src/prompts.py

"""Prompt templates and management for AI model interactions."""

from datetime import datetime
from src.constants import logger

# System message template that defines AI assistant behavior and rules
system_message = """
You are a helpful assistant whose main purpose is to generate synthetic datasets
based on a given business problem.

🔹 General Guidelines:
- Be accurate and concise.
- Use only standard Python libraries (pandas, numpy, os, datetime, etc.)
- The dataset must contain the requested number of samples.
- Always respect the requested output format exactly.
- If multiple entities exist, save each to a separate file.
- Do not use f-strings anywhere in the code — not in file paths or in content.
  Use standard string concatenation instead.

🔹 File Path Rules:
- Define the full file path using os.path.join(...) — exactly as shown —
  no shortcuts or direct strings.
  - Use two hardcoded string literals only — no variables, no f-strings,
    no formatting, no expressions.
  - First argument: full directory path (use forward slashes).
  - Second argument: full filename with timestamp and correct extension.
  - Example: os.path.join("C:/Users/.../output", "sales_20250323_123456.json")
- ⚠️ Do not use intermediate variables like directory, filename, or output_dir.
- ⚠️ Do not skip or replace any of the above instructions. They are required
  for the code to work correctly.

🔹 File Saving Instructions:

- ✅ CSV:
    df.to_csv(file_path, index=False, encoding="utf-8")

- ✅ JSON:
    with open(file_path, "w", encoding="utf-8") as f:
        df.to_json(f, orient="records", lines=False, force_ascii=False, indent=2)

- ✅ Parquet:
    df.to_parquet(file_path, engine="pyarrow", index=False)

- ✅ Markdown (for Text):
    - Generate properly formatted Markdown content.
    - Save it as a `.md` file using UTF-8 encoding.
"""


def build_user_prompt(**input_data):
    """Build user prompt for AI model based on dataset generation parameters."""
    try:
        # Normalize file path separators to forward slashes for consistency
        file_path = input_data["file_path"].replace("\\", "/")

        # Generate timestamp for unique file naming
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")

        # Construct the user prompt for the LLM with all required parameters
        user_prompt = (
            f"Generate a synthetic {input_data['dataset_type'].lower()} "
            f"dataset in {input_data['output_format'].upper()} format.\n"
            f"Business problem: {input_data['business_problem']}\n"
            f"Samples: {input_data['num_samples']}\n"
            f"Directory: {file_path}\n"
            f"Timestamp: {timestamp}"
        )

        return user_prompt

    except KeyError as e:
        # Handle missing keys in input_data dictionary
        logger.warning(f"Missing input key: {e}")
        raise
    except Exception as e:
        # Log any other error during prompt building process
        logger.warning(f"Error in build_user_prompt: {e}")
        raise