Update app.py

app.py

@@ -1,145 +1,120 @@
-from flask import Flask, render_template, request, jsonify, redirect, url_for
-from huggingface_hub import InferenceClient
 import os
 import json
+from flask import Flask, render_template, request, jsonify, redirect, url_for
+from werkzeug.utils import secure_filename
+from huggingface_hub import InferenceClient
 import pandas as pd
-import PyPDF2
 import docx
-from werkzeug.utils import secure_filename
+from PyPDF2 import PdfReader
 
 app = Flask(__name__)
-app.config["UPLOAD_FOLDER"] = "uploads"
-app.config["HISTORY_FILE"] = "history.json"
 
-# Initialize Hugging Face API client
-API_KEY = "APIHUGGING"  # Replace with your key
-client = InferenceClient(api_key=API_KEY)
-
-# Allowed file extensions
+# Set up file upload configurations
+UPLOAD_FOLDER = "uploads"
+app.config["UPLOAD_FOLDER"] = UPLOAD_FOLDER
 ALLOWED_EXTENSIONS = {"txt", "csv", "json", "pdf", "docx"}
 
+# Retrieve Hugging Face API key securely from environment variables
+api_key = os.getenv("HF_API_KEY")
+if not api_key:
+    raise ValueError("Hugging Face API key not found. Set 'HF_API_KEY' in your Space secrets.")
+
+# Initialize Hugging Face Inference Client
+client = InferenceClient(api_key=api_key)
 
-# Utility: Check allowed file types
+
+# Function to check allowed file types
 def allowed_file(filename):
-    return "." in filename and filename.rsplit(".", 1)[1].lower() in ALLOWED_EXTENSIONS
+    return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
 
 
-# Utility: Load conversation history
-def load_history():
+# Function to read uploaded files and extract content
+def extract_file_content(filepath, file_type):
+    content = ""
+    try:
+        if file_type == "txt":
+            with open(filepath, "r", encoding="utf-8") as file:
+                content = file.read()
+        elif file_type == "csv":
+            df = pd.read_csv(filepath)
+            content = df.to_string()
+        elif file_type == "json":
+            with open(filepath, "r", encoding="utf-8") as file:
+                content = json.dumps(json.load(file), indent=4)
+        elif file_type == "pdf":
+            reader = PdfReader(filepath)
+            content = "".join(page.extract_text() for page in reader.pages)
+        elif file_type == "docx":
+            doc = docx.Document(filepath)
+            content = "\n".join(paragraph.text for paragraph in doc.paragraphs)
+    except Exception as e:
+        raise ValueError(f"Error extracting file content: {e}")
+    return content
+
+
+# Function to send content to Hugging Face model
+def get_bot_response(prompt):
     try:
-        with open(app.config["HISTORY_FILE"], "r") as file:
-            return json.load(file)
-    except FileNotFoundError:
-        return []
-
-
-# Utility: Save conversation history
-def save_history(history):
-    with open(app.config["HISTORY_FILE"], "w") as file:
-        json.dump(history, file, indent=4)
-
-
-# Utility: Extract text from files
-def extract_text(file_path, file_type):
-    if file_type == "txt":
-        with open(file_path, "r") as f:
-            return f.read()
-    elif file_type == "csv":
-        df = pd.read_csv(file_path)
-        return df.to_string()
-    elif file_type == "json":
-        with open(file_path, "r") as f:
-            data = json.load(f)
-            return json.dumps(data, indent=4)
-    elif file_type == "pdf":
-        text = ""
-        with open(file_path, "rb") as f:
-            reader = PyPDF2.PdfReader(f)
-            for page in reader.pages:
-                text += page.extract_text()
-        return text
-    elif file_type == "docx":
-        doc = docx.Document(file_path)
-        return "\n".join([p.text for p in doc.paragraphs])
-    else:
-        return ""
-
-
-# Hugging Face Chat Response
-def get_bot_response(messages):
-    stream = client.chat.completions.create(
-        model="Qwen/Qwen2.5-Coder-32B-Instruct",
-        messages=messages,
-        max_tokens=500,
-        stream=True
-    )
-    bot_response = ""
-    for chunk in stream:
-        if chunk.choices and len(chunk.choices) > 0:
-            new_content = chunk.choices[0].delta.content
-            bot_response += new_content
-    return bot_response
-
-
-@app.route("/")
-def home():
-    history = load_history()
-    return render_template("home.html", history=history)
-
-
-@app.route("/upload", methods=["POST"])
+        response = client.text_generation(
+            prompt=prompt,
+            model="Qwen/Qwen2.5-Coder-32B-Instruct",
+            max_tokens=500
+        )
+        return response
+    except Exception as e:
+        return f"Error in model response: {e}"
+
+
+# Route: Home Page (File Upload Form)
+@app.route("/", methods=["GET", "POST"])
 def upload_file():
-    if "file" not in request.files:
-        return redirect(request.url)
+    if request.method == "POST":
+        # Check if file is uploaded
+        if "file" not in request.files:
+            return jsonify({"error": "No file part"}), 400
 
-    file = request.files["file"]
-    if file and allowed_file(file.filename):
-        filename = secure_filename(file.filename)
-        file_path = os.path.join(app.config["UPLOAD_FOLDER"], filename)
-        os.makedirs(app.config["UPLOAD_FOLDER"], exist_ok=True)
-        file.save(file_path)
+        file = request.files["file"]
 
-        # Extract text from file
-        file_type = filename.rsplit(".", 1)[1].lower()
-        extracted_text = extract_text(file_path, file_type)
+        if file.filename == "":
+            return jsonify({"error": "No selected file"}), 400
 
-        # Update conversation history
-        history = load_history()
-        history.append({"role": "user", "content": f"File content:\n{extracted_text}"})
+        if file and allowed_file(file.filename):
+            filename = secure_filename(file.filename)
+            filepath = os.path.join(app.config["UPLOAD_FOLDER"], filename)
+            os.makedirs(app.config["UPLOAD_FOLDER"], exist_ok=True)
+            file.save(filepath)
 
-        # Get response from Hugging Face API
-        bot_response = get_bot_response(history)
-        history.append({"role": "assistant", "content": bot_response})
+            # Extract file content
+            file_type = filename.rsplit(".", 1)[1].lower()
+            try:
+                content = extract_file_content(filepath, file_type)
+            except Exception as e:
+                return jsonify({"error": str(e)}), 500
 
-        save_history(history)
+            # Send content to Hugging Face model
+            response = get_bot_response(content)
 
-        return jsonify({"response": bot_response})
-    else:
-        return jsonify({"error": "Invalid file type"}), 400
+            return jsonify({"response": response})
 
+        else:
+            return jsonify({"error": "File type not allowed"}), 400
 
-@app.route("/generate", methods=["POST"])
-def generate_response():
-    data = request.json
-    user_message = data.get("message")
-    if not user_message:
-        return jsonify({"error": "Message is required"}), 400
+    return render_template("upload.html")
 
-    # Update conversation history
-    history = load_history()
-    history.append({"role": "user", "content": user_message})
 
-    # Get response from Hugging Face API
-    bot_response = get_bot_response(history)
-    history.append({"role": "assistant", "content": bot_response})
+# Route: Retrieve Model Response (API Endpoint)
+@app.route("/generate", methods=["POST"])
+def generate_response():
+    data = request.get_json()
+    prompt = data.get("prompt")
 
-    save_history(history)
+    if not prompt:
+        return jsonify({"error": "No prompt provided"}), 400
 
-    return jsonify({"response": bot_response})
+    # Send prompt to Hugging Face model
+    response = get_bot_response(prompt)
+    return jsonify({"response": response})
 
 
 if __name__ == "__main__":
-    os.makedirs(app.config["UPLOAD_FOLDER"], exist_ok=True)
     app.run(debug=True)
-
-