|
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 |
|
import mistral_gradio |
|
import fireworks_gradio |
|
import cerebras_gradio |
|
import groq_gradio |
|
import together_gradio |
|
import nvidia_gradio |
|
import dashscope_gradio |
|
|
|
|
|
def create_interface(model_name, src_registry, **kwargs): |
|
return gr.load( |
|
name=model_name, |
|
src=src_registry, |
|
fill_height=True, |
|
**kwargs |
|
) |
|
|
|
def update_model(new_model, container, src_registry, **kwargs): |
|
with container: |
|
|
|
container.clear() |
|
|
|
new_interface = create_interface(new_model, src_registry, **kwargs) |
|
new_interface.render() |
|
|
|
with gr.Blocks(fill_height=True) as demo: |
|
|
|
with gr.Tab("Meta Llama"): |
|
with gr.Row(): |
|
llama_model = gr.Dropdown( |
|
choices=[ |
|
'Meta-Llama-3.2-1B-Instruct', |
|
'Meta-Llama-3.2-3B-Instruct', |
|
'Llama-3.2-11B-Vision-Instruct', |
|
'Llama-3.2-90B-Vision-Instruct', |
|
'Meta-Llama-3.1-8B-Instruct', |
|
'Meta-Llama-3.1-70B-Instruct', |
|
'Meta-Llama-3.1-405B-Instruct' |
|
], |
|
value='Llama-3.2-90B-Vision-Instruct', |
|
label="Select Llama Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as llama_container: |
|
llama_interface = create_interface(llama_model.value, sambanova_gradio.registry, multimodal=True) |
|
|
|
llama_model.change( |
|
fn=lambda new_model: update_model(new_model, llama_container, sambanova_gradio.registry, multimodal=True), |
|
inputs=[llama_model], |
|
outputs=[] |
|
) |
|
|
|
gr.Markdown("**Note:** You need to use a SambaNova API key from [SambaNova Cloud](https://cloud.sambanova.ai/).") |
|
|
|
|
|
with gr.Tab("Gemini"): |
|
with gr.Row(): |
|
gemini_model = gr.Dropdown( |
|
choices=[ |
|
'gemini-1.5-flash', |
|
'gemini-1.5-flash-8b', |
|
'gemini-1.5-pro', |
|
'gemini-exp-1114' |
|
], |
|
value='gemini-1.5-pro', |
|
label="Select Gemini Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as gemini_container: |
|
gemini_interface = create_interface(gemini_model.value, gemini_gradio.registry) |
|
|
|
gemini_model.change( |
|
fn=lambda new_model: update_model(new_model, gemini_container, gemini_gradio.registry), |
|
inputs=[gemini_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("ChatGPT"): |
|
with gr.Row(): |
|
model_choice = gr.Dropdown( |
|
choices=[ |
|
'gpt-4o-2024-11-20', |
|
'gpt-4o', |
|
'gpt-4o-2024-08-06', |
|
'gpt-4o-2024-05-13', |
|
'chatgpt-4o-latest', |
|
'gpt-4o-mini', |
|
'gpt-4o-mini-2024-07-18', |
|
'o1-preview', |
|
'o1-preview-2024-09-12', |
|
'o1-mini', |
|
'o1-mini-2024-09-12', |
|
'gpt-4-turbo', |
|
'gpt-4-turbo-2024-04-09', |
|
'gpt-4-turbo-preview', |
|
'gpt-4-0125-preview', |
|
'gpt-4-1106-preview', |
|
'gpt-4', |
|
'gpt-4-0613' |
|
], |
|
value='gpt-4o-2024-11-20', |
|
label="Select Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as chatgpt_container: |
|
chatgpt_interface = create_interface(model_choice.value, openai_gradio.registry) |
|
|
|
model_choice.change( |
|
fn=lambda new_model: update_model(new_model, chatgpt_container, openai_gradio.registry), |
|
inputs=[model_choice], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("Claude"): |
|
with gr.Row(): |
|
claude_model = gr.Dropdown( |
|
choices=[ |
|
'claude-3-5-sonnet-20241022', |
|
'claude-3-5-haiku-20241022', |
|
'claude-3-opus-20240229', |
|
'claude-3-sonnet-20240229', |
|
'claude-3-haiku-20240307' |
|
], |
|
value='claude-3-5-sonnet-20241022', |
|
label="Select Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as claude_container: |
|
claude_interface = create_interface(claude_model.value, anthropic_gradio.registry, accept_token=True) |
|
|
|
claude_model.change( |
|
fn=lambda new_model: update_model(new_model, claude_container, anthropic_gradio.registry, accept_token=True), |
|
inputs=[claude_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("Grok"): |
|
with gr.Row(): |
|
grok_model = gr.Dropdown( |
|
choices=[ |
|
'grok-beta', |
|
'grok-vision-beta' |
|
], |
|
value='grok-vision-beta', |
|
label="Select Grok Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as grok_container: |
|
grok_interface = create_interface(grok_model.value, xai_gradio.registry) |
|
|
|
grok_model.change( |
|
fn=lambda new_model: update_model(new_model, grok_container, xai_gradio.registry), |
|
inputs=[grok_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("Hugging Face"): |
|
with gr.Row(): |
|
hf_model = gr.Dropdown( |
|
choices=[ |
|
'Qwen/Qwen2.5-Coder-32B-Instruct', |
|
'Qwen/Qwen2.5-72B-Instruct', |
|
'meta-llama/Llama-3.1-70B-Instruct', |
|
'mistralai/Mixtral-8x7B-Instruct-v0.1', |
|
'meta-llama/Llama-3.1-8B-Instruct', |
|
'google/gemma-2-9b-it', |
|
'mistralai/Mistral-7B-v0.1', |
|
'meta-llama/Llama-2-7b-chat-hf', |
|
'meta-llama/Llama-3.2-3B-Instruct', |
|
'meta-llama/Llama-3.2-1B-Instruct', |
|
'Qwen/Qwen2.5-1.5B-Instruct', |
|
'microsoft/Phi-3.5-mini-instruct', |
|
'HuggingFaceTB/SmolLM2-1.7B-Instruct', |
|
'google/gemma-2-2b-it', |
|
'meta-llama/Llama-3.2-3B', |
|
'meta-llama/Llama-3.2-1B', |
|
'openai-community/gpt2' |
|
], |
|
value='HuggingFaceTB/SmolLM2-1.7B-Instruct', |
|
label="Select Hugging Face Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as hf_container: |
|
hf_interface = create_interface(hf_model.value, "models") |
|
|
|
hf_model.change( |
|
fn=lambda new_model: update_model(new_model, hf_container, "models"), |
|
inputs=[hf_model], |
|
outputs=[] |
|
) |
|
|
|
gr.Markdown(""" |
|
**Note:** These models are loaded directly from Hugging Face Hub. Some models may require authentication. |
|
""") |
|
|
|
|
|
with gr.Tab("Groq"): |
|
with gr.Row(): |
|
groq_model = gr.Dropdown( |
|
choices=[ |
|
'llama3-groq-8b-8192-tool-use-preview', |
|
'llama3-groq-70b-8192-tool-use-preview', |
|
'llama-3.2-1b-preview', |
|
'llama-3.2-3b-preview', |
|
'llama-3.2-11b-text-preview', |
|
'llama-3.2-90b-text-preview', |
|
'mixtral-8x7b-32768', |
|
'gemma2-9b-it', |
|
'gemma-7b-it' |
|
], |
|
value='llama3-groq-70b-8192-tool-use-preview', |
|
label="Select Groq Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as groq_container: |
|
groq_interface = create_interface(groq_model.value, groq_gradio.registry) |
|
|
|
groq_model.change( |
|
fn=lambda new_model: update_model(new_model, groq_container, groq_gradio.registry), |
|
inputs=[groq_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("Hyperbolic"): |
|
with gr.Row(): |
|
hyperbolic_model = gr.Dropdown( |
|
choices=[ |
|
'Qwen/Qwen2.5-Coder-32B-Instruct', |
|
'meta-llama/Llama-3.2-3B-Instruct', |
|
'meta-llama/Meta-Llama-3.1-8B-Instruct', |
|
'meta-llama/Meta-Llama-3.1-70B-Instruct', |
|
'meta-llama/Meta-Llama-3-70B-Instruct', |
|
'NousResearch/Hermes-3-Llama-3.1-70B', |
|
'Qwen/Qwen2.5-72B-Instruct', |
|
'deepseek-ai/DeepSeek-V2.5', |
|
'meta-llama/Meta-Llama-3.1-405B-Instruct' |
|
], |
|
value='Qwen/Qwen2.5-Coder-32B-Instruct', |
|
label="Select Hyperbolic Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as hyperbolic_container: |
|
hyperbolic_interface = create_interface(hyperbolic_model.value, hyperbolic_gradio.registry) |
|
|
|
hyperbolic_model.change( |
|
fn=lambda new_model: update_model(new_model, hyperbolic_container, hyperbolic_gradio.registry), |
|
inputs=[hyperbolic_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("Qwen"): |
|
with gr.Row(): |
|
qwen_model = gr.Dropdown( |
|
choices=[ |
|
'qwen-turbo-latest', |
|
'qwen-turbo', |
|
'qwen-plus', |
|
'qwen-max', |
|
'qwen1.5-110b-chat', |
|
'qwen1.5-72b-chat', |
|
'qwen1.5-32b-chat', |
|
'qwen1.5-14b-chat', |
|
'qwen1.5-7b-chat' |
|
], |
|
value='qwen-turbo-latest', |
|
label="Select Qwen Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as qwen_container: |
|
qwen_interface = create_interface(qwen_model.value, dashscope_gradio.registry) |
|
|
|
qwen_model.change( |
|
fn=lambda new_model: update_model(new_model, qwen_container, dashscope_gradio.registry), |
|
inputs=[qwen_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("Perplexity"): |
|
with gr.Row(): |
|
perplexity_model = gr.Dropdown( |
|
choices=[ |
|
'llama-3.1-sonar-small-128k-online', |
|
'llama-3.1-sonar-large-128k-online', |
|
'llama-3.1-sonar-huge-128k-online', |
|
'llama-3.1-sonar-small-128k-chat', |
|
'llama-3.1-sonar-large-128k-chat', |
|
'llama-3.1-8b-instruct', |
|
'llama-3.1-70b-instruct' |
|
], |
|
value='llama-3.1-sonar-large-128k-online', |
|
label="Select Perplexity Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as perplexity_container: |
|
perplexity_interface = create_interface(perplexity_model.value, perplexity_gradio.registry, accept_token=True) |
|
|
|
perplexity_model.change( |
|
fn=lambda new_model: update_model(new_model, perplexity_container, perplexity_gradio.registry, accept_token=True), |
|
inputs=[perplexity_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("Mistral"): |
|
with gr.Row(): |
|
mistral_model = gr.Dropdown( |
|
choices=[ |
|
'mistral-large-latest', |
|
'pixtral-large-latest', |
|
'ministral-3b-latest', |
|
'ministral-8b-latest', |
|
'mistral-small-latest', |
|
'codestral-latest', |
|
'mistral-embed', |
|
'mistral-moderation-latest', |
|
'pixtral-12b-2409', |
|
'open-mistral-nemo', |
|
'open-codestral-mamba' |
|
], |
|
value='pixtral-large-latest', |
|
label="Select Mistral Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as mistral_container: |
|
mistral_interface = create_interface(mistral_model.value, mistral_gradio.registry) |
|
|
|
mistral_model.change( |
|
fn=lambda new_model: update_model(new_model, mistral_container, mistral_gradio.registry), |
|
inputs=[mistral_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("Fireworks"): |
|
with gr.Row(): |
|
fireworks_model = gr.Dropdown( |
|
choices=[ |
|
'f1-preview', |
|
'f1-mini-preview' |
|
], |
|
value='f1-preview', |
|
label="Select Fireworks Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as fireworks_container: |
|
fireworks_interface = create_interface(fireworks_model.value, fireworks_gradio.registry) |
|
|
|
fireworks_model.change( |
|
fn=lambda new_model: update_model(new_model, fireworks_container, fireworks_gradio.registry), |
|
inputs=[fireworks_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("Cerebras"): |
|
with gr.Row(): |
|
cerebras_model = gr.Dropdown( |
|
choices=[ |
|
'llama3.1-8b', |
|
'llama3.1-70b', |
|
'llama3.1-405b' |
|
], |
|
value='llama3.1-70b', |
|
label="Select Cerebras Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as cerebras_container: |
|
cerebras_interface = create_interface(cerebras_model.value, cerebras_gradio.registry, accept_token=True) |
|
|
|
cerebras_model.change( |
|
fn=lambda new_model: update_model(new_model, cerebras_container, cerebras_gradio.registry, accept_token=True), |
|
inputs=[cerebras_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("Together"): |
|
with gr.Row(): |
|
together_model = gr.Dropdown( |
|
choices=[ |
|
'meta-llama/Llama-Vision-Free', |
|
'meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo', |
|
'meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo', |
|
'meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo', |
|
'meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo', |
|
'meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo', |
|
'meta-llama/Meta-Llama-3-8B-Instruct-Turbo', |
|
'meta-llama/Meta-Llama-3-70B-Instruct-Turbo', |
|
'meta-llama/Llama-3.2-3B-Instruct-Turbo', |
|
'meta-llama/Meta-Llama-3-8B-Instruct-Lite', |
|
'meta-llama/Meta-Llama-3-70B-Instruct-Lite', |
|
'meta-llama/Llama-3-8b-chat-hf', |
|
'meta-llama/Llama-3-70b-chat-hf', |
|
'nvidia/Llama-3.1-Nemotron-70B-Instruct-HF', |
|
'Qwen/Qwen2.5-Coder-32B-Instruct', |
|
'microsoft/WizardLM-2-8x22B', |
|
'google/gemma-2-27b-it', |
|
'google/gemma-2-9b-it', |
|
'databricks/dbrx-instruct', |
|
'mistralai/Mixtral-8x7B-Instruct-v0.1', |
|
'mistralai/Mixtral-8x22B-Instruct-v0.1', |
|
'Qwen/Qwen2.5-7B-Instruct-Turbo', |
|
'Qwen/Qwen2.5-72B-Instruct-Turbo', |
|
'Qwen/Qwen2-72B-Instruct', |
|
'deepseek-ai/deepseek-llm-67b-chat', |
|
'google/gemma-2b-it', |
|
'Gryphe/MythoMax-L2-13b', |
|
'meta-llama/Llama-2-13b-chat-hf', |
|
'mistralai/Mistral-7B-Instruct-v0.1', |
|
'mistralai/Mistral-7B-Instruct-v0.2', |
|
'mistralai/Mistral-7B-Instruct-v0.3', |
|
'NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO', |
|
'togethercomputer/StripedHyena-Nous-7B', |
|
'upstage/SOLAR-10.7B-Instruct-v1.0' |
|
], |
|
value='meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo', |
|
label="Select Together Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as together_container: |
|
together_interface = create_interface(together_model.value, together_gradio.registry, multimodal=True) |
|
|
|
together_model.change( |
|
fn=lambda new_model: update_model(new_model, together_container, together_gradio.registry, multimodal=True), |
|
inputs=[together_model], |
|
outputs=[] |
|
) |
|
|
|
|
|
with gr.Tab("NVIDIA"): |
|
with gr.Row(): |
|
nvidia_model = gr.Dropdown( |
|
choices=[ |
|
'nvidia/llama3-chatqa-1.5-70b', |
|
'nvidia/llama3-chatqa-1.5-8b', |
|
'nvidia-nemotron-4-340b-instruct', |
|
'meta/llama-3.1-70b-instruct', |
|
'meta/codellama-70b', |
|
'meta/llama2-70b', |
|
'meta/llama3-8b', |
|
'meta/llama3-70b', |
|
'mistralai/codestral-22b-instruct-v0.1', |
|
'mistralai/mathstral-7b-v0.1', |
|
'mistralai/mistral-large-2-instruct', |
|
'mistralai/mistral-7b-instruct', |
|
'mistralai/mistral-7b-instruct-v0.3', |
|
'mistralai/mixtral-8x7b-instruct', |
|
'mistralai/mixtral-8x22b-instruct', |
|
'mistralai/mistral-large', |
|
'google/gemma-2b', |
|
'google/gemma-7b', |
|
'google/gemma-2-2b-it', |
|
'google/gemma-2-9b-it', |
|
'google/gemma-2-27b-it', |
|
'google/codegemma-1.1-7b', |
|
'google/codegemma-7b', |
|
'google/recurrentgemma-2b', |
|
'google/shieldgemma-9b', |
|
'microsoft/phi-3-medium-128k-instruct', |
|
'microsoft/phi-3-medium-4k-instruct', |
|
'microsoft/phi-3-mini-128k-instruct', |
|
'microsoft/phi-3-mini-4k-instruct', |
|
'microsoft/phi-3-small-128k-instruct', |
|
'microsoft/phi-3-small-8k-instruct', |
|
'qwen/qwen2-7b-instruct', |
|
'databricks/dbrx-instruct', |
|
'deepseek-ai/deepseek-coder-6.7b-instruct', |
|
'upstage/solar-10.7b-instruct', |
|
'snowflake/arctic' |
|
], |
|
value='meta/llama-3.1-70b-instruct', |
|
label="Select NVIDIA Model", |
|
interactive=True |
|
) |
|
|
|
with gr.Column() as nvidia_container: |
|
nvidia_interface = create_interface(nvidia_model.value, nvidia_gradio.registry, accept_token=True) |
|
|
|
nvidia_model.change( |
|
fn=lambda new_model: update_model(new_model, nvidia_container, nvidia_gradio.registry, accept_token=True), |
|
inputs=[nvidia_model], |
|
outputs=[] |
|
) |
|
|
|
demo.launch(ssr_mode=False) |
|
|
|
|
|
|
