Forge (🔥)
A minimal-core, zero-magic, native async/streaming framework for LLM tools & agents.
Forge is built as a lightweight, transparent alternative to LangChain. Instead of deep nested wrappers, magic execution chains, and implicit retries, Forge provides a flat execution model: agent -> tool call -> result.
⚡ Key Features
- Flat Execution Model: Explicit, readable loops. Debugging is simple because there are no hidden layers.
- Typed Tool Schemas: Use Python function signatures + Pydantic for automated, clean JSON schema generation.
- Native Async & Streaming: Built from the ground up on async/await for fast, non-blocking execution.
- Built-in Local Tracing: Full visibility into exact request/response payloads without relying on external paid services.
- Zero Bloat: Lightweight dependencies. Optional provider packages (e.g.
anthropic).
🚀 Quickstart
import asyncio
from forge import Agent, tool, AnthropicProvider
@tool(description="Calculate the result of a mathematical expression")
def calculate(expression: str) -> str:
return str(eval(expression))
async def main():
provider = AnthropicProvider(model="claude-3-5-sonnet-20241022")
agent = Agent(
provider=provider,
tools=[calculate],
system_prompt="You are a helpful assistant.",
verbose=True,
)
history = await agent.run("What is 128 * 42?")
print("Answer:", history[-1].content)
if __name__ == "__main__":
asyncio.run(main())
🛠️ Testing & Development
Run unit tests via pytest:
pytest
1 maintainer
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