Generating files from default preprocessed prompt name fails: could not determine language #8
Description
The default file name for preprocessing does not make sense <basename>_<language>_preprocessed.prompt because when generating this preprocessed file it is unable to automatically detect the language.
Reproduction
- Create a mock python file in
config_example.py, e.g.:
from fastapi import FastAPI
from app.config import create_settings
def create_app() -> FastAPI:
"""
Creates and configures the FastAPI application using environment-based settings.
Returns:
FastAPI: Configured FastAPI application instance.
"""
app = FastAPI(
title=settings.PROJECT_NAME,
version=settings.VERSION
)
# Example usage of settings
print("JWT Secret Key:", settings.JWT_SECRET_KEY)
print("Allowed CORS Origins:", settings.CORS_ORIGINS)
print("Token Expiry (minutes):", settings.ACCESS_TOKEN_EXPIRE_MINUTES)
print("Rate Limit:", settings.RATE_LIMIT_PER_MINUTE)
print("Log Level:", settings.LOG_LEVEL)
@app.get("/health")
def health_check() -> dict[str, str]:
"""
Health check endpoint.
Returns:
dict: Application name and version.
"""
return {
"project": settings.PROJECT_NAME,
"version": settings.VERSION
}
return app
settings = create_settings(env_file="example.env")
app = create_app()- Create prompt in
src/app/config_python.promptwith a value that requires preprocessing:
Create a configuration module that handles all application settings using Pydantic's BaseSettings.
It is located under app/config.py.
Requirements:
1. Settings Class:
- Create a Settings class that inherits from BaseSettings
- Use environment variables for all configuration
- Include type hints for all settings
2. Required Settings:
- PROJECT_NAME: Name of the project (used in FastAPI title)
- VERSION: Current version of the application (used in FastAPI and health check)
- JWT_SECRET_KEY: Secret key for JWT token generation
- JWT_ALGORITHM: Algorithm for JWT (default to "HS256")
- ACCESS_TOKEN_EXPIRE_MINUTES: Token expiration time
- CORS_ORIGINS: List of allowed CORS origins
- RATE_LIMIT_PER_MINUTE: Rate limit for authentication endpoints
- LOG_LEVEL: Application logging level
3. Environment Variables:
- All settings should be configurable via environment variables
- Use .env file for local development
- Include example .env file in documentation
- Default values should be provided where appropriate
4. Validation:
- Add validation for required settings
- Include reasonable defaults where appropriate
- Add validation for CORS origins format
- Validate JWT secret key length
- Validate version format (semantic versioning)
- Validate project name format
5. Documentation:
- Add docstrings for the Settings class
- Document each setting with its purpose and format
- Include example usage
- Document environment variable names
- Include example .env file
The module should be importable as 'config' and expose a 'settings' instance that can be used
throughout the application.
Example usage:
from config import settings
# Access settings
jwt_secret = settings.JWT_SECRET_KEY
cors_origins = settings.CORS_ORIGINS
project_name = settings.PROJECT_NAME
version = settings.VERSION
Example .env file:
PROJECT_NAME=pdd
VERSION=0.1.0
JWT_SECRET_KEY=your-secret-key-here
JWT_ALGORITHM=HS256
ACCESS_TOKEN_EXPIRE_MINUTES=30
CORS_ORIGINS=["http://localhost:3000"]
RATE_LIMIT_PER_MINUTE=60
LOG_LEVEL=INFO
Make sure the code is executable via a unit test settings without side effects.
e.g. the following example should be executable without any side effects required.
<include>config_example.py</include>
Specifically, the `.env` file will not be available when executing the example. Adjust the interface so you can construct a new working example which will not require any side effects.
Please generate the complete config.py implementation following these requirements.
- Run
pdd --local preprocess config_change_python.prompt. This createsconfig_python_preprocessed.prompt. - Run pdd --local generate config_python_preprocessed.prompt
Expected output
The config.py should be generated using the preprocessed prompt given.
Actual output
Error:
Could not determine language from input files or options.
Error during path construction: Could not determine language from input files or options.
Suggested Fix
If the prompt file ends with _preprocessed then you ignore that substring and try to read the language from the preceding substring.
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