Create app.py

app.py

@@ -0,0 +1,71 @@
+import os
+import fitz  # PyMuPDF for PDFs
+import pytesseract
+from PIL import Image
+import io
+from flask import Flask, request, jsonify
+from mistralai.client import MistralClient
+from mistralai.models.chat_completion import ChatMessage
+
+# Initialize Flask app
+app = Flask(__name__)
+
+# Set Mistral API Key
+os.environ["MISTRAL_API_KEY"] = "your_api_key_here"
+client = MistralClient(api_key=os.getenv("MISTRAL_API_KEY"))
+
+# Set Tesseract Path for Windows (if needed)
+# pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"
+
+def extract_text_from_pdf(pdf_path):
+    """Extract text from PDFs, using OCR for scanned pages."""
+    doc = fitz.open(pdf_path)
+    text = ""
+
+    for page in doc:
+        extracted_text = page.get_text("text")
+        
+        # If no text, apply OCR (for scanned PDFs)
+        if not extracted_text.strip():
+            pix = page.get_pixmap()
+            img = Image.open(io.BytesIO(pix.tobytes()))
+            extracted_text = pytesseract.image_to_string(img)
+
+        text += extracted_text + "\n"
+    
+    return text
+
+def query_mistral(pdf_text, user_query):
+    """Send extracted text and user query to Mistral AI."""
+    messages = [
+        ChatMessage(role="system", content="You are an AI that answers questions based on PDFs."),
+        ChatMessage(role="user", content=f"Document content: {pdf_text[:3000]}... (truncated)"),
+        ChatMessage(role="user", content=f"User question: {user_query}")
+    ]
+    
+    response = client.chat(model="mistral-7b", messages=messages)
+    return response.choices[0].message.content
+
+@app.route("/upload", methods=["POST"])
+def upload_pdf():
+    if "file" not in request.files:
+        return jsonify({"error": "No file uploaded"}), 400
+
+    file = request.files["file"]
+    pdf_path = "uploaded.pdf"
+    file.save(pdf_path)
+
+    # Extract text
+    pdf_text = extract_text_from_pdf(pdf_path)
+    return jsonify({"message": "PDF uploaded and processed", "text": pdf_text[:500]})  # Preview
+
+@app.route("/chat", methods=["POST"])
+def chat():
+    data = request.json
+    user_query = data.get("query", "")
+    pdf_text = extract_text_from_pdf("uploaded.pdf")
+    response = query_mistral(pdf_text, user_query)
+    return jsonify({"response": response})
+
+if __name__ == "__main__":
+    app.run(debug=True)