Spaces:
Runtime error
Runtime error
File size: 8,583 Bytes
b3b66bf c919a10 53c7098 6aaa79e 59c62cc b9f9a46 684bece 53c7098 c919a10 90a0c6e af4bac7 0f3449e c919a10 0f3449e c919a10 af4bac7 81d02d1 f599584 828cfdc 81d02d1 828cfdc 81d02d1 c919a10 828cfdc 53c7098 81d02d1 f599584 828cfdc 81d02d1 828cfdc 81d02d1 53c7098 828cfdc 8c97520 81d02d1 8c97520 9452a52 8c97520 59c62cc b9f9a46 f6a6c6d 684bece f6a6c6d 684bece 9452a52 c919a10 b3b66bf |
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 |
import gradio as gr
import gemini_gradio
import openai_gradio
import anthropic_gradio
import sambanova_gradio
import xai_gradio
import hyperbolic_gradio
import perplexity_gradio
with gr.Blocks(fill_height=True) as demo:
with gr.Tab("Gemini"):
with gr.Row():
gemini_model = gr.Dropdown(
choices=[
'gemini-1.5-flash', # Fast and versatile performance
'gemini-1.5-flash-8b', # High volume, lower intelligence tasks
'gemini-1.5-pro', # Complex reasoning tasks
'gemini-exp-1114' # Quality improvements
],
value='gemini-1.5-pro', # Default to the most advanced model
label="Select Gemini Model",
interactive=True
)
gemini_interface = gr.load(
name=gemini_model.value,
src=gemini_gradio.registry,
)
def update_gemini_model(new_model):
return gr.load(
name=new_model,
src=gemini_gradio.registry,
)
gemini_model.change(
fn=update_gemini_model,
inputs=[gemini_model],
outputs=[gemini_interface]
)
with gr.Tab("ChatGPT"):
with gr.Row():
model_choice = gr.Dropdown(
choices=[
'gpt-4o', # Most advanced model
'gpt-4o-2024-08-06', # Latest snapshot
'gpt-4o-2024-05-13', # Original snapshot
'chatgpt-4o-latest', # Latest ChatGPT version
'gpt-4o-mini', # Small model
'gpt-4o-mini-2024-07-18', # Latest mini version
'o1-preview', # Reasoning model
'o1-preview-2024-09-12', # Latest o1 model snapshot
'o1-mini', # Faster reasoning model
'o1-mini-2024-09-12', # Latest o1-mini model snapshot
'gpt-4-turbo', # Latest GPT-4 Turbo model
'gpt-4-turbo-2024-04-09', # Latest GPT-4 Turbo snapshot
'gpt-4-turbo-preview', # GPT-4 Turbo preview model
'gpt-4-0125-preview', # GPT-4 Turbo preview model for laziness
'gpt-4-1106-preview', # Improved instruction following model
'gpt-4', # Standard GPT-4 model
'gpt-4-0613' # Snapshot of GPT-4 from June 2023
],
value='gpt-4o', # Default to the most advanced model
label="Select Model",
interactive=True
)
chatgpt_interface = gr.load(
name=model_choice.value,
src=openai_gradio.registry,
accept_token=True
)
def update_model(new_model):
return gr.load(
name=new_model,
src=openai_gradio.registry,
accept_token=True
)
model_choice.change(
fn=update_model,
inputs=[model_choice],
outputs=[chatgpt_interface]
)
with gr.Tab("Claude"):
with gr.Row():
claude_model = gr.Dropdown(
choices=[
'claude-3-5-sonnet-20241022', # Latest Sonnet
'claude-3-5-haiku-20241022', # Latest Haiku
'claude-3-opus-20240229', # Opus
'claude-3-sonnet-20240229', # Previous Sonnet
'claude-3-haiku-20240307' # Previous Haiku
],
value='claude-3-5-sonnet-20241022', # Default to latest Sonnet
label="Select Model",
interactive=True
)
claude_interface = gr.load(
name=claude_model.value,
src=anthropic_gradio.registry,
accept_token=True
)
def update_claude_model(new_model):
return gr.load(
name=new_model,
src=anthropic_gradio.registry,
accept_token=True
)
claude_model.change(
fn=update_claude_model,
inputs=[claude_model],
outputs=[claude_interface]
)
with gr.Tab("Meta Llama"):
with gr.Row():
llama_model = gr.Dropdown(
choices=[
'Meta-Llama-3.2-1B-Instruct', # Llama 3.2 1B
'Meta-Llama-3.2-3B-Instruct', # Llama 3.2 3B
'Llama-3.2-11B-Vision-Instruct', # Llama 3.2 11B
'Llama-3.2-90B-Vision-Instruct', # Llama 3.2 90B
'Meta-Llama-3.1-8B-Instruct', # Llama 3.1 8B
'Meta-Llama-3.1-70B-Instruct', # Llama 3.1 70B
'Meta-Llama-3.1-405B-Instruct' # Llama 3.1 405B
],
value='Llama-3.2-90B-Vision-Instruct', # Default to the most advanced model
label="Select Llama Model",
interactive=True
)
llama_interface = gr.load(
name=llama_model.value,
src=sambanova_gradio.registry,
accept_token=True,
multimodal=True
)
def update_llama_model(new_model):
return gr.load(
name=new_model,
src=sambanova_gradio.registry,
accept_token=True,
multimodal=True
)
llama_model.change(
fn=update_llama_model,
inputs=[llama_model],
outputs=[llama_interface]
)
gr.Markdown("**Note:** You need to use a SambaNova API key from [SambaNova Cloud](https://cloud.sambanova.ai/).")
with gr.Tab("Grok"):
gr.load(
name='grok-beta',
src=xai_gradio.registry,
accept_token=True
)
with gr.Tab("Qwen2.5 72B"):
gr.load(
name='Qwen/Qwen2.5-72B-Instruct',
src=hyperbolic_gradio.registry,
accept_token=True
)
gr.Markdown("**Note:** You need to use a Hyperbolic API key from [Hyperbolic](https://app.hyperbolic.xyz/).")
with gr.Tab("Perplexity"):
with gr.Row():
perplexity_model = gr.Dropdown(
choices=[
# Sonar Models (Online)
'llama-3.1-sonar-small-128k-online', # 8B params
'llama-3.1-sonar-large-128k-online', # 70B params
'llama-3.1-sonar-huge-128k-online', # 405B params
# Sonar Models (Chat)
'llama-3.1-sonar-small-128k-chat', # 8B params
'llama-3.1-sonar-large-128k-chat', # 70B params
# Open Source Models
'llama-3.1-8b-instruct', # 8B params
'llama-3.1-70b-instruct' # 70B params
],
value='llama-3.1-sonar-large-128k-online', # Default to large online model
label="Select Perplexity Model",
interactive=True
)
perplexity_interface = gr.load(
name=perplexity_model.value,
src=perplexity_gradio.registry,
accept_token=True
)
def update_perplexity_model(new_model):
return gr.load(
name=new_model,
src=perplexity_gradio.registry,
accept_token=True
)
perplexity_model.change(
fn=update_perplexity_model,
inputs=[perplexity_model],
outputs=[perplexity_interface]
)
gr.Markdown("""
**Note:** Models are grouped into three categories:
- **Sonar Online Models**: Include search capabilities (beta access required)
- **Sonar Chat Models**: Standard chat models
- **Open Source Models**: Based on Hugging Face implementations
For access to Online LLMs features, please fill out the [beta access form](https://perplexity.typeform.com/apiaccessform?typeform-source=docs.perplexity.ai).
""")
demo.launch()
|