Update app.py

app.py

@@ -1,39 +1,77 @@
-from flask import Flask, request, jsonify
-from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
-import torch
+from flask import Flask, request, jsonify, send_file
+from flask_cors import CORS
+from fpdf import FPDF
+from docx import Document
+import openai
+import os
+import uuid
 
 app = Flask(__name__)
+CORS(app)
 
-# Load Mistral 7B model from Hugging Face (ensure your Space is on GPU)
-model_name = "mistralai/Mistral-7B-Instruct-v0.2"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")
-
-generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
-
-@app.route("/")
-def home():
-    return "✅ UniSolve (Mistral 7B) backend is running."
+openai.api_key = os.environ.get("OPENAI_API_KEY")
 
 @app.route("/generate", methods=["POST"])
 def generate():
-    data = request.get_json()
-    subject = data.get("subject", "")
-    citation = data.get("citation", "")
-    case_study = data.get("case_study", "")
-    questions = data.get("questions", "")
-
-    prompt = (
-        f"Subject: {subject}\n"
-        f"Citation Style: {citation}\n"
-        f"Case Study: {case_study}\n"
-        f"Questions: {questions}\n\n"
-        f"Write a full, detailed academic response. Use {citation} citation style."
-    )
+    try:
+        data = request.json
+        subject = data.get("category", "")
+        citation = data.get("citationStyle", "")
+        case_study = data.get("caseStudy", "")
+        questions = data.get("questions", "")
+
+        prompt = (
+            f"You are an academic writing assistant for university students. "
+            f"Respond in Times New Roman, using university-level detail. Use the following:\n"
+            f"- Subject: {subject}\n"
+            f"- Citation Style: {citation}\n"
+            f"- Case Study: {case_study}\n"
+            f"- Questions: {questions}\n"
+            f"Respond with a clear, structured academic answer using {citation} citation style. "
+            f"Use credible university-grade sources with proper citations. "
+            f"Do NOT add a conclusion unless asked. Only answer the questions."
+        )
+
+        completion = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo-0125",
+            messages=[{"role": "user", "content": prompt}],
+            max_tokens=3000,
+            temperature=0.7
+        )
+
+        result = completion.choices[0].message["content"]
+        return jsonify({"response": result})
+
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
+
+@app.route("/export/pdf", methods=["POST"])
+def export_pdf():
+    try:
+        content = request.json.get("content", "")
+        filename = f"/tmp/{uuid.uuid4().hex}.pdf"
+        pdf = FPDF()
+        pdf.add_page()
+        pdf.set_auto_page_break(auto=True, margin=15)
+        pdf.set_font("Times", size=12)
+        for line in content.split("\n"):
+            pdf.multi_cell(0, 10, line)
+        pdf.output(filename)
+        return send_file(filename, as_attachment=True)
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
 
+@app.route("/export/word", methods=["POST"])
+def export_word():
     try:
-        result = generator(prompt, max_new_tokens=1024, do_sample=True, temperature=0.7)
-        return jsonify({"response": result[0]["generated_text"]})
+        content = request.json.get("content", "")
+        filename = f"/tmp/{uuid.uuid4().hex}.docx"
+        doc = Document()
+        doc.styles["Normal"].font.name = "Times New Roman"
+        for line in content.split("\n"):
+            doc.add_paragraph(line)
+        doc.save(filename)
+        return send_file(filename, as_attachment=True)
     except Exception as e:
         return jsonify({"error": str(e)}), 500