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1 Parent(s): cfef15a

Update app.py

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Files changed (1) hide show
  1. app.py +57 -154
app.py CHANGED
@@ -10,229 +10,132 @@ from transformers import AutoModel, AutoTokenizer
10
 
11
  # Argparser
12
  parser = argparse.ArgumentParser(description='demo')
13
- parser.add_argument('--device', type=str, default='cuda', help='cuda or mps')
 
14
  args = parser.parse_args()
15
  device = args.device
16
- assert device in ['cuda', 'mps']
 
 
 
 
 
 
17
 
18
  # Load model
19
  model_path = 'openbmb/MiniCPM-V-2'
20
- if 'int4' in model_path:
21
- if device == 'mps':
22
- print('Error: running int4 model with bitsandbytes on Mac is not supported right now.')
23
- exit()
24
- model = AutoModel.from_pretrained(model_path, trust_remote_code=True)
25
- else:
26
- model = AutoModel.from_pretrained(model_path, trust_remote_code=True, torch_dtype=torch.float16, device_map=device)
27
  tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
28
- model.eval()
29
-
30
 
 
 
31
 
32
  ERROR_MSG = "Error, please retry"
33
- model_name = 'MiniCPM-V 2'
34
 
 
35
  form_radio = {
36
  'choices': ['Beam Search', 'Sampling'],
37
- #'value': 'Beam Search',
38
  'value': 'Sampling',
39
  'interactive': True,
40
  'label': 'Decode Type'
41
  }
42
- # Beam Form
43
- num_beams_slider = {
44
- 'minimum': 0,
45
- 'maximum': 5,
46
- 'value': 3,
47
- 'step': 1,
48
- 'interactive': True,
49
- 'label': 'Num Beams'
50
- }
51
- repetition_penalty_slider = {
52
- 'minimum': 0,
53
- 'maximum': 3,
54
- 'value': 1.2,
55
- 'step': 0.01,
56
- 'interactive': True,
57
- 'label': 'Repetition Penalty'
58
- }
59
- repetition_penalty_slider2 = {
60
- 'minimum': 0,
61
- 'maximum': 3,
62
- 'value': 1.05,
63
- 'step': 0.01,
64
- 'interactive': True,
65
- 'label': 'Repetition Penalty'
66
- }
67
- max_new_tokens_slider = {
68
- 'minimum': 1,
69
- 'maximum': 4096,
70
- 'value': 1024,
71
- 'step': 1,
72
- 'interactive': True,
73
- 'label': 'Max New Tokens'
74
- }
75
-
76
- top_p_slider = {
77
- 'minimum': 0,
78
- 'maximum': 1,
79
- 'value': 0.8,
80
- 'step': 0.05,
81
- 'interactive': True,
82
- 'label': 'Top P'
83
- }
84
- top_k_slider = {
85
- 'minimum': 0,
86
- 'maximum': 200,
87
- 'value': 100,
88
- 'step': 1,
89
- 'interactive': True,
90
- 'label': 'Top K'
91
- }
92
- temperature_slider = {
93
- 'minimum': 0,
94
- 'maximum': 2,
95
- 'value': 0.7,
96
- 'step': 0.05,
97
- 'interactive': True,
98
- 'label': 'Temperature'
99
- }
100
 
 
 
 
 
 
 
 
 
101
 
102
  def create_component(params, comp='Slider'):
103
  if comp == 'Slider':
104
- return gr.Slider(
105
- minimum=params['minimum'],
106
- maximum=params['maximum'],
107
- value=params['value'],
108
- step=params['step'],
109
- interactive=params['interactive'],
110
- label=params['label']
111
- )
112
  elif comp == 'Radio':
113
- return gr.Radio(
114
- choices=params['choices'],
115
- value=params['value'],
116
- interactive=params['interactive'],
117
- label=params['label']
118
- )
119
  elif comp == 'Button':
120
- return gr.Button(
121
- value=params['value'],
122
- interactive=True
123
- )
124
 
125
-
126
- def chat(img, msgs, ctx, params=None, vision_hidden_states=None):
127
- default_params = {"num_beams":3, "repetition_penalty": 1.2, "max_new_tokens": 1024}
128
  if params is None:
129
  params = default_params
130
  if img is None:
131
  return -1, "Error, invalid image, please upload a new image", None, None
132
  try:
133
  image = img.convert('RGB')
134
- answer = model.chat(
135
- image=image,
136
- msgs=msgs,
137
- tokenizer=tokenizer,
138
- **params
139
- )
140
- res = re.sub(r'(<box>.*</box>)', '', answer)
141
- res = res.replace('<ref>', '')
142
- res = res.replace('</ref>', '')
143
- res = res.replace('<box>', '')
144
- answer = res.replace('</box>', '')
145
- return 0, answer, None, None
146
  except Exception as err:
147
  print(err)
148
  traceback.print_exc()
149
  return -1, ERROR_MSG, None, None
150
 
151
-
152
  def upload_img(image, _chatbot, _app_session):
153
  image = Image.fromarray(image)
154
-
155
- _app_session['sts']=None
156
- _app_session['ctx']=[]
157
- _app_session['img']=image
158
  _chatbot.append(('', 'Image uploaded successfully, you can talk to me now'))
159
  return _chatbot, _app_session
160
 
161
-
162
  def respond(_question, _chat_bot, _app_cfg, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature):
163
  if _app_cfg.get('ctx', None) is None:
164
  _chat_bot.append((_question, 'Please upload an image to start'))
165
  return '', _chat_bot, _app_cfg
166
 
167
  _context = _app_cfg['ctx'].copy()
168
- if _context:
169
- _context.append({"role": "user", "content": _question})
170
- else:
171
- _context = [{"role": "user", "content": _question}]
172
- print('<User>:', _question)
173
 
174
  if params_form == 'Beam Search':
175
- params = {
176
- 'sampling': False,
177
- 'num_beams': num_beams,
178
- 'repetition_penalty': repetition_penalty,
179
- "max_new_tokens": 896
180
- }
181
- else:
182
  params = {
183
  'sampling': True,
184
  'top_p': top_p,
185
  'top_k': top_k,
186
  'temperature': temperature,
187
  'repetition_penalty': repetition_penalty_2,
188
- "max_new_tokens": 896
189
  }
 
190
  code, _answer, _, sts = chat(_app_cfg['img'], _context, None, params)
191
- print('<Assistant>:', _answer)
192
-
193
  _context.append({"role": "assistant", "content": _answer})
194
  _chat_bot.append((_question, _answer))
195
  if code == 0:
196
- _app_cfg['ctx']=_context
197
- _app_cfg['sts']=sts
198
  return '', _chat_bot, _app_cfg
199
 
200
-
201
- def regenerate_button_clicked(_question, _chat_bot, _app_cfg, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature):
202
- if len(_chat_bot) <= 1:
203
- _chat_bot.append(('Regenerate', 'No question for regeneration.'))
204
- return '', _chat_bot, _app_cfg
205
- elif _chat_bot[-1][0] == 'Regenerate':
206
- return '', _chat_bot, _app_cfg
207
- else:
208
- _question = _chat_bot[-1][0]
209
- _chat_bot = _chat_bot[:-1]
210
- _app_cfg['ctx'] = _app_cfg['ctx'][:-2]
211
- return respond(_question, _chat_bot, _app_cfg, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature)
212
-
213
-
214
 
215
  with gr.Blocks() as demo:
 
 
216
  with gr.Row():
217
  with gr.Column(scale=2, min_width=300):
218
- app_session = gr.State({'sts':None,'ctx':None,'img':None})
219
  bt_pic = gr.Image(label="Upload an image to start")
220
- txt_message = gr.Textbox(label="Input text")
 
221
  with gr.Column(scale=2, min_width=300):
222
- chat_bot = gr.Chatbot(label=f"Chat with {model_name}")
223
-
224
- regenerate.click(
225
- regenerate_button_clicked,
226
- [txt_message, chat_bot, app_session, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature],
227
- [txt_message, chat_bot, app_session]
228
- )
229
  txt_message.submit(
230
  respond,
231
- [txt_message, chat_bot, app_session, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature],
232
  [txt_message, chat_bot, app_session]
233
  )
234
- 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])
235
 
236
- # launch
237
- demo.launch(share=False, debug=True, show_api=False, server_port=8080, server_name="0.0.0.0")
238
 
 
 
 
10
 
11
  # Argparser
12
  parser = argparse.ArgumentParser(description='demo')
13
+ parser.add_argument('--device', type=str, default='cpu', help='cpu')
14
+ parser.add_argument('--dtype', type=str, default='fp32', help='fp32')
15
  args = parser.parse_args()
16
  device = args.device
17
+ assert device in ['cpu']
18
+
19
+ # Set dtype
20
+ if args.dtype == 'fp32':
21
+ dtype = torch.float32
22
+ else:
23
+ dtype = torch.float16
24
 
25
  # Load model
26
  model_path = 'openbmb/MiniCPM-V-2'
27
+ model = AutoModel.from_pretrained(model_path, trust_remote_code=True).to(dtype=dtype)
 
 
 
 
 
 
28
  tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
 
 
29
 
30
+ model = model.to(device=device)
31
+ model.eval()
32
 
33
  ERROR_MSG = "Error, please retry"
34
+ model_name = 'MiniCPM-V 2.0'
35
 
36
+ # UI Components
37
  form_radio = {
38
  'choices': ['Beam Search', 'Sampling'],
 
39
  'value': 'Sampling',
40
  'interactive': True,
41
  'label': 'Decode Type'
42
  }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
43
 
44
+ # Sliders and their settings
45
+ num_beams_slider = {'minimum': 0, 'maximum': 5, 'value': 3, 'step': 1, 'interactive': True, 'label': 'Num Beams'}
46
+ repetition_penalty_slider = {'minimum': 0, 'maximum': 3, 'value': 1.2, 'step': 0.01, 'interactive': True, 'label': 'Repetition Penalty'}
47
+ repetition_penalty_slider2 = {'minimum': 0, 'maximum': 3, 'value': 1.05, 'step': 0.01, 'interactive': True, 'label': 'Repetition Penalty'}
48
+ max_new_tokens_slider = {'minimum': 1, 'maximum': 4096, 'value': 1024, 'step': 1, 'interactive': True, 'label': 'Max New Tokens'}
49
+ top_p_slider = {'minimum': 0, 'maximum': 1, 'value': 0.8, 'step': 0.05, 'interactive': True, 'label': 'Top P'}
50
+ top_k_slider = {'minimum': 0, 'maximum': 200, 'value': 100, 'step': 1, 'interactive': True, 'label': 'Top K'}
51
+ temperature_slider = {'minimum': 0, 'maximum': 2, 'value': 0.7, 'step': 0.05, 'interactive': True, 'label': 'Temperature'}
52
 
53
  def create_component(params, comp='Slider'):
54
  if comp == 'Slider':
55
+ return gr.Slider(**params)
 
 
 
 
 
 
 
56
  elif comp == 'Radio':
57
+ return gr.Radio(choices=params['choices'], value=params['value'], interactive=params['interactive'], label=params['label'])
 
 
 
 
 
58
  elif comp == 'Button':
59
+ return gr.Button(value=params['value'], interactive=True)
 
 
 
60
 
61
+ def chat(img, msgs, ctx, params=None):
62
+ default_params = {"num_beams": 3, "repetition_penalty": 1.2, "max_new_tokens": 1024}
 
63
  if params is None:
64
  params = default_params
65
  if img is None:
66
  return -1, "Error, invalid image, please upload a new image", None, None
67
  try:
68
  image = img.convert('RGB')
69
+ answer, context, _ = model.chat(image=image, msgs=msgs, context=None, tokenizer=tokenizer, **params)
70
+ res = re.sub(r'(<box>.*</box>)', '', answer).replace('<ref>', '').replace('</ref>', '').replace('<box>', '').replace('</box>', '')
71
+ return 0, res, None, None
 
 
 
 
 
 
 
 
 
72
  except Exception as err:
73
  print(err)
74
  traceback.print_exc()
75
  return -1, ERROR_MSG, None, None
76
 
 
77
  def upload_img(image, _chatbot, _app_session):
78
  image = Image.fromarray(image)
79
+ _app_session['sts'] = None
80
+ _app_session['ctx'] = []
81
+ _app_session['img'] = image
 
82
  _chatbot.append(('', 'Image uploaded successfully, you can talk to me now'))
83
  return _chatbot, _app_session
84
 
 
85
  def respond(_question, _chat_bot, _app_cfg, params_form, num_beams, repetition_penalty, repetition_penalty_2, top_p, top_k, temperature):
86
  if _app_cfg.get('ctx', None) is None:
87
  _chat_bot.append((_question, 'Please upload an image to start'))
88
  return '', _chat_bot, _app_cfg
89
 
90
  _context = _app_cfg['ctx'].copy()
91
+ _context.append({"role": "user", "content": _question})
 
 
 
 
92
 
93
  if params_form == 'Beam Search':
94
+ params = {'sampling': False, 'num_beams': num_beams, 'repetition_penalty': repetition_penalty, "max_new_tokens": 896}
95
+ else: # Ensure this block is executed for Sampling
 
 
 
 
 
96
  params = {
97
  'sampling': True,
98
  'top_p': top_p,
99
  'top_k': top_k,
100
  'temperature': temperature,
101
  'repetition_penalty': repetition_penalty_2,
102
+ "max_new_tokens": 896
103
  }
104
+
105
  code, _answer, _, sts = chat(_app_cfg['img'], _context, None, params)
106
+
 
107
  _context.append({"role": "assistant", "content": _answer})
108
  _chat_bot.append((_question, _answer))
109
  if code == 0:
110
+ _app_cfg['ctx'] = _context
111
+ _app_cfg['sts'] = sts
112
  return '', _chat_bot, _app_cfg
113
 
114
+ def clear(chat_bot, app_session):
115
+ app_session['img'] = None
116
+ chat_bot.clear()
117
+ return chat_bot
 
 
 
 
 
 
 
 
 
 
118
 
119
  with gr.Blocks() as demo:
120
+ gr.Markdown("<h1 style='text-align: center;'>Medical Assistant</h1>")
121
+
122
  with gr.Row():
123
  with gr.Column(scale=2, min_width=300):
124
+ app_session = gr.State({'sts': None, 'ctx': None, 'img': None})
125
  bt_pic = gr.Image(label="Upload an image to start")
126
+ txt_message = gr.Textbox(label="Ask your question...")
127
+
128
  with gr.Column(scale=2, min_width=300):
129
+ chat_bot = gr.Chatbot(label=f"Chatbot")
130
+ clear_button = gr.Button(value='Clear')
 
 
 
 
 
131
  txt_message.submit(
132
  respond,
133
+ [txt_message, chat_bot, app_session],
134
  [txt_message, chat_bot, app_session]
135
  )
 
136
 
137
+ 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])
138
+ clear_button.click(clear, [chat_bot, app_session], chat_bot)
139
 
140
+ # Launch
141
+ demo.launch(share=True, debug=True, show_api=False)