File size: 7,394 Bytes
72bf0de
 
 
8400d16
 
 
72bf0de
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8400d16
 
 
 
 
72bf0de
8400d16
72bf0de
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8400d16
72bf0de
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
import os 
from typing import Iterator
from text_generation import Client
import gradio as gr

model_id = 'HuggingFaceH4/zephyr-7b-beta'

API_URL = "https://api-inference.huggingface.co/models/" + model_id 
HF_TOKEN = os.environ.get('HF_READ_TOKEN', None)

client = Client(
    API_URL,
    headers={'Authorization'L f"Bearer {HF_TOKEN"}
)
EOS_STRING = "</s>"
EOT_STRING = "<EOT>"

def get_prompt(message, chat_history, system_prompt):
    texts = [f"<s>[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n"]

    do_strip = False
    for user_input, response in chat_history:
        user_input = user_input.strip() if do_strip else user_input
        do_strip = True
        texts.append(f"{user_input} [/INST] {response.strip()} </s><s>[INST] ")
    message = message.strip() if do_strip else message
    texts.append(f"{message} [/INST]")
    return ''.join(texts)

def run(message, chat_history, system_prompt, max_new_tokens=1024, temperature=0.1, top_p=0.9, top_k=50):
    prompt = get_prompt(message, chat_history, system_prompt)

    generate_kwargs = dict(
        max_new_tokens=max_new_tokens,
        do_sample=True,
        top_p=top_p,
        top_k=top_k,
        temperature=temperature
    )
    stream = client.generate_stream(prompt, **generate_kwargs)
    output = ''
    for response in stream:
        if any([end_token in response.token_text for end_token in [EOS_STRING, EOT_STRING]]):
            return output
        else:
            output += response.token.text
        yield output
    return output


DEFAULT_SYSTEM_PROMPT = """
    You are Zephyr. You are an AI assistant, you are moderately-polite and give only true information.
    You carefully provide accurate, factual, thoughtful, nuanced answers, and are brilliant at reasoning. 
    If you think there might not be a correct answer, you say so. Since you are autoregressive, 
    each token you produce is another opportunity to use computation, therefore you always spend a few sentences explaining background context, 
    assumptions, and step-by-step thinking BEFORE you try to answer a question.
"""
MAX_MAX_NEW_TOKENS = 4096
DEFAULT_MAX_NEW_TOKENS = 1024
MAX_INPUT_TOKEN_LENGTH = 4096

DESCRIPTION = """
    # Zephyr-7b ChatBot
"""

def clear_and_save_textbox(message): return '', message
    
def display_input(message, history=[]):
    history.append((message, ''))
    return history

def delete_prev_fn(history=[]):
    try:
        message, _ = history.pop()
    except IndexError:
        message = ''
    return history, message or ''

def generate(message, history_with_input, system_prompt, max_new_tokens, temperature, top_p, top_k):
    if max_new_tokens > MAX_MAX_NEW_TOKENS:
        raise ValueError

    history = history_with_input[:-1]
    generator = run(message, history, system_prompt, max_new_tokens, temperature, top_p, top_k)
    try:
        first_response = next(generator)
        yield history + [(message, first_response)]
    except StopIteration:
        yield history + [(message, '')]
    for response in generator:
        yield history + [(message, response)]

def process_example(message):
    generator = generate(message, [], DEFAULT_SYSTEM_PROMPT, 1024, 1, 0.95, 50)
    for x in generator:
        pass
    return '', x

def check_input_token_length(message, chat_history, system_prompt):
    input_token_length = len(message) + len(chat_history)
    if input_token_length > MAX_INPUT_TOKEN_LENGTH:
        raise gr.Error(f"The accumulated input is too long ({input_token_length} > {MAX_INPUT_TOKEN_LENGTH}). Clear your chat history and try again.")

with gr.Block() as demo:
    gr.Markdown(DESCRIPTION)

    with gr.Group():
        with gr.Row():
            textbox = gr.Textbox(
                container=False,
                show_label=False,
                placeholder='Hi, Zephyr',
                scale=10
            )
            submit_button = gr.Button('Submit', variant='primary', scale=1, min_width=0)

    with gr.Row():
        retry_button = gr.Button('Retry', variant='secondary')
        undo_button = gr.Button('Undo', variant='secondary')
        clear_button = gr.Button('Clear', variant='secondary')

    saved_input = gr.State()

    with gr.Accordion(label='Advanced options', open=False):
        system_prompt = gr.Textbox(label='System prompt', value=DEFAULT_SYSTEM_PROMPT, lines=5, interactive=False)
        max_new_tokens = gr.Slider(label='Max New Tokens', minimum=1, maximum=MAX_MAX_NEW_TOKENS, step=1, value=DEFAULT_MAX_NEW_TOKENS)
        temperature = gr.Slider(label='Temperature', minimum=0.1, maximum=4.0, step=0.1, value=0.1)
        top_p = gr.Slider(label='Top-P (nucleus sampling)', minimum=0.05, maximum=1.0, step=0.05, value=0.9)
        top_k = gr.Slider(label='Top-K', minimum=1, maximum=1000, step=1, value=10)

    textbox.submit(
        fn=clear_and_save_textbox,
        inputs=textbox,
        outputs=[textbox, saved_input],
        api_name=False,
        queue=False,
    ).then(
        fn=display_input,
        inputs=[saved_input, chatbot],
        outputs=chatbot,
        api_name=False,
        queue=False,
    ).then(
        fn=check_input_token_length,
        inputs=[saved_input, chatbot, system_prompt],
        api_name=False,
        queue=False,
    ).success(
        fn=generate,
        inputs=[
            saved_input,
            chatbot,
            system_prompt,
            max_new_tokens,
            temperature,
            top_p,
            top_k,
        ],
        outputs=chatbot,
        api_name=False,
    )

    button_event_preprocess = submit_button.click(
        fn=clear_and_save_textbox,
        inputs=textbox,
        outputs=[textbox, saved_input],
        api_name=False,
        queue=False,
    ).then(
        fn=display_input,
        inputs=[saved_input, chatbot],
        outputs=chatbot,
        api_name=False,
        queue=False,
    ).then(
        fn=check_input_token_length,
        inputs=[saved_input, chatbot, system_prompt],
        api_name=False,
        queue=False,
    ).success(
        fn=generate,
        inputs=[
            saved_input,
            chatbot,
            system_prompt,
            max_new_tokens,
            temperature,
            top_p,
            top_k,
        ],
        outputs=chatbot,
        api_name=False,
    )

    retry_button.click(
        fn=delete_prev_fn,
        inputs=chatbot,
        outputs=[chatbot, saved_input],
        api_name=False,
        queue=False,
    ).then(
        fn=display_input,
        inputs=[saved_input, chatbot],
        outputs=chatbot,
        api_name=False,
        queue=False,
    ).then(
        fn=generate,
        inputs=[
            saved_input,
            chatbot,
            system_prompt,
            max_new_tokens,
            temperature,
            top_p,
            top_k,
        ],
        outputs=chatbot,
        api_name=False,
    )

    undo_button.click(
        fn=delete_prev_fn,
        inputs=chatbot,
        outputs=[chatbot, saved_input],
        api_name=False,
        queue=False,
    ).then(
        fn=lambda x: x,
        inputs=[saved_input],
        outputs=textbox,
        api_name=False,
        queue=False,
    )

    clear_button.click(
        fn=lambda: ([], ''),
        outputs=[chatbot, saved_input],
        queue=False,
        api_name=False,
    )


demo.queue(max_size=32).launch(show_api=False)