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Futuresony commited on Dec 12, 2024

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8a11c03

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1 Parent(s): 8c8e15f

Update app.py

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app.py +48 -135

app.py CHANGED Viewed

@@ -1,152 +1,65 @@
-from flask import Flask, request, jsonify, render_template
 from huggingface_hub import InferenceClient
-import os
-# 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)

+import gradio as gr
 from huggingface_hub import InferenceClient
 """
+For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+"""
+client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
     messages.append({"role": "user", "content": message})
     response = ""
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
         stream=True,
+        temperature=temperature,
+        top_p=top_p,
     ):
+        token = message.choices[0].delta.content
         response += token
+        yield response
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
+)
 if __name__ == "__main__":
+    demo.launch()