Update app.py

app.py

@@ -1,115 +1,32 @@
-import openai
-import gradio as gr
+from flask import Flask, request, jsonify
+from openai import OpenAI
 import os
-from fpdf import FPDF
-import tempfile
 
-# Set your OpenAI API key
-openai.api_key = "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"
+app = Flask(__name__)
 
-history = []
+openai_api_key = os.getenv("OPENAI_API_KEY")
+client = OpenAI(api_key=openai_api_key)
 
-def generate_essay(category, case_study, questions):
-    prompt = (
-        f"You are EssayMate, a university-level academic writing assistant specialised in {category}. "
-        "Your job is to help students respond to complex academic prompts with accurate, structured, and well-referenced answers.\n\n"
-        "Your rules are:\n"
-        "- Use a formal academic tone.\n"
-        "- Include only reliable, university-grade sources with Harvard-style citations.\n"
-        "- If no source can be confirmed, write: '[Citation available upon request or from verified academic databases]'.\n"
-        "- Do not include examples unless explicitly asked.\n"
-        "- Do not include a conclusion unless requested.\n\n"
-        f"CASE STUDY:\n{case_study}\n\n"
-        f"QUESTIONS:\n{questions}\n\n"
-        "Write the response below:\n"
-    )
-
-    try:
-        response = openai.chat.completions.create(
-            model="gpt-3.5-turbo",
-            messages=[
-                {"role": "system", "content": f"You are a Harvard-style academic writing assistant in {category}."},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.7,
-            max_tokens=1800
-        )
-        reply = response.choices[0].message.content.strip()
-        history.append(reply)
-        return reply
-    except Exception as e:
-        return f"⚠️ Error: {str(e)}"
-
-def download_pdf(text):
-    pdf = FPDF()
-    pdf.add_page()
-    pdf.set_auto_page_break(auto=True, margin=15)
-    pdf.set_font("Arial", size=12)
-    for line in text.split("\n"):
-        pdf.multi_cell(0, 10, line)
-    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf")
-    pdf.output(temp_file.name)
-    return temp_file.name
-
-# Gradio UI
-with gr.Blocks(css="""
-    body {
-        background-color: #f2f8ff;
-        font-family: 'Inter', 'Helvetica Neue', Helvetica, sans-serif;
-        color: #003366;
-    }
-    .gr-box, textarea, input, .gr-textbox textarea {
-        background-color: #e6f0ff !important;
-        border: 1px solid #99c2ff !important;
-        border-radius: 10px !important;
-        padding: 14px !important;
-        font-size: 15px;
-        color: #003366 !important;
-    }
-    .gr-button {
-        background-color: #0066cc !important;
-        color: white !important;
-        border-radius: 10px !important;
-        padding: 12px 20px !important;
-        font-size: 16px !important;
-        font-weight: 600;
-        transition: background-color 0.3s ease;
-    }
-    .gr-button:hover {
-        background-color: #005bb5 !important;
-    }
-    h1, h2, h3, .gr-markdown, .gr-markdown h1 {
-        color: #002c5e !important;
-        font-weight: 600;
-    }
-    label {
-        font-weight: 600;
-        color: #002855 !important;
-    }
-""") as iface:
-    gr.Markdown("# 🧠 EssayMate — Academic AI Writing Tool")
-    gr.Markdown("AI-powered academic support with Harvard-style referencing. Designed for students in Nursing, Psychology, Law, Education, and more.")
-
-    with gr.Row():
-        category = gr.Dropdown(
-            choices=["Nursing", "Psychology", "Law", "Education", "Other"],
-            label="📂 Subject Area",
-            value="Nursing"
-        )
+@app.route("/generate", methods=["POST"])
+def generate():
+    data = request.json
+    case_study = data.get("case_study", "")
+    questions = data.get("questions", "")
+    subject = data.get("category", "")
+    style = data.get("citation", "")
 
-    with gr.Row():
-        with gr.Column():
-            case_study = gr.Textbox(lines=10, label="🩺 Case Study")
-        with gr.Column():
-            questions = gr.Textbox(lines=20, label="❓ Questions")
-
-    generate_btn = gr.Button("✍️ Generate Response")
-    output = gr.Textbox(lines=30, label="📄 EssayMate Output")
-
-    download_btn = gr.Button("📄 Download as PDF")
-    file_output = gr.File(label="Download Link")
+    full_prompt = (
+        f"You are an academic assistant for {subject}.\n"
+        f"Use {style} citation style. Write clear, well-structured university-level responses.\n\n"
+        f"Case Study:\n{case_study}\n\n"
+        f"Questions:\n{questions}\n"
+    )
 
-    generate_btn.click(fn=generate_essay, inputs=[category, case_study, questions], outputs=output)
-    download_btn.click(fn=download_pdf, inputs=output, outputs=file_output)
+    response = client.chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": full_prompt}],
+        temperature=0.5,
+        max_tokens=2048
+    )
 
-iface.launch()
+    return jsonify({"answer": response.choices[0].message.content.strip()})