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import os
import gradio as gr
import asyncio
import pandas as pd
from datetime import datetime
from langchain.schema.output_parser import StrOutputParser
from langchain.chat_models import ChatOpenAI
from langchain.prompts.chat import (
ChatPromptTemplate,
HumanMessagePromptTemplate,
SystemMessagePromptTemplate,
)
# Load OpenAI model with API key
openai_key = os.getenv('OPENAI_API_KEY')
model = ChatOpenAI(model_name="gpt-4-0125-preview", temperature=0.4)
# System prompt templates
raft_base_template = os.getenv('RAFT_BASE_TEMPLATE')
raft_base_template_v2 = os.getenv('RAFT_BASE_TEMPLATE_V2')
raft_metaprompt_template = os.getenv('RAFT_METAPROMPT_TEMPLATE')
raft_metaprompt_template_v2 = os.getenv('RAFT_METAPROMPT_TEMPLATE_2')
# System prompt template
customer_template = os.getenv('CUSTOMER_TEMPLATE')
# Initialize DataFrame
results_df = pd.DataFrame(columns=['Experiment Number','Temperature', 'PromptID','Business Idea', 'Generated Domains'])
def extract_content_inside_brackets(json_string):
# Находим позицию первой открывающей и последней закрывающей скобки
start = json_string.find('[')
end = json_string.find(']', start)
# Если скобки найдены, извлекаем содержимое между ними
if start != -1 and end != -1:
content_inside_brackets = json_string[start+1:end]
return content_inside_brackets
else:
# Возвращаем None, если скобки не найдены
return None
list_of_prompts = ['customer_template', 'raft_base_template', 'raft_metaprompt_template', 'raft_base_template_v2', 'raft_metaprompt_template_v2']
# Function to generate domain names based on different templates
async def generate_domain_names(business_idea, temperature):
model.temperature = temperature # Update model temperature
prompts = [customer_template, raft_base_template, raft_metaprompt_template, raft_base_template_v2, raft_metaprompt_template_v2]
tasks = []
for prompt in prompts:
system_message_prompt = SystemMessagePromptTemplate.from_template(prompt)
human_message_prompt = HumanMessagePromptTemplate.from_template("User's input: ~###~ {user_input}~###~,")
combined_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
json_chain = combined_prompt | model | StrOutputParser() | extract_content_inside_brackets
task = asyncio.to_thread(json_chain.invoke, {"user_input": business_idea})
tasks.append(task)
domains = await asyncio.gather(*tasks)
# Update DataFrame and save to JSON
experiment_number = datetime.now().strftime("%Y%m%d%H%M%S")
for i, domain in enumerate(domains):
new_row = {
'Experiment Number': experiment_number,
'Business Idea': business_idea,
'Temperature': temperature,
'PromptID': list_of_prompts[i],
'Generated Domains': domain
}
global results_df
results_df = pd.concat([results_df, pd.DataFrame([new_row])], ignore_index=True)
save_to_json(results_df)
return domains
# Function to save DataFrame to JSON
def save_to_json(df):
json_path = 'domain_name_generation_results.json'
df.to_json(json_path, orient='records', lines=True)
# Function to download the DataFrame as an Excel file
def download_excel():
df = pd.read_json('domain_name_generation_results.json', lines=True)
excel_path = 'domain_name_generation_results.xlsx'
df.to_excel(excel_path, index=False)
return excel_path
# Setup Gradio interface
def setup_interface():
with gr.Blocks() as iface:
with gr.Row():
text_input = gr.Textbox(label="Enter your business idea", placeholder="Type here...", lines=2)
temperature_slider = gr.Slider(minimum=0, maximum=1, step=0.01, label="Set Temperature")
submit_button = gr.Button("Generate")
with gr.Row():
output1 = gr.Textbox(label="Output for Customer Template")
output2 = gr.Textbox(label="Output for Base Raft Template")
output3 = gr.Textbox(label="Output for MetaPrompt Raft Template")
output4 = gr.Textbox(label="Output for Base Raft Template (Новые домены после точки)")
output5 = gr.Textbox(label="Output for MetaPrompt Raft Template (Новые домены после точки)")
with gr.Row():
download_btn = gr.Button("Download Excel")
submit_button.click(
fn=generate_domain_names,
inputs=[text_input, temperature_slider],
outputs=[output1, output2, output3, output4, output5]
)
download_btn.click(
fn=download_excel,
inputs=None,
outputs=gr.File(label="Download Excel")
)
return iface
iface = setup_interface()
iface.launch()
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