|
| 1 | +import base64 |
| 2 | +import os |
| 3 | +import time |
| 4 | + |
| 5 | +import gradio as gr |
| 6 | +import modelscope_studio.components.antd as antd |
| 7 | +import modelscope_studio.components.antdx as antdx |
| 8 | +import modelscope_studio.components.base as ms |
| 9 | +import modelscope_studio.components.pro as pro |
| 10 | +from modelscope_studio.components.pro.chatbot import (ChatbotBotConfig, |
| 11 | + ChatbotPromptsConfig, |
| 12 | + ChatbotWelcomeConfig) |
| 13 | +from modelscope_studio.components.pro.multimodal_input import \ |
| 14 | + MultimodalInputUploadConfig |
| 15 | +from openai import OpenAI |
| 16 | + |
| 17 | +client = OpenAI( |
| 18 | + base_url='https://api-inference.modelscope.cn/v1/', |
| 19 | + api_key=os.getenv("MODELSCOPE_ACCESS_TOKEN"), # ModelScope Token |
| 20 | +) |
| 21 | + |
| 22 | +model = "Qwen/Qwen2.5-72B-Instruct" |
| 23 | + |
| 24 | + |
| 25 | +def prompt_select(input_value, e: gr.EventData): |
| 26 | + input_value["text"] = e._data["payload"][0]["value"]["description"] |
| 27 | + return gr.update(value=input_value) |
| 28 | + |
| 29 | + |
| 30 | +def clear(): |
| 31 | + return gr.update(value=None) |
| 32 | + |
| 33 | + |
| 34 | +def cancel(chatbot_value): |
| 35 | + chatbot_value[-1]["loading"] = False |
| 36 | + chatbot_value[-1]["status"] = "done" |
| 37 | + chatbot_value[-1]["footer"] = "Chat completion paused" |
| 38 | + |
| 39 | + return gr.update(value=chatbot_value), gr.update(loading=False), gr.update( |
| 40 | + disabled=False) |
| 41 | + |
| 42 | + |
| 43 | +def retry(chatbot_value, e: gr.EventData): |
| 44 | + index = e._data["payload"][0]["index"] |
| 45 | + chatbot_value = chatbot_value[:index] |
| 46 | + |
| 47 | + yield gr.update(loading=True), gr.update(value=chatbot_value), gr.update( |
| 48 | + disabled=True) |
| 49 | + for chunk in submit(None, chatbot_value): |
| 50 | + yield chunk |
| 51 | + |
| 52 | + |
| 53 | +def format_history(history): |
| 54 | + messages = [{"role": "system", "content": "You are a helpful assistant."}] |
| 55 | + for item in history: |
| 56 | + if item["role"] == "user": |
| 57 | + messages.append({ |
| 58 | + "role": |
| 59 | + "user", |
| 60 | + "content": [{ |
| 61 | + "type": "text", |
| 62 | + "text": item["content"] |
| 63 | + }] |
| 64 | + }) |
| 65 | + elif item["role"] == "assistant": |
| 66 | + # ignore thought message |
| 67 | + messages.append({"role": "assistant", "content": item["content"]}) |
| 68 | + return messages |
| 69 | + |
| 70 | + |
| 71 | +def submit(input_value, chatbot_value): |
| 72 | + if input_value is not None: |
| 73 | + chatbot_value.append({ |
| 74 | + "role": "user", |
| 75 | + "content": input_value["text"], |
| 76 | + }) |
| 77 | + history_messages = format_history(chatbot_value) |
| 78 | + chatbot_value.append({ |
| 79 | + "role": "assistant", |
| 80 | + "content": "", |
| 81 | + "loading": True, |
| 82 | + "status": "pending" |
| 83 | + }) |
| 84 | + yield { |
| 85 | + input: gr.update(value=None, loading=True), |
| 86 | + clear_btn: gr.update(disabled=True), |
| 87 | + chatbot: gr.update(value=chatbot_value) |
| 88 | + } |
| 89 | + |
| 90 | + try: |
| 91 | + response = client.chat.completions.create(model=model, |
| 92 | + messages=history_messages, |
| 93 | + stream=True) |
| 94 | + start_time = time.time() |
| 95 | + |
| 96 | + for chunk in response: |
| 97 | + chatbot_value[-1]["content"] += chunk.choices[0].delta.content |
| 98 | + chatbot_value[-1]["loading"] = False |
| 99 | + |
| 100 | + yield {chatbot: gr.update(value=chatbot_value)} |
| 101 | + |
| 102 | + chatbot_value[-1]["footer"] = "{:.2f}".format(time.time() - |
| 103 | + start_time) + 's' |
| 104 | + chatbot_value[-1]["status"] = "done" |
| 105 | + yield { |
| 106 | + clear_btn: gr.update(disabled=False), |
| 107 | + input: gr.update(loading=False), |
| 108 | + chatbot: gr.update(value=chatbot_value), |
| 109 | + } |
| 110 | + except Exception as e: |
| 111 | + chatbot_value[-1]["loading"] = False |
| 112 | + chatbot_value[-1]["status"] = "done" |
| 113 | + chatbot_value[-1]["content"] = "Failed to respond, please try again." |
| 114 | + yield { |
| 115 | + clear_btn: gr.update(disabled=False), |
| 116 | + input: gr.update(loading=False), |
| 117 | + chatbot: gr.update(value=chatbot_value), |
| 118 | + } |
| 119 | + raise e |
| 120 | + |
| 121 | + |
| 122 | +def close_copilot(): |
| 123 | + return gr.update(md=24), gr.update(md=0), gr.update(elem_style=dict( |
| 124 | + display="")) |
| 125 | + |
| 126 | + |
| 127 | +def open_copilot(): |
| 128 | + return gr.update(md=16), gr.update(md=8), gr.update(elem_style=dict( |
| 129 | + display="none")) |
| 130 | + |
| 131 | + |
| 132 | +def resize_window(e: gr.EventData): |
| 133 | + screen_width = e._data["screen"]["width"] |
| 134 | + is_mobile = screen_width < 768 |
| 135 | + return gr.update(visible=False if is_mobile else True), gr.update( |
| 136 | + visible=False if is_mobile else True) |
| 137 | + |
| 138 | + |
| 139 | +css = """ |
| 140 | +.copilot-container { |
| 141 | + height: calc(100vh - 32px - 21px - 16px); |
| 142 | +} |
| 143 | +
|
| 144 | +.copilot-container .copilot { |
| 145 | + height: 100%; |
| 146 | + padding: 10px; |
| 147 | + background: var(--background-fill-secondary); |
| 148 | + border-top: 1px solid var(--border-color-primary); |
| 149 | + border-right: 1px solid var(--border-color-primary); |
| 150 | + border-bottom: 1px solid var(--border-color-primary); |
| 151 | +} |
| 152 | +
|
| 153 | +
|
| 154 | +.copilot-container .content-body { |
| 155 | + height: 100%; |
| 156 | + overflow: auto; |
| 157 | +} |
| 158 | +
|
| 159 | +@media (max-width: 768px) { |
| 160 | + .copilot-container { |
| 161 | + height: auto; |
| 162 | + } |
| 163 | + .copilot-container .copilot { |
| 164 | + height: 600px; |
| 165 | + border-left: 1px solid var(--border-color-primary); |
| 166 | + } |
| 167 | + .copilot-container .content-body { |
| 168 | + height: auto; |
| 169 | + max-height: 400px; |
| 170 | + } |
| 171 | +} |
| 172 | +""" |
| 173 | + |
| 174 | +with gr.Blocks(css=css) as demo, ms.Application() as app, antdx.XProvider(): |
| 175 | + with antd.Row(elem_classes="copilot-container", wrap=True): |
| 176 | + # Content column |
| 177 | + with antd.Col(md=16, xs=24, |
| 178 | + elem_style=dict(height="100%")) as content_col: |
| 179 | + with ms.AutoLoading(elem_style=dict(height="100%")): |
| 180 | + with antd.Card(elem_style=dict(height="100%", |
| 181 | + borderRadius=0, |
| 182 | + display="flex", |
| 183 | + flexDirection="column"), |
| 184 | + class_names=dict(body="content-body")): |
| 185 | + # Title |
| 186 | + with ms.Slot("title"): |
| 187 | + with antd.Typography.Title(level=1, |
| 188 | + elem_style=dict( |
| 189 | + margin=0, |
| 190 | + textAlign="center", |
| 191 | + fontSize=30)): |
| 192 | + ms.Text("🤖 Copilot Template") |
| 193 | + |
| 194 | + # Copilot button |
| 195 | + with ms.Slot("extra"): |
| 196 | + copilot_open_btn = antd.Button( |
| 197 | + "✨ AI Copilot", |
| 198 | + shape="round", |
| 199 | + variant='filled', |
| 200 | + color="primary", |
| 201 | + elem_style=dict(display="none")) |
| 202 | + |
| 203 | + # Content |
| 204 | + ms.Markdown(""" |
| 205 | +<img src="https://mdn.alipayobjects.com/huamei_iwk9zp/afts/img/A*48RLR41kwHIAAAAAAAAAAAAADgCCAQ/fmt.webp" style="width: 100%;" /> |
| 206 | +<h4>What is the RICH design paradigm?</h4> |
| 207 | +<div> |
| 208 | +RICH is an AI interface design paradigm we propose, similar to how the WIMP paradigm |
| 209 | +relates to graphical user interfaces. |
| 210 | +</div> |
| 211 | +<br /> |
| 212 | +<div> |
| 213 | +The ACM SIGCHI 2005 (the premier conference on human-computer interaction) defined |
| 214 | +that the core issues of human-computer interaction can be divided into three levels: |
| 215 | +</div> |
| 216 | +<ul> |
| 217 | +<li> |
| 218 | + Interface Paradigm Layer: Defines the design elements of human-computer |
| 219 | + interaction interfaces, guiding designers to focus on core issues. |
| 220 | +</li> |
| 221 | +<li> |
| 222 | + User model layer: Build an interface experience evaluation model to measure the |
| 223 | + quality of the interface experience. |
| 224 | +</li> |
| 225 | +<li> |
| 226 | + Software framework layer: The underlying support algorithms and data structures |
| 227 | + for human-computer interfaces, which are the contents hidden behind the front-end |
| 228 | + interface. |
| 229 | +</li> |
| 230 | +</ul> |
| 231 | +<div> |
| 232 | +The interface paradigm is the aspect that designers need to focus on and define the |
| 233 | +most when a new human-computer interaction technology is born. The interface |
| 234 | +paradigm defines the design elements that designers should pay attention to, and |
| 235 | +based on this, it is possible to determine what constitutes good design and how to |
| 236 | +achieve it. |
| 237 | +</div> |
| 238 | +""") |
| 239 | + |
| 240 | + # Copilot column |
| 241 | + with antd.Col(md=8, xs=24, |
| 242 | + elem_style=dict(height="100%")) as copilot_col: |
| 243 | + with ms.AutoLoading(elem_style=dict(height="100%")): |
| 244 | + with antd.Flex( |
| 245 | + vertical=True, |
| 246 | + gap="small", |
| 247 | + elem_classes="copilot", |
| 248 | + ): |
| 249 | + with antd.Flex(justify="space-between", align="center"): |
| 250 | + antd.Typography.Title("✨ AI Copilot", |
| 251 | + level=4, |
| 252 | + elem_style=dict(margin=0)) |
| 253 | + with antd.Flex(align="center", gap="small"): |
| 254 | + with antd.Button( |
| 255 | + variant="text", |
| 256 | + color="default") as copilot_close_btn: |
| 257 | + with ms.Slot("icon"): |
| 258 | + antd.Icon("CloseOutlined") |
| 259 | + antd.Divider(size="small") |
| 260 | + chatbot = pro.Chatbot( |
| 261 | + # for flex=1 to fill the remaining space |
| 262 | + height=0, |
| 263 | + elem_style=dict(flex=1), |
| 264 | + welcome_config=ChatbotWelcomeConfig( |
| 265 | + variant="filled", |
| 266 | + title="👋🏻 Hello, I'm AI Copilot", |
| 267 | + description="Enter a prompt to get started", |
| 268 | + prompts=ChatbotPromptsConfig( |
| 269 | + title="I can help: ", |
| 270 | + vertical=True, |
| 271 | + items=[{ |
| 272 | + "description": |
| 273 | + "Help me with a plan to start a business" |
| 274 | + }, { |
| 275 | + "description": |
| 276 | + "Help me with a plan to achieve my goals" |
| 277 | + }, { |
| 278 | + "description": |
| 279 | + "Help me with a plan for a successful interview" |
| 280 | + }])), |
| 281 | + user_config=dict( |
| 282 | + avatar= |
| 283 | + "https://api.dicebear.com/7.x/miniavs/svg?seed=3"), |
| 284 | + bot_config=ChatbotBotConfig( |
| 285 | + header="Copilot", |
| 286 | + actions=["copy", "retry"], |
| 287 | + avatar= |
| 288 | + "https://api.dicebear.com/7.x/miniavs/svg?seed=2"), |
| 289 | + ) |
| 290 | + |
| 291 | + with pro.MultimodalInput( |
| 292 | + upload_config=MultimodalInputUploadConfig( |
| 293 | + allow_upload=False)) as input: |
| 294 | + with ms.Slot("prefix"): |
| 295 | + with antd.Button(value=None, |
| 296 | + color="default", |
| 297 | + variant="text") as clear_btn: |
| 298 | + with ms.Slot("icon"): |
| 299 | + antd.Icon("ClearOutlined") |
| 300 | + clear_btn.click(fn=clear, outputs=[chatbot]) |
| 301 | + submit_event = input.submit(fn=submit, |
| 302 | + inputs=[input, chatbot], |
| 303 | + outputs=[input, chatbot, clear_btn]) |
| 304 | + input.cancel(fn=cancel, |
| 305 | + inputs=[chatbot], |
| 306 | + outputs=[chatbot, input, clear_btn], |
| 307 | + cancels=[submit_event], |
| 308 | + queue=False) |
| 309 | + chatbot.retry(fn=retry, |
| 310 | + inputs=[chatbot], |
| 311 | + outputs=[input, chatbot, clear_btn]) |
| 312 | + chatbot.welcome_prompt_select(fn=prompt_select, |
| 313 | + inputs=[input], |
| 314 | + outputs=[input]) |
| 315 | + copilot_open_btn.click( |
| 316 | + fn=open_copilot, |
| 317 | + outputs=[content_col, copilot_col, copilot_open_btn]) |
| 318 | + copilot_close_btn.click( |
| 319 | + fn=close_copilot, |
| 320 | + outputs=[content_col, copilot_col, copilot_open_btn]) |
| 321 | + gr.on([app.mount, app.resize], |
| 322 | + fn=resize_window, |
| 323 | + outputs=[copilot_open_btn, copilot_close_btn]) |
| 324 | +if __name__ == "__main__": |
| 325 | + demo.queue().launch() |
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