File size: 7,415 Bytes
ea30afb
9fdba0a
eeb8511
908d449
 
eeb8511
 
 
67bb418
 
42be940
 
eeb8511
 
 
 
 
7916190
 
 
eeb8511
 
67bb418
 
 
 
12a2b97
908d449
ea30afb
 
 
2c0f2ed
 
 
 
 
 
9fdba0a
 
 
 
 
eeb8511
 
fc7864f
7916190
2c0f2ed
 
42be940
 
eeb8511
9fdba0a
ea30afb
908d449
 
 
 
 
9fdba0a
908d449
2c0f2ed
 
 
42be940
 
 
eeb8511
fc7864f
eeb8511
7916190
 
 
 
eeb8511
 
fc7864f
 
eeb8511
7916190
fc7864f
7916190
 
eeb8511
 
9fdba0a
 
 
 
 
 
 
 
908d449
 
 
 
 
 
 
eeb8511
ea30afb
908d449
 
fc7864f
 
67bb418
 
 
 
 
 
908d449
 
eeb8511
908d449
 
7916190
 
 
2c0f2ed
7916190
 
2c0f2ed
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
42be940
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
908d449
9fdba0a
eeb8511
9fdba0a
 
 
 
 
eeb8511
fc7864f
7916190
2c0f2ed
 
42be940
 
eeb8511
 
 
908d449
eeb8511
42be940
eeb8511
908d449
 
 
fc7864f
 
 
 
908d449
 
 
7916190
 
2c0f2ed
 
42be940
 
 
908d449
 
9fdba0a
 
908d449
9fdba0a
 
 
908d449
 
 
9fdba0a
 
908d449
9fdba0a
 
 
908d449
 
fc7864f
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
import os
import time
from typing import List, Tuple, Optional

import google.generativeai as genai
import gradio as gr
from PIL import Image

print("google-generativeai:", genai.__version__)

TITLE = """<h1 align="center">Gemini Playground 💬</h1>"""
SUBTITLE = """<h2 align="center">Play with Gemini Pro and Gemini Pro Vision API</h2>"""
DUPLICATE = """
<div style="text-align: center; display: flex; justify-content: center; align-items: center;">
    <a href="https://huggingface.co/spaces/SkalskiP/ChatGemini?duplicate=true">
        <img src="https://bit.ly/3gLdBN6" alt="Duplicate Space" style="margin-right: 10px;">
    </a>
    <span>Duplicate the Space and run securely with your 
        <a href="https://makersuite.google.com/app/apikey">GOOGLE API KEY</a>.
    </span>
</div>
"""
AVATAR_IMAGES = (
    None,
    "https://media.roboflow.com/spaces/gemini-icon.png"
)


GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")


def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]:
    if not stop_sequences:
        return None
    return [sequence.strip() for sequence in stop_sequences.split(",")]


def user(text_prompt: str, chatbot: List[Tuple[str, str]]):
    return "", chatbot + [[text_prompt, None]]


def bot(
    google_key: str,
    image_prompt: Optional[Image.Image],
    image_prompt_2: Optional[Image.Image],
    temperature: float,
    max_output_tokens: int,
    stop_sequences: str,
    top_k: int,
    top_p: float,
    chatbot: List[Tuple[str, str]]
):
    google_key = google_key if google_key else GOOGLE_API_KEY
    if not google_key:
        raise ValueError(
            "GOOGLE_API_KEY is not set. "
            "Please follow the instructions in the README to set it up.")

    text_prompt = chatbot[-1][0]
    genai.configure(api_key=google_key)
    generation_config = genai.types.GenerationConfig(
        temperature=temperature,
        max_output_tokens=max_output_tokens,
        stop_sequences=preprocess_stop_sequences(stop_sequences=stop_sequences),
        top_k=top_k,
        top_p=top_p)

    if image_prompt is None and image_prompt_2 is None:
        model = genai.GenerativeModel('gemini-pro')
        response = model.generate_content(
            text_prompt,
            stream=True,
            generation_config=generation_config)
        response.resolve()
    else:
        contents = [text_prompt, image_prompt, image_prompt_2]
        contents = [content for content in contents if content is not None]
        model = genai.GenerativeModel('gemini-pro-vision')
        response = model.generate_content(
            contents=contents,
            stream=True,
            generation_config=generation_config)
        response.resolve()

    # streaming effect
    chatbot[-1][1] = ""
    for chunk in response:
        for i in range(0, len(chunk.text), 10):
            section = chunk.text[i:i + 10]
            chatbot[-1][1] += section
            time.sleep(0.01)
            yield chatbot


google_key_component = gr.Textbox(
    label="GOOGLE API KEY",
    value="",
    type="password",
    placeholder="...",
    info="You have to provide your own GOOGLE_API_KEY for this app to function properly",
    visible=GOOGLE_API_KEY is None
)

image_prompt_component = gr.Image(type="pil", label="Image")
image_prompt_2_component = gr.Image(type="pil", label="Image")
chatbot_component = gr.Chatbot(
    label='Gemini',
    bubble_full_width=False,
    avatar_images=AVATAR_IMAGES,
    scale=2
)
text_prompt_component = gr.Textbox(
    placeholder="Hi there!",
    label="Ask me anything and press Enter"
)
run_button_component = gr.Button()
temperature_component = gr.Slider(
    minimum=0,
    maximum=1.0,
    value=0.4,
    step=0.05,
    label="Temperature",
    info=(
        "Temperature controls the degree of randomness in token selection. Lower "
        "temperatures are good for prompts that expect a true or correct response, "
        "while higher temperatures can lead to more diverse or unexpected results. "
    ))
max_output_tokens_component = gr.Slider(
    minimum=1,
    maximum=2048,
    value=1024,
    step=1,
    label="Token limit",
    info=(
        "Token limit determines the maximum amount of text output from one prompt. A "
        "token is approximately four characters. The default value is 2048."
    ))
stop_sequences_component = gr.Textbox(
    label="Add stop sequence",
    value="",
    type="text",
    placeholder="STOP, END",
    info=(
        "A stop sequence is a series of characters (including spaces) that stops "
        "response generation if the model encounters it. The sequence is not included "
        "as part of the response. You can add up to five stop sequences."
    ))
top_k_component = gr.Slider(
    minimum=1,
    maximum=40,
    value=32,
    step=1,
    label="Top-K",
    info=(
        "Top-k changes how the model selects tokens for output. A top-k of 1 means the "
        "selected token is the most probable among all tokens in the model’s "
        "vocabulary (also called greedy decoding), while a top-k of 3 means that the "
        "next token is selected from among the 3 most probable tokens (using "
        "temperature)."
    ))
top_p_component = gr.Slider(
    minimum=0,
    maximum=1,
    value=1,
    step=0.01,
    label="Top-P",
    info=(
        "Top-p changes how the model selects tokens for output. Tokens are selected "
        "from most probable to least until the sum of their probabilities equals the "
        "top-p value. For example, if tokens A, B, and C have a probability of .3, .2, "
        "and .1 and the top-p value is .5, then the model will select either A or B as "
        "the next token (using temperature). "
    ))

user_inputs = [
    text_prompt_component,
    chatbot_component
]

bot_inputs = [
    google_key_component,
    image_prompt_component,
    image_prompt_2_component,
    temperature_component,
    max_output_tokens_component,
    stop_sequences_component,
    top_k_component,
    top_p_component,
    chatbot_component
]

with gr.Blocks() as demo:
    gr.HTML(TITLE)
    gr.HTML(SUBTITLE)
    gr.HTML(DUPLICATE)
    with gr.Column():
        google_key_component.render()
        with gr.Row():
            with gr.Column(scale=1):
                image_prompt_component.render()
                with gr.Accordion("Multi Image", open=False):
                    image_prompt_2_component.render()
            chatbot_component.render()
        text_prompt_component.render()
        run_button_component.render()
        with gr.Accordion("Parameters", open=False):
            temperature_component.render()
            max_output_tokens_component.render()
            stop_sequences_component.render()
            with gr.Accordion("Advanced", open=False):
                top_k_component.render()
                top_p_component.render()

    run_button_component.click(
        fn=user,
        inputs=user_inputs,
        outputs=[text_prompt_component, chatbot_component],
        queue=False
    ).then(
        fn=bot, inputs=bot_inputs, outputs=[chatbot_component],
    )

    text_prompt_component.submit(
        fn=user,
        inputs=user_inputs,
        outputs=[text_prompt_component, chatbot_component],
        queue=False
    ).then(
        fn=bot, inputs=bot_inputs, outputs=[chatbot_component],
    )

demo.queue(max_size=99).launch(debug=False, show_error=True)