| import ast
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| import json
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| import random
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| import time
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|
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| import names
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| from google import genai
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| client = genai.Client(
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| api_key="API"
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| )
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| MODELS = [
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| "gemini-3.6-flash",
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| "gemini-3.5-flash",
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| "gemini-3.1-flash-lite",
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| "gemini-3.5-flash-lite",
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| "gemini-2.5-flash",
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| "gemini-2.5-flash-lite",
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| "gemini-3.1-flash-lite-preview",
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| "gemini-2.5-pro",
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| "gemini-3.1-pro-preview",
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| "gemini-3-pro-preview",
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| "gemini-pro-latest",
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| "gemini-flash-latest"
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| ]
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|
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| current_model = 0
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| generation_config = {
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| "max_output_tokens": 65536,
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| "thinking_level": "medium",
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| "temperature": 1.2,
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| }
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| with open("EmailPrompt.txt", "r", encoding="utf-8") as f:
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| inst = f.read().strip()
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| with open("Topics.txt", "r", encoding="utf-8") as f:
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| topics = ast.literal_eval(f.read())
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| def generate_person_name(role):
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| """
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| Generates names with occasional titles.
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| Recipients are more likely to have titles because
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| professional emails often address people formally.
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| """
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| name = names.get_full_name()
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| if role == "recipient":
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| title_chance = 0.35
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| else:
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| title_chance = 0.10
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| if random.random() < title_chance:
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| title = random.choice([
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| "Mr.",
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| "Mrs.",
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| "Ms.",
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| "Dr.",
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| "Prof."
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| ])
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| return f"{title} {name}"
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| return name
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| def create_email_prompt(topic):
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| sender = generate_person_name("sender")
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| recipient = generate_person_name("recipient")
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| templates = [
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| f"Write an email about {topic}.",
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| f"Create an email from {sender} to {recipient} about {topic}.",
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| f"Write an email from {sender} explaining {topic} to {recipient}.",
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| f"Write an email to {recipient} regarding {topic}.",
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| f"Write an email where {sender} needs to discuss {topic} with {recipient}.",
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| f"Generate a professional email from {sender} concerning {topic}.",
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| f"Write an email from {sender} requesting something related to {topic}.",
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| f"Create an email that {sender} would send to {recipient} about {topic}.",
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| f"Write an email addressed to {recipient} explaining the situation involving {topic}.",
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| f"Generate a workplace-style email from {sender} about {topic}.",
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| f"Write an email where an employee contacts {recipient} about {topic}.",
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| f"Write an email where I need to communicate {topic} to someone important.",
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| f"Create a formal email discussing {topic}.",
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| f"Write a message that could be sent to a supervisor about {topic}.",
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| f"Write an email from a person named {sender} about {topic}."
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| ]
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| return random.choice(templates)
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| with open("terrible_emails_dataset.jsonl", "w", encoding="utf-8") as outfile:
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| for topic in topics:
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| prompt = create_email_prompt(topic)
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| print(
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| f"[{MODELS[current_model]}] Generating: {topic}"
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| )
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|
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| while True:
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| try:
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| interaction = client.interactions.create(
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| model=MODELS[current_model],
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| input=prompt,
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| system_instruction=inst,
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| generation_config=generation_config,
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| )
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| assistant_response = interaction.output_text
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| break
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|
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| except Exception as e:
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| error = str(e)
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| error_lower = error.lower()
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| print(error)
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| if any(x in error_lower for x in (
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| "resource_exhausted",
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| "quota",
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| "daily limit",
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| "per day",
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| "429",
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| "rate limit",
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| )):
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| if current_model < len(MODELS) - 1:
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| current_model += 1
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| print(
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| f"Switching to {MODELS[current_model]}"
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| )
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| continue
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| raise RuntimeError(
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| "All models exhausted quota."
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| )
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| if any(x in error_lower for x in (
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| "500",
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| "502",
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| "503",
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| "504",
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| "internal",
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| "timeout",
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| "connection",
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| "unavailable",
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| )):
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| print(
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| "Temporary error. Retrying in 15 seconds..."
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| )
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| time.sleep(15)
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| continue
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| raise
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|
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| dataset_entry = {
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| "messages": [
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| {
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| "role": "user",
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| "content": prompt,
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| },
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| {
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| "role": "assistant",
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| "content": assistant_response,
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| },
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| ]
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| }
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| outfile.write(
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| json.dumps(
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| dataset_entry,
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| ensure_ascii=False
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| )
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| )
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|
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| outfile.write("\n")
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| outfile.flush()
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| print("Done!") |
