Create app.py

app.py

@@ -0,0 +1,202 @@
+import gradio as gr
+import requests
+import datetime
+import json
+import base64
+import tempfile
+import os
+
+# API endpoints
+LOGIN_URL = "http://164.52.195.95/login"
+CHAT_URL = "http://164.52.195.95/v1/chat/completions"
+
+# Global token
+access_token = None
+chat_history = []
+
+def login_user(username, password):
+    global access_token, chat_history
+    print("Attempting login...")
+    try:
+        response = requests.post(
+            LOGIN_URL,
+            headers={"Content-Type": "application/x-www-form-urlencoded"},
+            data={
+                "grant_type": "password",
+                "username": username,
+                "password": password,
+                "scope": "",
+                "client_id": "string",
+                "client_secret": "********"
+            }
+        )
+        print("Login response status:", response.status_code)
+        response.raise_for_status()
+        token_data = response.json()
+        access_token = token_data["access_token"]
+        chat_history = []
+        return gr.update(visible=False), gr.update(visible=True), "✅ Login successful!"
+    except Exception as e:
+        print("Login failed:", e)
+        return gr.update(), gr.update(), f"❌ Login failed: {e}"
+
+def make_return(chatbot, msg="", image=None, alert_text=None):
+    return chatbot, msg, image, gr.update(visible=bool(alert_text), value=alert_text or "")
+
+def send_message(message_text, image_files, chatbot):
+    global chat_history, access_token
+    print("Sending message:", message_text)
+    if access_token is None:
+        return make_return(chatbot + [{"role": "assistant", "content": "Please login first."}])
+
+    media_blocks = []
+    image_previews = []
+    if image_files:
+        for image_file in image_files:
+            try:
+                with open(image_file, "rb") as img_f:
+                    base64_image = base64.b64encode(img_f.read()).decode("utf-8")
+                data_uri = f"data:image/jpeg;base64,{base64_image}"
+                media_blocks.append({
+                    "type": "image_url",
+                    "image_url": {"url": data_uri}
+                })
+                image_previews.append(data_uri)
+            except Exception as e:
+                print("Error encoding image:", e)
+                return make_return(chatbot + [{"role": "user", "content": message_text}, {"role": "assistant", "content": f"Image processing failed: {e}"}], "", None, f"❌ Image processing failed: {e}")
+
+    message_group = []
+
+    for i in range(0, len(chatbot), 2):
+        user_msg = chatbot[i]
+        assistant_msg = chatbot[i + 1] if i + 1 < len(chatbot) else {"role": "assistant", "content": ""}
+
+        user_content = user_msg["content"]
+        if isinstance(user_content, str):
+            message_group.append({
+                "role": "user",
+                "content": [{"type": "text", "text": user_content}]
+            })
+        elif isinstance(user_content, list):
+            message_group.append({
+                "role": "user",
+                "content": user_content
+            })
+
+        if isinstance(assistant_msg["content"], str):
+            message_group.append({
+                "role": "assistant",
+                "content": assistant_msg["content"]
+            })
+
+    new_msg = [{"type": "text", "text": message_text}]
+    if media_blocks:
+        new_msg.extend(media_blocks)
+
+    message_group.append({
+        "role": "user",
+        "content": new_msg
+    })
+
+    payload = {
+        "model": "./models/Llama-3.2-11B-Vision-Instruct",
+        "messages": message_group,
+        "temperature": 0.3,
+        "max_tokens": 500,
+        "stream": True
+    }
+
+    # print("Final Payload:", json.dumps(payload, indent=2)[-1000:])
+
+    headers = {
+        "Authorization": f"Bearer {access_token}",
+        "Content-Type": "application/json"
+    }
+
+    response_text = ""
+    try:
+        with requests.post(CHAT_URL, headers=headers, json=payload, stream=True) as response:
+            print("Streaming response...")
+            if response.status_code != 200:
+                try:
+                    error_json = response.json()
+                    error_msg = error_json.get("message", "Unknown error")
+                except:
+                    error_msg = response.text
+                return make_return(chatbot, "", None, f"❌ API Error {response.status_code}: {error_msg}")
+
+            for line in response.iter_lines():
+                if line:
+                    line = line.decode("utf-8")
+                    print("Stream chunk:", line)
+                    if line.startswith("data:"):
+                        content = line[5:].strip()
+                        if content == "[DONE]":
+                            break
+                        try:
+                            data_json = json.loads(content)
+                            delta = data_json["choices"][0]["delta"]
+                            token = delta.get("content", "")
+                            response_text += token
+                            yield chatbot + [
+                                {"role": "user", "content": message_text},
+                                {"role": "assistant", "content": response_text}
+                            ], "", None, gr.update(visible=False)
+                        except Exception as json_err:
+                            print("Error parsing stream chunk:", json_err)
+                            continue
+    except Exception as e:
+        print("Error during streaming:", e)
+        return make_return(chatbot + [
+            {"role": "user", "content": message_text},
+            {"role": "assistant", "content": f"❌ Error: {e}"}
+        ], "", None, f"❌ {e}")
+
+    print("Final assistant response:", response_text)
+    return make_return(chatbot + [
+        {"role": "user", "content": message_text},
+        {"role": "assistant", "content": response_text}
+    ])
+
+# === UI ===
+with gr.Blocks(css="""
+    .message-input-box textarea {
+        border-radius: 16px !important;
+        padding: 12px !important;
+        background-color: #2c2c2c;
+        color: white;
+    }
+    .message-input-box textarea::placeholder {
+        color: #aaa;
+    }
+    .toast-alert {
+        background-color: #ff4d4f;
+        color: white;
+        padding: 10px 16px;
+        border-radius: 8px;
+        margin: 10px 0;
+        font-weight: bold;
+    }
+""") as app:
+    gr.Markdown("# 🤖 Secure AI Assistant Panel")
+
+    with gr.Column(visible=True) as login_page:
+        username = gr.Textbox(label="Username")
+        password = gr.Textbox(label="Password", type="password")
+        login_btn = gr.Button("Login")
+        login_status = gr.Markdown(visible=True)
+
+    with gr.Column(visible=False) as chat_page:
+        chatbot = gr.Chatbot(label="Chat", show_label=False, height=420, type="messages")
+        with gr.Row():
+            msg = gr.Textbox(label="", placeholder="Ask anything", elem_classes=["message-input-box"])
+            send_btn = gr.Button("Send")
+        img = gr.File(label="Upload Images (optional)", type="filepath", interactive=True, file_types=[".png", ".jpg", ".jpeg"], file_count="multiple")
+        image_preview = gr.Image(label="Image Preview", visible=False)
+        error_alert = gr.Markdown(visible=False, elem_classes=["toast-alert"])
+
+    login_btn.click(fn=login_user, inputs=[username, password], outputs=[login_page, chat_page, login_status])
+    send_btn.click(fn=send_message, inputs=[msg, img, chatbot], outputs=[chatbot, msg, image_preview, error_alert])
+
+app.launch()