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app.py

@@ -1,89 +1,85 @@
 import os, requests
+import gradio as gr
 from pypdf import PdfReader
-import streamlit as st
 
-# --- Setup ---
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
-if not OPENAI_API_KEY:
-    st.warning("⚠️ Set your OpenAI key using the next cell before generating.")
 OPENAI_URL = "https://api.openai.com/v1/chat/completions"
 MODEL = "gpt-4o-mini"
 MAX_PAGES, MAX_CHARS = 15, 10000
 
-# --- UI ---
-st.set_page_config(page_title="StudySnap", page_icon="📚", layout="centered")
-st.title("📚 StudySnap — Summaries + MCQs")
-tab1, tab2 = st.tabs(["Paste Text", "Upload PDF"])
-length = st.radio("Output length:", ["short","medium","long"], index=1, horizontal=True)
+def extract_text(pdf_file):
+    try:
+        reader = PdfReader(pdf_file)
+        pages = min(len(reader.pages), MAX_PAGES)
+        text = "\n".join((reader.pages[i].extract_text() or "") for i in range(pages))
+        lines = [ln.strip() for ln in text.splitlines() if ln.strip()]
+        return "\n".join(lines)[:MAX_CHARS]
+    except Exception:
+        return ""
 
-with tab1:
-    text_input = st.text_area("Paste your notes/article here:", height=220)
-
-with tab2:
-    pdf_file = st.file_uploader("Upload PDF (first 15 pages only)", type=["pdf"])
-
-# --- Helpers ---
-def extract_pdf_text(file):
-    r = PdfReader(file)
-    pages = min(len(r.pages), MAX_PAGES)
-    text = "\n".join(r.pages[i].extract_text() or "" for i in range(pages))
-    lines = [ln.strip() for ln in text.splitlines() if ln.strip()]
-    return "\n".join(lines)[:MAX_CHARS]
-
-def call_openai(system, user):
+def call_openai(system_prompt, user_content):
     if not OPENAI_API_KEY:
-        raise RuntimeError("API key missing.")
+        raise RuntimeError("Missing OPENAI_API_KEY (set it in Space → Settings → Secrets).")
     headers = {"Authorization": f"Bearer {OPENAI_API_KEY}", "Content-Type": "application/json"}
-    body = {"model": MODEL, "messages":[{"role":"system","content":system},{"role":"user","content":user}], "temperature":0.2}
+    body = {
+        "model": MODEL,
+        "messages": [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_content}
+        ],
+        "temperature": 0.2
+    }
     r = requests.post(OPENAI_URL, headers=headers, json=body, timeout=60)
     r.raise_for_status()
     return r.json()["choices"][0]["message"]["content"]
 
-# --- AI Wrappers ---
-def summarize(txt, length):
-    sys = ("You are a precise study assistant. Summarize in bullet points for MBA-level students. "
-           "short=5 bullets, medium=8–10, long=12–15.")
-    usr = f"Length: {length}\n\nCONTENT:\n{txt[:MAX_CHARS]}"
+def summarize(content, length):
+    sys = ("You are a precise study assistant for MBA-level students. "
+           "Summarize in clean bullet points; short=5 bullets, medium=8-10, long=12-15.")
+    usr = f"Length: {length}\n\nCONTENT:\n{content[:MAX_CHARS]}"
     return call_openai(sys, usr)
 
-def make_mcqs(txt):
-    sys = ("Create 10 single-answer MCQs with 4 options (A–D), plus 'Answer: X' and a short explanation. "
-           "Keep options plausible, style professional.")
-    usr = txt[:8000]
+def mcqs(content):
+    sys = ("Create 10 single-answer MCQs from the content. "
+           "Each item: question + 4 options labeled A)–D), then a line 'Answer: X' "
+           "and a one-sentence explanation.")
+    usr = f"CONTENT:\n{content[:8000]}"
     return call_openai(sys, usr)
 
-# --- Main ---
-if st.button("Generate", type="primary"):
-    if pdf_file:
-        content = extract_pdf_text(pdf_file)
-        title = pdf_file.name
-    elif text_input.strip():
-        content = text_input.strip()
-        title = "Pasted Text"
-    else:
-        st.warning("Paste text or upload a PDF first.")
-        st.stop()
+def generate(pasted_text, pdf_file, length):
+    source = ""
+    if pdf_file is not None:
+        source = extract_text(pdf_file)
+    if not source and pasted_text:
+        source = pasted_text.strip()[:MAX_CHARS]
+    if not source:
+        return "❌ Paste text or upload a PDF.", ""
+    if len(source) < 200:
+        return "❌ Input too short.", ""
 
-    if len(content) < 200:
-        st.warning("Input too short.")
-        st.stop()
+    try:
+        summary_md = summarize(source, length)
+    except Exception as e:
+        return f"❌ Summarization failed: {e}", ""
+    try:
+        mcq_md = mcqs(source)
+    except Exception as e:
+        mcq_md = f"❌ MCQ generation failed: {e}"
 
-    with st.spinner("Summarizing..."):
-        try:
-            summary = summarize(content, length)
-            st.success("✅ Summary Ready!")
-            st.markdown(summary)
-        except Exception as e:
-            st.error(f"Summarization failed: {e}")
-            st.stop()
+    summary_md = f"### 📄 Summary\n\n{summary_md}"
+    mcq_md = f"### 🧠 Practice — 10 MCQs\n\n{mcq_md}"
+    return summary_md, mcq_md
 
-    st.divider()
-    st.subheader("🧠 Practice — 10 MCQs")
-    with st.spinner("Generating questions..."):
-        try:
-            mcqs = make_mcqs(content)
-            st.markdown(mcqs)
-        except Exception as e:
-            st.error(f"MCQ generation failed: {e}")
+with gr.Blocks(title="StudySnap — Summaries + MCQs") as demo:
+    gr.Markdown("# 📚 StudySnap\nUpload a PDF or paste text. Get a clean summary + 10 MCQs.")
+    with gr.Row():
+        pasted = gr.Textbox(label="Paste Text", lines=10, placeholder="Paste your lecture notes or article here…")
+        pdf = gr.File(label="Upload PDF (first 15 pages)", file_types=[".pdf"])
+    length = gr.Radio(["short", "medium", "long"], value="medium", label="Output length")
+    btn = gr.Button("Generate", variant="primary")
+    out_summary = gr.Markdown()
+    out_mcq = gr.Markdown()
+    btn.click(fn=generate, inputs=[pasted, pdf, length], outputs=[out_summary, out_mcq])
 
-st.caption("MVP limits: 15 pages / 10k characters. We never store your files.")
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -1,4 +1,3 @@
-streamlit>=1.36
+gradio>=4.44
 pypdf>=4.2
-python-docx>=1.1
 requests>=2.32