ratyim commited on
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c73413c
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1 Parent(s): 93807bd

Update app.py

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Files changed (1) hide show
  1. app.py +82 -112
app.py CHANGED
@@ -1,5 +1,6 @@
1
  #!/usr/bin/env python
2
  # encoding: utf-8
 
3
  import spaces
4
  import gradio as gr
5
  from PIL import Image
@@ -10,37 +11,39 @@ import argparse
10
  from transformers import AutoModel, AutoTokenizer
11
 
12
  # README, How to run demo on different devices
 
 
13
 
14
- # For Nvidia GPUs.
15
- # python web_demo_2.5.py --device cuda
16
 
17
  # For Mac with MPS (Apple silicon or AMD GPUs).
18
- # PYTORCH_ENABLE_MPS_FALLBACK=1 python web_demo_2.5.py --device mps
19
 
20
  # Argparser
21
  parser = argparse.ArgumentParser(description='demo')
22
  parser.add_argument('--device', type=str, default='cuda', help='cuda or mps')
 
23
  args = parser.parse_args()
24
  device = args.device
25
  assert device in ['cuda', 'mps']
 
 
 
 
26
 
27
  # Load model
28
- model_path = 'openbmb/MiniCPM-Llama3-V-2_5'
29
- if 'int4' in model_path:
30
- if device == 'mps':
31
- print('Error: running int4 model with bitsandbytes on Mac is not supported right now.')
32
- exit()
33
- model = AutoModel.from_pretrained(model_path, trust_remote_code=True)
34
- else:
35
- model = AutoModel.from_pretrained(model_path, trust_remote_code=True).to(dtype=torch.float16)
36
- model = model.to(device=device)
37
  tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
 
 
38
  model.eval()
39
 
40
 
41
 
42
  ERROR_MSG = "Error, please retry"
43
- model_name = 'MiniCPM-Llama3-V 2.5'
44
 
45
  form_radio = {
46
  'choices': ['Beam Search', 'Sampling'],
@@ -134,33 +137,30 @@ def create_component(params, comp='Slider'):
134
 
135
  @spaces.GPU(duration=120)
136
  def chat(img, msgs, ctx, params=None, vision_hidden_states=None):
137
- default_params = {"stream": False, "sampling": False, "num_beams":3, "repetition_penalty": 1.2, "max_new_tokens": 1024}
138
  if params is None:
139
  params = default_params
140
  if img is None:
141
- yield "Error, invalid image, please upload a new image"
142
- else:
143
- try:
144
- image = img.convert('RGB')
145
- answer = model.chat(
146
- image=image,
147
- msgs=msgs,
148
- tokenizer=tokenizer,
149
- **params
150
- )
151
- # if params['stream'] is False:
152
- # res = re.sub(r'(<box>.*</box>)', '', answer)
153
- # res = res.replace('<ref>', '')
154
- # res = res.replace('</ref>', '')
155
- # res = res.replace('<box>', '')
156
- # answer = res.replace('</box>', '')
157
- # else:
158
- for char in answer:
159
- yield char
160
- except Exception as err:
161
- print(err)
162
- traceback.print_exc()
163
- yield ERROR_MSG
164
 
165
 
166
  def upload_img(image, _chatbot, _app_session):
@@ -173,51 +173,46 @@ def upload_img(image, _chatbot, _app_session):
173
  return _chatbot, _app_session
174
 
175
 
176
- def respond(_chat_bot, _app_cfg, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature):
177
- _question = _chat_bot[-1][0]
178
- print('<Question>:', _question)
179
  if _app_cfg.get('ctx', None) is None:
180
- _chat_bot[-1][1] = 'Please upload an image to start'
181
- yield (_chat_bot, _app_cfg)
 
 
 
 
182
  else:
183
- _context = _app_cfg['ctx'].copy()
184
- if _context:
185
- _context.append({"role": "user", "content": _question})
186
- else:
187
- _context = [{"role": "user", "content": _question}]
188
- if params_form == 'Beam Search':
189
- params = {
190
- 'sampling': False,
191
- 'stream': False,
192
- 'num_beams': num_beams,
193
- 'repetition_penalty': repetition_penalty,
194
- "max_new_tokens": 896
195
- }
196
- else:
197
- params = {
198
- 'sampling': True,
199
- 'stream': True,
200
- 'top_p': top_p,
201
- 'top_k': top_k,
202
- 'temperature': temperature,
203
- 'repetition_penalty': repetition_penalty_2,
204
- "max_new_tokens": 896
205
- }
206
-
207
- gen = chat(_app_cfg['img'], _context, None, params)
208
- _chat_bot[-1][1] = ""
209
- for _char in gen:
210
- _chat_bot[-1][1] += _char
211
- _context[-1]["content"] += _char
212
- yield (_chat_bot, _app_cfg)
213
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
214
 
215
- def request(_question, _chat_bot, _app_cfg):
216
- _chat_bot.append((_question, None))
 
 
 
217
  return '', _chat_bot, _app_cfg
218
 
219
 
220
- def regenerate_button_clicked(_question, _chat_bot, _app_cfg):
221
  if len(_chat_bot) <= 1:
222
  _chat_bot.append(('Regenerate', 'No question for regeneration.'))
223
  return '', _chat_bot, _app_cfg
@@ -227,18 +222,9 @@ def regenerate_button_clicked(_question, _chat_bot, _app_cfg):
227
  _question = _chat_bot[-1][0]
228
  _chat_bot = _chat_bot[:-1]
229
  _app_cfg['ctx'] = _app_cfg['ctx'][:-2]
230
- return request(_question, _chat_bot, _app_cfg)
231
- # return respond(_chat_bot, _app_cfg, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature)
232
 
233
 
234
- def clear_button_clicked(_question, _chat_bot, _app_cfg, _bt_pic):
235
- _chat_bot.clear()
236
- _app_cfg['sts'] = None
237
- _app_cfg['ctx'] = None
238
- _app_cfg['img'] = None
239
- _bt_pic = None
240
- return '', _chat_bot, _app_cfg, _bt_pic
241
-
242
 
243
  with gr.Blocks() as demo:
244
  with gr.Row():
@@ -253,43 +239,27 @@ with gr.Blocks() as demo:
253
  temperature = create_component(temperature_slider)
254
  repetition_penalty_2 = create_component(repetition_penalty_slider2)
255
  regenerate = create_component({'value': 'Regenerate'}, comp='Button')
256
- clear = create_component({'value': 'Clear'}, comp='Button')
257
  with gr.Column(scale=3, min_width=500):
258
  app_session = gr.State({'sts':None,'ctx':None,'img':None})
259
  bt_pic = gr.Image(label="Upload an image to start")
260
  chat_bot = gr.Chatbot(label=f"Chat with {model_name}")
261
  txt_message = gr.Textbox(label="Input text")
262
 
263
- clear.click(
264
- clear_button_clicked,
265
- [txt_message, chat_bot, app_session, bt_pic],
266
- [txt_message, chat_bot, app_session, bt_pic],
267
- queue=False
268
- )
269
- txt_message.submit(
270
- request,
271
- #[txt_message, chat_bot, app_session, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature],
272
- [txt_message, chat_bot, app_session],
273
- [txt_message, chat_bot, app_session],
274
- queue=False
275
- ).then(
276
- respond,
277
- [chat_bot, app_session, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature],
278
- [chat_bot, app_session]
279
- )
280
  regenerate.click(
281
  regenerate_button_clicked,
282
- [txt_message, chat_bot, app_session],
283
- [txt_message, chat_bot, app_session],
284
- queue=False
285
- ).then(
286
- respond,
287
- [chat_bot, app_session, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature],
288
- [chat_bot, app_session]
289
  )
290
  bt_pic.upload(lambda: None, None, chat_bot, queue=False).then(upload_img, inputs=[bt_pic,chat_bot,app_session], outputs=[chat_bot,app_session])
291
 
292
  # launch
293
  #demo.launch(share=False, debug=True, show_api=False, server_port=8080, server_name="0.0.0.0")
294
- demo.queue()
295
- demo.launch()
 
 
 
1
  #!/usr/bin/env python
2
  # encoding: utf-8
3
+ import timm
4
  import spaces
5
  import gradio as gr
6
  from PIL import Image
 
11
  from transformers import AutoModel, AutoTokenizer
12
 
13
  # README, How to run demo on different devices
14
+ # For Nvidia GPUs support BF16 (like A100, H100, RTX3090)
15
+ # python web_demo.py --device cuda --dtype bf16
16
 
17
+ # For Nvidia GPUs do NOT support BF16 (like V100, T4, RTX2080)
18
+ # python web_demo.py --device cuda --dtype fp16
19
 
20
  # For Mac with MPS (Apple silicon or AMD GPUs).
21
+ # PYTORCH_ENABLE_MPS_FALLBACK=1 python web_demo.py --device mps --dtype fp16
22
 
23
  # Argparser
24
  parser = argparse.ArgumentParser(description='demo')
25
  parser.add_argument('--device', type=str, default='cuda', help='cuda or mps')
26
+ parser.add_argument('--dtype', type=str, default='bf16', help='bf16 or fp16')
27
  args = parser.parse_args()
28
  device = args.device
29
  assert device in ['cuda', 'mps']
30
+ if args.dtype == 'bf16':
31
+ dtype = torch.bfloat16
32
+ else:
33
+ dtype = torch.float16
34
 
35
  # Load model
36
+ model_path = 'openbmb/MiniCPM-V-2'
37
+ model = AutoModel.from_pretrained(model_path, trust_remote_code=True).to(dtype=torch.bfloat16)
 
 
 
 
 
 
 
38
  tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
39
+
40
+ model = model.to(device=device, dtype=dtype)
41
  model.eval()
42
 
43
 
44
 
45
  ERROR_MSG = "Error, please retry"
46
+ model_name = 'MiniCPM-V 2.0'
47
 
48
  form_radio = {
49
  'choices': ['Beam Search', 'Sampling'],
 
137
 
138
  @spaces.GPU(duration=120)
139
  def chat(img, msgs, ctx, params=None, vision_hidden_states=None):
140
+ default_params = {"num_beams":3, "repetition_penalty": 1.2, "max_new_tokens": 1024}
141
  if params is None:
142
  params = default_params
143
  if img is None:
144
+ return -1, "Error, invalid image, please upload a new image", None, None
145
+ try:
146
+ image = img.convert('RGB')
147
+ answer, context, _ = model.chat(
148
+ image=image,
149
+ msgs=msgs,
150
+ context=None,
151
+ tokenizer=tokenizer,
152
+ **params
153
+ )
154
+ res = re.sub(r'(<box>.*</box>)', '', answer)
155
+ res = res.replace('<ref>', '')
156
+ res = res.replace('</ref>', '')
157
+ res = res.replace('<box>', '')
158
+ answer = res.replace('</box>', '')
159
+ return -1, answer, None, None
160
+ except Exception as err:
161
+ print(err)
162
+ traceback.print_exc()
163
+ return -1, ERROR_MSG, None, None
 
 
 
164
 
165
 
166
  def upload_img(image, _chatbot, _app_session):
 
173
  return _chatbot, _app_session
174
 
175
 
176
+ def respond(_question, _chat_bot, _app_cfg, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature):
 
 
177
  if _app_cfg.get('ctx', None) is None:
178
+ _chat_bot.append((_question, 'Please upload an image to start'))
179
+ return '', _chat_bot, _app_cfg
180
+
181
+ _context = _app_cfg['ctx'].copy()
182
+ if _context:
183
+ _context.append({"role": "user", "content": _question})
184
  else:
185
+ _context = [{"role": "user", "content": _question}]
186
+ print('<User>:', _question)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
187
 
188
+ if params_form == 'Beam Search':
189
+ params = {
190
+ 'sampling': False,
191
+ 'num_beams': num_beams,
192
+ 'repetition_penalty': repetition_penalty,
193
+ "max_new_tokens": 896
194
+ }
195
+ else:
196
+ params = {
197
+ 'sampling': True,
198
+ 'top_p': top_p,
199
+ 'top_k': top_k,
200
+ 'temperature': temperature,
201
+ 'repetition_penalty': repetition_penalty_2,
202
+ "max_new_tokens": 896
203
+ }
204
+ code, _answer, _, sts = chat(_app_cfg['img'], _context, None, params)
205
+ print('<Assistant>:', _answer)
206
 
207
+ _context.append({"role": "assistant", "content": _answer})
208
+ _chat_bot.append((_question, _answer))
209
+ if code == 0:
210
+ _app_cfg['ctx']=_context
211
+ _app_cfg['sts']=sts
212
  return '', _chat_bot, _app_cfg
213
 
214
 
215
+ def regenerate_button_clicked(_question, _chat_bot, _app_cfg, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature):
216
  if len(_chat_bot) <= 1:
217
  _chat_bot.append(('Regenerate', 'No question for regeneration.'))
218
  return '', _chat_bot, _app_cfg
 
222
  _question = _chat_bot[-1][0]
223
  _chat_bot = _chat_bot[:-1]
224
  _app_cfg['ctx'] = _app_cfg['ctx'][:-2]
225
+ return respond(_question, _chat_bot, _app_cfg, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature)
 
226
 
227
 
 
 
 
 
 
 
 
 
228
 
229
  with gr.Blocks() as demo:
230
  with gr.Row():
 
239
  temperature = create_component(temperature_slider)
240
  repetition_penalty_2 = create_component(repetition_penalty_slider2)
241
  regenerate = create_component({'value': 'Regenerate'}, comp='Button')
 
242
  with gr.Column(scale=3, min_width=500):
243
  app_session = gr.State({'sts':None,'ctx':None,'img':None})
244
  bt_pic = gr.Image(label="Upload an image to start")
245
  chat_bot = gr.Chatbot(label=f"Chat with {model_name}")
246
  txt_message = gr.Textbox(label="Input text")
247
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
248
  regenerate.click(
249
  regenerate_button_clicked,
250
+ [txt_message, chat_bot, app_session, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature],
251
+ [txt_message, chat_bot, app_session]
252
+ )
253
+ txt_message.submit(
254
+ respond,
255
+ [txt_message, chat_bot, app_session, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature],
256
+ [txt_message, chat_bot, app_session]
257
  )
258
  bt_pic.upload(lambda: None, None, chat_bot, queue=False).then(upload_img, inputs=[bt_pic,chat_bot,app_session], outputs=[chat_bot,app_session])
259
 
260
  # launch
261
  #demo.launch(share=False, debug=True, show_api=False, server_port=8080, server_name="0.0.0.0")
262
+ demo.launch()
263
+
264
+
265
+