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###################################################################################################
# Evaluations_Benchmarks_tab.py - Gradio code for G-Eval testing
# We will use the G-Eval API to evaluate the quality of the generated summaries.
import logging
import gradio as gr
from App_Function_Libraries.Benchmarks_Evaluations.ms_g_eval import run_geval
from App_Function_Libraries.Utils.Utils import default_api_endpoint, global_api_endpoints, format_api_name
def create_geval_tab():
with gr.Tab("G-Eval", visible=True):
gr.Markdown("# G-Eval Summarization Evaluation")
with gr.Row():
with gr.Column():
document_input = gr.Textbox(label="Source Document", lines=10)
summary_input = gr.Textbox(label="Summary", lines=5)
api_name_input = gr.Dropdown(
choices=["OpenAI", "Anthropic", "Cohere", "Groq", "OpenRouter", "DeepSeek", "HuggingFace", "Mistral", "Llama.cpp", "Kobold", "Ooba", "Tabbyapi", "VLLM", "Local-LLM", "Ollama"],
label="Select API"
)
api_key_input = gr.Textbox(label="API Key (if required)", type="password")
evaluate_button = gr.Button("Evaluate Summary")
with gr.Column():
output = gr.Textbox(label="Evaluation Results", lines=10)
evaluate_button.click(
fn=run_geval,
inputs=[document_input, summary_input, api_name_input, api_key_input],
outputs=output
)
return document_input, summary_input, api_name_input, api_key_input, evaluate_button, output
def create_infinite_bench_tab():
try:
default_value = None
if default_api_endpoint:
if default_api_endpoint in global_api_endpoints:
default_value = format_api_name(default_api_endpoint)
else:
logging.warning(f"Default API endpoint '{default_api_endpoint}' not found in global_api_endpoints")
except Exception as e:
logging.error(f"Error setting default API endpoint: {str(e)}")
default_value = None
with gr.Tab("Infinite Bench", visible=True):
gr.Markdown("# Infinite Bench Evaluation (Coming Soon)")
with gr.Row():
with gr.Column():
# Refactored API selection dropdown
api_name_input = gr.Dropdown(
choices=["None"] + [format_api_name(api) for api in global_api_endpoints],
value=default_value,
label="API for Summarization (Optional)"
)
api_key_input = gr.Textbox(label="API Key (if required)", type="password")
evaluate_button = gr.Button("Evaluate Summary")
with gr.Column():
output = gr.Textbox(label="Evaluation Results", lines=10)
# evaluate_button.click(
# fn=run_geval,
# inputs=[api_name_input, api_key_input],
# outputs=output
# )
return api_name_input, api_key_input, evaluate_button, output
# If you want to run this as a standalone Gradio app
if __name__ == "__main__":
with gr.Blocks() as demo:
create_geval_tab()
demo.launch()
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