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import os
import tempfile
import gradio as gr
import toml
from aphra import translate
theme = gr.themes.Soft(
primary_hue="rose",
secondary_hue="pink",
spacing_size="lg",
)
def create_config_file(api_key, writer_model, searcher_model, critic_model):
config = {
"openrouter": {"api_key": api_key},
"llms": {
"writer": writer_model,
"searcher": searcher_model,
"critiquer": critic_model
}
}
with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.toml') as tmp:
toml.dump(config, tmp)
return tmp.name
def process_input(file, text_input, api_key, writer_model, searcher_model, critic_model, source_lang, target_lang):
if file is not None:
with open(file, 'r', encoding='utf-8') as file:
text = file.read()
else:
text = text_input
config_file = create_config_file(api_key, writer_model, searcher_model, critic_model)
try:
translation = translate(
source_language=source_lang,
target_language=target_lang,
text=text,
config_file=config_file,
log_calls=False
)
finally:
os.unlink(config_file)
return translation
def create_interface():
with gr.Blocks(theme=theme) as demo:
gr.Markdown("<font size=6.5><center>🌐💬 Aphra</center></font>")
gr.Markdown(
"""<div style="display: flex;align-items: center;justify-content: center">
[<a href="https://davidlms.github.io/aphra/">Project Page</a>] | [<a href="https://github.com/DavidLMS/aphra">Github</a>]</div>
"""
)
gr.Markdown("🌐💬 Aphra is an open-source translation agent designed to enhance the quality of text translations by leveraging large language models (LLMs).")
with gr.Row():
api_key = gr.Textbox(label="OpenRouter API Key", type="password")
writer_model = gr.Dropdown(
["anthropic/claude-3.5-sonnet:beta", "openai/gpt-4o-2024-08-06", "google/gemini-pro-1.5-exp"],
label="Writer Model",
value="anthropic/claude-3.5-sonnet:beta",
allow_custom_value=True
)
searcher_model = gr.Dropdown(
["perplexity/llama-3-sonar-large-32k-online", "perplexity/llama-3.1-sonar-huge-128k-online", "perplexity/llama-3.1-sonar-small-128k-online"],
label="Searcher Model",
value="perplexity/llama-3-sonar-large-32k-online",
allow_custom_value=True
)
critic_model = gr.Dropdown(
["anthropic/claude-3.5-sonnet:beta", "openai/gpt-4o-2024-08-06", "google/gemini-pro-1.5-exp"],
label="Critic Model",
value="anthropic/claude-3.5-sonnet:beta",
allow_custom_value=True
)
with gr.Row():
source_lang = gr.Dropdown(
["Spanish", "English", "French", "German"],
label="Source Language",
value="Spanish",
allow_custom_value=True
)
target_lang = gr.Dropdown(
["English", "Spanish", "French", "German"],
label="Target Language",
value="English",
allow_custom_value=True
)
with gr.Row():
file = gr.File(label="Upload .txt or .md file", file_types=[".txt", ".md"])
text_input = gr.Textbox(label="Or paste your text here", lines=5)
translate_btn = gr.Button("Translate with 🌐💬 Aphra")
output = gr.Textbox(label="Translation by 🌐💬 Aphra")
translate_btn.click(
process_input,
inputs=[file, text_input, api_key, writer_model, searcher_model, critic_model, source_lang, target_lang],
outputs=[output]
)
return demo
if __name__ == "__main__":
interface = create_interface()
interface.launch()
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