File size: 9,555 Bytes
936b915
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7853329
 
936b915
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
import gradio as gr
from huggingface_hub import InferenceClient

# Initialize clients
text_client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
image_client = InferenceClient("SG161222/RealVisXL_V3.0")

def check_custom_responses(message: str) -> str:
    """Check for specific patterns and return custom responses."""
    message_lower = message.lower()
    custom_responses = {
        "what is ur name?": "xylaria",
        "what is ur Name?": "xylaria",
        "what is Ur name?": "xylaria",
        "what is Ur Name?": "xylaria",
        "What is ur name?": "xylaria",
        "What is ur Name?": "xylaria",
        "What is Ur name?": "xylaria",
        "What is Ur Name?": "xylaria",
        "what's ur name?": "xylaria",
        "what's ur Name?": "xylaria",
        "what's Ur name?": "xylaria",
        "what's Ur Name?": "xylaria",
        "whats ur name?": "xylaria",
        "whats ur Name?": "xylaria",
        "whats Ur name?": "xylaria",
        "whats Ur Name?": "xylaria",
        "what's your name?": "xylaria",
        "what's your Name?": "xylaria",
        "what's Your name?": "xylaria",
        "what's Your Name?": "xylaria",
        "Whats ur name?": "xylaria",
        "Whats ur Name?": "xylaria",
        "Whats Ur name?": "xylaria",
        "Whats Ur Name?": "xylaria",
        "What Is Your Name?": "xylaria",
        "What Is Ur Name?": "xylaria",
        "What Is Your Name?": "xylaria",
        "What Is Ur Name?": "xylaria",
        "what is your name?": "xylaria",
        "what is your Name?": "xylaria",
        "what is Your name?": "xylaria",
        "what is Your Name?": "xylaria",
        "how many 'r' is in strawberry?": "3",
        "how many 'R' is in strawberry?": "3",
        "how many 'r' Is in strawberry?": "3",
        "how many 'R' Is in strawberry?": "3",
        "How many 'r' is in strawberry?": "3",
        "How many 'R' is in strawberry?": "3",
        "How Many 'r' Is In Strawberry?": "3",
        "How Many 'R' Is In Strawberry?": "3",
        "how many r is in strawberry?": "3",
        "how many R is in strawberry?": "3",
        "how many r Is in strawberry?": "3",
        "how many R Is in strawberry?": "3",
        "How many r is in strawberry?": "3",
        "How many R is in strawberry?": "3",
        "How Many R Is In Strawberry?": "3",
        "how many 'r' in strawberry?": "3",
        "how many r's are in strawberry?": "3",
        "how many Rs are in strawberry?": "3",
        "How Many R's Are In Strawberry?": "3",
        "How Many Rs Are In Strawberry?": "3",
        "who is your developer?": "sk md saad amin",
        "who is your Developer?": "sk md saad amin",
        "who is Your Developer?": "sk md saad amin",
        "who is ur developer?": "sk md saad amin",
        "who is ur Developer?": "sk md saad amin",
        "who is Your Developer?": "sk md saad amin",
        "Who is ur developer?": "sk md saad amin",
        "Who is ur Developer?": "sk md saad amin",
        "who is ur dev?": "sk md saad amin",
        "Who is ur dev?": "sk md saad amin",
        "who is your dev?": "sk md saad amin",
        "Who is your dev?": "sk md saad amin",
        "Who's your developer?": "sk md saad amin",
        "Who's ur developer?": "sk md saad amin",
        "Who Is Your Developer?": "sk md saad amin",
        "Who Is Ur Developer?": "sk md saad amin",
        "Who Is Your Dev?": "sk md saad amin",
        "Who Is Ur Dev?": "sk md saad amin",
        "who's your developer?": "sk md saad amin",
        "who's ur developer?": "sk md saad amin",
        "who is your devloper?": "sk md saad amin", 
        "who is ur devloper?": "sk md saad amin",   
        "how many r is in strawberry?": "3",
        "how many R is in strawberry?": "3",
        "how many r Is in strawberry?": "3",
        "how many R Is in strawberry?": "3",
        "How many r is in strawberry?": "3",
        "How many R is in strawberry?": "3",
        "How Many R Is In Strawberry?": "3",
        "how many 'r' is in strawberry?": "3",
        "how many 'R' is in strawberry?": "3",
        "how many 'r' Is in strawberry?": "3",
        "how many 'R' Is in strawberry?": "3",
        "How many 'r' is in strawberry?": "3",
        "How many 'R' is in strawberry?": "3",
        "How Many 'r' Is In Strawberry?": "3",
        "How Many 'R' Is In Strawberry?": "3",
        "how many r's are in strawberry?": "3",
        "how many Rs are in strawberry?": "3",
        "How Many R's Are In Strawberry?": "3",
        "How Many Rs Are In Strawberry?": "3",
        "how many Rs's are in strawberry?": "3",
        "wat is ur name?": "xylaria",
        "wat is ur Name?": "xylaria",
        "wut is ur name?": "xylaria",
        "wut ur name?": "xylaria",
        "wats ur name?": "xylaria",
        "wats ur name": "xylaria",
        "who's ur dev?": "sk md saad amin",
        "who's your dev?": "sk md saad amin",
        "who ur dev?": "sk md saad amin",
        "who's ur devloper?": "sk md saad amin", 
        "how many r in strawbary?": "3",
        "how many r in strawbary?": "3",
        "how many R in strawbary?": "3",
        "how many 'r' in strawbary?": "3",
        "how many 'R' in strawbary?": "3",
        "how many r in strawbry?": "3",
        "how many R in strawbry?": "3",
        "how many r is in strawbry?": "3",
        "how many 'r' is in strawbry?": "3",
        "how many 'R' is in strawbry?": "3",
        "who is ur dev": "sk md saad amin",
        "who is ur devloper": "sk md saad amin", 
        "what is ur dev": "sk md saad amin",
        "who is ur dev?": "sk md saad amin",
        "who is ur dev?": "sk md saad amin",
        "whats ur dev?": "sk md saad amin",
    }

    for pattern, response in custom_responses.items():
        if pattern in message_lower:
            return response
    return None

def is_image_request(message: str) -> bool:
    """Detect if the message is requesting image generation."""
    image_triggers = [
        "generate an image",
        "create an image",
        "draw",
        "make a picture",
        "generate a picture",
        "create a picture",
        "generate art",
        "create art",
        "make art",
        "visualize",
        "show me",
    ]
    message_lower = message.lower()
    return any(trigger in message_lower for trigger in image_triggers)

def generate_image(prompt: str) -> str:
    """Generate an image using DALLE-4K model."""
    try:
        response = image_client.text_to_image(
            prompt,
            parameters={
                "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth",
                "num_inference_steps": 30,
                "guidance_scale": 7.5,
                "sampling_steps": 15,
                "upscaler": "4x-UltraSharp",
                "denoising_strength": 0.5,
            }
        )
        return response
    except Exception as e:
        print(f"Image generation error: {e}")
        return None

def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    # First check for custom responses
    custom_response = check_custom_responses(message)
    if custom_response:
        yield custom_response
        return

    if is_image_request(message):
        try:
            image = generate_image(message)
            if image:
                return f"Here's your generated image based on: {message}"
            else:
                return "Sorry, I couldn't generate the image. Please try again."
        except Exception as e:
            return f"An error occurred while generating the image: {str(e)}"

    # Prepare conversation history
    messages = [{"role": "system", "content": system_message}]
    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})
    
    messages.append({"role": "user", "content": message})

    # Get response from model
    response = ""
    for message in text_client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content
        response += token
        yield response

    yield response

# Custom CSS for the Gradio interface
custom_css = """
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600&display=swap');
body, .gradio-container {
    font-family: 'Inter', sans-serif;
}
"""

# System message
system_message = """
You are a helpful assistant. Given a script, divide it into segments suitable for generating images, ensuring each segment is less than 500 characters you make 6 prompts for a video quires

"""

# Gradio chat interface
demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(
            value=system_message,
            visible=False,
        ),
        gr.Slider(
            minimum=1,
            maximum=16343,
            value=16343,
            step=1,
            label="Max new tokens"
        ),
        gr.Slider(
            minimum=0.1,
            maximum=4.0,
            value=0.7,
            step=0.1,
            label="Temperature"
        ),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)"
        ),
    ],
    css=custom_css
)
demo.launch()