xcv

Sleeping

App Files Files Community

soiz1 commited on Apr 18

Commit

2b448ee

verified ·

1 Parent(s): f3cbed6

Update app.py

Browse files

Files changed (1) hide show

app.py +51 -234

app.py CHANGED Viewed

@@ -1,212 +1,28 @@
-from flask import Flask, request, Response, render_template
 from huggingface_hub import hf_hub_download
 from llama_cpp import Llama
-app = Flask(__name__)
-# HTML content as a string
-HTML_CONTENT = '''
-<!DOCTYPE html>
-<html lang="en">
-<head>
-  <meta charset="UTF-8">
-  <meta http-equiv="X-UA-Compatible" content="IE=edge">
-  <meta name="viewport" content="width=device-width, initial-scale=1.0">
-  <link rel="stylesheet" href="https://fonts.googleapis.com/css2?family=Material+Symbols+Rounded:opsz,wght,FILL,GRAD@20..48,100..700,0..1,-50..200" />
-  <link rel="preconnect" href="https://fonts.googleapis.com">
-  <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
-  <link href="https://fonts.googleapis.com/css2?family=Poppins:wght@300&display=swap" rel="stylesheet">
-  <title>AI Chat Interface</title>
-  <style>
-    *{
-      padding: 0;
-      margin: 0;
-      font-family: 'Poppins', sans-serif;
-      box-sizing: border-box;
-    }
-    body {
-  overflow: hidden;
-}
-/* Hide scrollbar only for Webkit browsers (Chrome, Safari, Opera) */
-::-webkit-scrollbar {
-  display: none;
-}
-    body{
-      width: 100%;
-      height: 100vh;
-      background-color: #212121;
-    }
-    .chat{
-      display: flex;
-      gap: 20px;
-      padding: 25px;
-      color: #fff;
-      font-size: 15px;
-      font-weight: 300;
-    }
-    .chat img{
-      width: 35px;
-      height: 35px;
-      border-radius: 50px;
-    }
-    .response{
-      background-color: #212121;
-    }
-    .messagebar{
-      position: fixed;
-      bottom: 0;
-      height: 5rem;
-      width: 100%;
-      display: flex;
-      align-items: center;
-      justify-content: center;
-      background-color: #212121;
-    }
-    .messagebar .bar-wrapper{
-      background-color: #2f2f2f;
-      border-radius: 20px;
-      width: 70vw;
-      padding: 10px;
-      display: flex;
-      align-items: center;
-      justify-content: space-between;
-    }
-    .bar-wrapper input{
-      width: 100%;
-      padding: 5px;
-      border: none;
-      outline: none;
-      font-size: 14px;
-      background: none;
-      color: #ccc;
-    }
-    .bar-wrapper input::placeholder{
-      color: #ccc;
-    }
-    .messagebar button{
-      display: flex;
-      align-items: center;
-      justify-content: center;
-      background: none;
-      border: none;
-      color: #fff;
-      cursor: pointer;
-    }
-    .message-box{
-      height: calc(100vh - 5rem);
-      overflow-y: auto;
-    }
-  </style>
-</head>
-<body>
-  <div class="chatbox-wrapper">
-    <div class="message-box" id="chat-container">
-      <div class="chat response">
-         <img src="https://freelogopng.com/images/all_img/1681038800chatgpt-logo-black.png" alt="AI">
-        <span>こんにちは! <br>
-          どのようにお手伝いできますか？
-        </span>
-      </div>
-    </div>
-    <div class="messagebar">
-      <div class="bar-wrapper">
-        <input type="text" id="user-input" placeholder="Enter your message...">
-        <button onclick="sendMessage()">
-          <span class="material-symbols-rounded">
-            send
-          </span>
-        </button>
-      </div>
-    </div>
-  </div>
-  <script>
-    const messageBar = document.querySelector("#user-input");
-    const sendBtn = document.querySelector(".bar-wrapper button");
-    const messageBox = document.querySelector("#chat-container");
-    function addMessage(message, isUser) {
-      const messageElement = document.createElement('div');
-      messageElement.classList.add('chat');
-      if (!isUser) messageElement.classList.add('response');
-      const imgElement = document.createElement('img');
-       imgElement.src = isUser ? "https://wallpaperaccess.com/full/1595920.jpg" : "https://freelogopng.com/images/all_img/1681038800chatgpt-logo-black.png";
-      imgElement.alt = isUser ? "User" : "AI";
-      const spanElement = document.createElement('span');
-      spanElement.textContent = message;
-      messageElement.appendChild(imgElement);
-      messageElement.appendChild(spanElement);
-      messageBox.appendChild(messageElement);
-      messageBox.scrollTop = messageBox.scrollHeight;
-    }
-    function sendMessage() {
-      const message = messageBar.value.trim();
-      if (message) {
-        addMessage(message, true);
-        messageBar.value = '';
-        const eventSource = new EventSource(`/chat?message=${encodeURIComponent(message)}`);
-        let aiResponse = '';
-        eventSource.onmessage = function(event) {
-          if (event.data === '[DONE]') {
-            eventSource.close();
-          } else {
-            aiResponse += event.data;
-            const aiMessageElement = document.querySelector('.chat.response:last-child span');
-            if (aiMessageElement) {
-              aiMessageElement.textContent = aiResponse;
-            } else {
-              addMessage(aiResponse, false);
-            }
-          }
-        };
-        eventSource.onerror = function(error) {
-          console.error('EventSource failed:', error);
-          eventSource.close();
-        };
-      }
-    }
-    messageBar.addEventListener('keypress', function(event) {
-      if (event.key === 'Enter') {
-        sendMessage();
-      }
-    });
-  </script>
-</body>
-</html>
-'''
 def download_model():
     model_name = "bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF"
-    model_file = "DeepSeek-Coder-V2-Lite-Instruct-Q6_K.gguf"  # or another quantized version
-    return hf_hub_download(repo_id=model_name, filename=model_file)
 def initialize_model():
     try:
         model_path = download_model()
         return Llama(
             model_path=model_path,
             n_ctx=4096,
             n_threads=4,
-            n_gpu_layers=-1  # Use GPU if available
         )
     except Exception as e:
         print(f"Error initializing model: {e}")
@@ -219,45 +35,46 @@ system_prompt = (
     "and technical questions, providing clear and concise answers."
 )
-chat_history = [{"role": "system", "content": system_prompt}]
-@app.route('/')
-def index():
-    return render_template('index.html')  # You should move your HTML to a templates folder
-@app.route('/chat')
-def chat():
-    global chat_history
-    user_message = request.args.get('message', '')
-    if not llm:
-        return Response("data: Model not loaded\n\ndata: [DONE]\n\n", content_type='text/event-stream')
-    chat_history.append({"role": "user", "content": user_message})
-    def generate():
-        ai_response = ""
-        # Format messages for the model
-        messages = [{"role": msg["role"], "content": msg["content"]} for msg in chat_history]
-        stream = llm.create_chat_completion(
-            messages=messages,
-            max_tokens=1000,
-            stop=["User:"],
-            stream=True
-        )
-        for output in stream:
-            chunk = output['choices'][0]['delta'].get('content', '')
-            if chunk:
-                ai_response += chunk
-                yield f"data: {chunk}\n\n"
-        chat_history.append({"role": "assistant", "content": ai_response.strip()})
-        if len(chat_history) > 10:  # Limit history to last 10 messages
-            chat_history = chat_history[-10:]
-        yield "data: [DONE]\n\n"
-    return Response(generate(), content_type='text/event-stream')
-if __name__ == '__main__':
-    app.run(debug=True, port=7860, host="0.0.0.0")

+import gradio as gr
 from huggingface_hub import hf_hub_download
 from llama_cpp import Llama
+import html
+# モデルのダウンロードと初期化
 def download_model():
     model_name = "bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF"
+    model_file = "DeepSeek-Coder-V2-Lite-Instruct-Q6_K.gguf"
+    try:
+        return hf_hub_download(repo_id=model_name, filename=model_file)
+    except Exception as e:
+        print(f"Model download failed: {e}")
+        return None
 def initialize_model():
     try:
         model_path = download_model()
+        if not model_path:
+            return None
         return Llama(
             model_path=model_path,
             n_ctx=4096,
             n_threads=4,
+            n_gpu_layers=-1
         )
     except Exception as e:
         print(f"Error initializing model: {e}")
     "and technical questions, providing clear and concise answers."
 )
+# チャットボットの処理関数
+def respond(message, chat_history):
+    if not message or not llm:
+        return chat_history
+    # チャット履歴の構築（システムプロンプト + 過去の会話 + 新しいメッセージ）
+    messages = [{"role": "system", "content": system_prompt}]
+    for user_msg, bot_msg in chat_history:
+        messages.append({"role": "user", "content": user_msg})
+        messages.append({"role": "assistant", "content": bot_msg})
+    messages.append({"role": "user", "content": message})
+    # AIからのレスポンス生成
+    response = llm.create_chat_completion(
+        messages=messages,
+        max_tokens=1000,
+        stop=["User:"],
+        stream=False
+    )
+    ai_response = response['choices'][0]['message']['content']
+    # チャット履歴に追加
+    chat_history.append((message, ai_response))
+    return chat_history
+# Gradioインターフェースの作成
+with gr.Blocks() as demo:
+    gr.Markdown("# AI Coding Assistant")
+    chatbot = gr.Chatbot(height=500)
+    msg = gr.Textbox(label="Your Message")
+    clear = gr.Button("Clear")
+    msg.submit(respond, [msg, chatbot], chatbot)
+    clear.click(lambda: None, None, chatbot, queue=False)
+# アプリの起動
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)