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Futuresony commited on Dec 12, 2024

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5117938

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1 Parent(s): 4a85dca

Update app.py

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app.py +122 -34

app.py CHANGED Viewed

@@ -5,59 +5,147 @@ import os
 # Initialize the Flask app
 app = Flask(__name__)
-# Initialize the Hugging Face Inference Client (Replace with your actual model identifier)
 client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")
-# Parameters from the image
-MAX_TOKENS = 1520
-TEMPERATURE = 0.7
-TOP_P = 0.95
-# In-memory storage for active chats (to maintain chat history)
-chat_history = {}
-@app.route("/")
-def home():
-    return render_template("editor.html")
-@app.route("/generate_code", methods=["POST"])
-def generate_code():
-    # Get the user ID (or session) and the prompt
-    user_id = request.json.get("user_id")
-    prompt = request.json.get("prompt")
-    # Get chat history for the user or initialize it
-    if user_id not in chat_history:
-        chat_history[user_id] = []
-    # Append the user's prompt to the chat history
-    chat_history[user_id].append({"role": "user", "content": prompt})
-    # System message
     system_message = "You are a friendly chatbot."
-    # Build the messages for the model
     messages = [{"role": "system", "content": system_message}]
-    messages.extend(chat_history[user_id])  # Add previous conversation history
-    # Generate the response
-    generated_code = ""
     for msg in client.chat_completion(
         messages=messages,
-        max_tokens=MAX_TOKENS,
-        temperature=TEMPERATURE,
-        top_p=TOP_P,
         stream=True,
     ):
         token = msg.choices[0].delta.content
-        generated_code += token
-    # Save the assistant's response to the chat history
-    chat_history[user_id].append({"role": "assistant", "content": generated_code})
-    return jsonify({"code": generated_code})
 if __name__ == "__main__":
     # Use PORT environment variable or default to 7860
     port = int(os.getenv("PORT", 7860))
-    app.run(host="0.0.0.0", port=port)

 # Initialize the Flask app
 app = Flask(__name__)
+# Initialize the Hugging Face Inference Client
 client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")
+# HTML template for the app
+HTML_TEMPLATE = """
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Chat Interface</title>
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            margin: 20px;
+        }
+        .container {
+            max-width: 800px;
+            margin: auto;
+        }
+        .chat-box {
+            border: 1px solid #ccc;
+            padding: 10px;
+            border-radius: 5px;
+            background-color: #f9f9f9;
+            height: 400px;
+            overflow-y: auto;
+        }
+        .chat-input {
+            width: 100%;
+            padding: 10px;
+            margin-top: 10px;
+            border: 1px solid #ccc;
+            border-radius: 5px;
+        }
+        .response {
+            background-color: #e8f5e9;
+            border: 1px solid #81c784;
+            padding: 8px;
+            margin-top: 5px;
+            border-radius: 5px;
+            white-space: pre-wrap; /* Preserve formatting */
+        }
+        .bold-italic {
+            font-weight: bold;
+            font-style: italic;
+        }
+        .code-box {
+            background-color: #f4f4f4;
+            border: 1px solid #ddd;
+            padding: 10px;
+            font-family: monospace;
+            white-space: pre-wrap;
+            overflow-x: auto;
+            border-radius: 5px;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>Chat Interface</h1>
+        <div class="chat-box" id="chat-box">
+            <!-- Chat history will appear here -->
+        </div>
+        <textarea id="message" class="chat-input" placeholder="Type your message here..."></textarea>
+        <button onclick="sendMessage()">Send</button>
+    </div>
+    <script>
+        function sendMessage() {
+            const message = document.getElementById("message").value;
+            const chatBox = document.getElementById("chat-box");
+            if (!message.trim()) return; // Don't send empty messages
+            // Append the user's message to the chat box
+            const userMessage = document.createElement("div");
+            userMessage.textContent = "You: " + message;
+            chatBox.appendChild(userMessage);
+            // Clear the input field
+            document.getElementById("message").value = "";
+            // Send the message to the server
+            fetch("/respond", {
+                method: "POST",
+                headers: {
+                    "Content-Type": "application/json",
+                },
+                body: JSON.stringify({ message: message }),
+            })
+                .then((response) => response.json())
+                .then((data) => {
+                    // Append the assistant's response to the chat box
+                    const botMessage = document.createElement("div");
+                    botMessage.innerHTML = `<div class="response">${data.response}</div>`;
+                    chatBox.appendChild(botMessage);
+                    // Scroll to the bottom of the chat box
+                    chatBox.scrollTop = chatBox.scrollHeight;
+                })
+                .catch((error) => console.error("Error:", error));
+        }
+    </script>
+</body>
+</html>
+"""
+@app.route("/")
+def home():
+    return HTML_TEMPLATE
+@app.route("/respond", methods=["POST"])
+def respond():
+    # Extract data from the request
+    data = request.json
+    message = data.get("message", "")
+    # Define system message
     system_message = "You are a friendly chatbot."
+    # Build the chat history and message
     messages = [{"role": "system", "content": system_message}]
+    messages.append({"role": "user", "content": message})
+    # Call the Hugging Face API
+    response = ""
     for msg in client.chat_completion(
         messages=messages,
+        max_tokens=512,
         stream=True,
+        temperature=0.7,
+        top_p=0.95,
     ):
         token = msg.choices[0].delta.content
+        response += token
+    # Return the response in bold italic format
+    response = response.replace("**", '<span class="bold-italic">').replace("**", "</span>")
+    return jsonify({"response": response})
 if __name__ == "__main__":
     # Use PORT environment variable or default to 7860
     port = int(os.getenv("PORT", 7860))
+    app.run(host="0.0.0.0", port=port)