prompting-forge 0.1.0

A lightweight, modular library for building, composing, and managing structured prompts for LLMs

prompting-forge

Minimal, focused prompting library for the Tool-Forge ecosystem.

This package provides the core prompt primitives only:

• PromptTemplate: define structured prompts with {variables}
• ChatPrompt: rendered prompt as messages (system + user)

All LLM execution, chaining, and parsing utilities live in genai-forge.

Install

pip install prompting-forge

For chaining (query | template | llm | parser) and model calls:

pip install genai-forge

Python 3.10+.

Quickstart (with genai-forge)

from prompting_forge.prompting import PromptTemplate
from genai_forge import create_llm, PydanticOutputParser
from pydantic import BaseModel

class CityPlan(BaseModel):
    city: str
    attractions: list[str]
    days: int

template = PromptTemplate(
    system="You are a concise assistant.",
    template="Create a weekend plan.\nCity: {city}",
)

llm = create_llm("openai:gpt-4o-mini", temperature=0.2)
parser = PydanticOutputParser(CityPlan)

query = "Generate a simple weekend plan for a city."
chain = query | template | llm | parser
plan = chain({"city": "Lisbon"})
print(plan)

Notes

• PromptTemplate uses Python str.format. Missing variables raise clear errors.
• When used with genai-forge, parser instructions can be appended automatically.
• The pipe operators on PromptTemplate are enabled via a lazy import of genai_forge.chain. If you don’t install genai-forge, you can still call template.format(...) manually and pass the result to your own client.