unclecode/promptuner

pip install git+https://github.com/unclecode/promptuner.git

export ANTHROPIC_API_KEY=YOUR_ANTHROPIC_API_KEY

from promptuner import Prompt
from promptuner.decorators import *
 
# Define the task
TASK = """Analyze the given email content and perform the following:
1. Classify the email into one of the provided class labels.
2. Score the email's importance on a scale of 1 to 10.
3. Provide a one-sentence summary of the email.
4. Extract the sender's email address.
Return the results in a JSON format."""

# Initialize a new Prompt
prompt = Prompt(TASK, variables=["EMAIL_CONTENT", "CLASS_LABELS"])
prompt.apply_decorator([
    Scratchpad(repeat=1),
    OutputExamples(repeat=1),
    ResultWrapper(repeat=1, tag="analysis"),
    JsonResponse()
])

# Train the prompt
prompt.train()

# Print the generated prompt template
print("Generated Prompt Template:")
print(prompt.content)
prompt.save("email_analysis_prompt.json")

# Sample email content
EMAIL_CONTENT = """
From: [email protected]
Subject: Urgent: Project Deadline Extension Request

Dear Team,

I hope this email finds you well. I'm writing to request an extension for the upcoming project deadline. Due to unforeseen circumstances, including a critical team member's illness and some technical challenges we've encountered, we're slightly behind schedule.

We've made significant progress, but we need an additional week to ensure we deliver a high-quality product. I believe this extension will allow us to address all remaining issues and exceed your expectations.

Please let me know if you need any further information or if you'd like to discuss this matter in more detail. I appreciate your understanding and look forward to your response.

Best regards,
John Doe
Project Manager
"""

prompt = Prompt.load("email_analysis_prompt.json")
# Define class labels
CLASS_LABELS = "Work-related, Personal, Spam, Urgent, Newsletter, Other"

# First Method: Use the generated prompt directly
import re
new_prompt = prompt.content.replace("{{EMAIL_CONTENT}}", EMAIL_CONTENT)
new_prompt = prompt.content.replace("{{CLASS_LABELS}}", CLASS_LABELS)
from openai import OpenAI
client = OpenAI()

completion = client.chat.completions.create(
  model="gpt-4o",
  messages=[
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": new_prompt}
  ]
)

answer = completion.choices[0].message
tag = "analysis"
pattern = f"<{tag}>(.*?)</{tag}>"
match = re.search(pattern, answer, re.DOTALL)
if match:
    result = match.group(1).strip()
print("\nEmail Analysis Results:")
print(result)

# Second Method: Use the promptuner library to execute the prompt
response = prompt(
    variable_values={
        "EMAIL_CONTENT": EMAIL_CONTENT,
        "CLASS_LABELS": CLASS_LABELS
    },
    model_name="ollama/phi3:latest"
    # model_name="claude-3-5-sonnet-20240620"
    # model_name="ollama/llama3"
    # model_name="ollama/qwen2:0.5b"
    # model_name="ollama/qwen2:1.5b"
)

print("\nEmail Analysis Results:")
print(response['answer'])

print("\nTags:")
for tag, content in response['tags'].items():
    if tag != "analysis":
        print(f"<{tag}>\n{content}\n</{tag}>")