+            quiz = generate_quiz(text)
+            return text, summary, flashcards, quiz, ""
+
+        def handle_question(text, question):
+            if not text.strip():
+                return "Please upload a file first."
+            if not question.strip():
+                return "Please enter a question."
+            return answer_question(text, question)
+
+        file_upload.change(
+            fn=handle_file_upload,
+            inputs=[file_upload],
+            outputs=[text_state, summary_output, flashcard_output, quiz_output, answer_output],
+            show_progress="minimal"
+        )
+
+        question_box.change(
+            fn=handle_question,
+            inputs=[text_state, question_box],
+            outputs=[answer_output],
+            show_progress="minimal"
+        )
+
+        return file_panel