logosai-forge 0.2.11

AI Agent Generation Library — Agents Building Agents

logosai-forge

FORGE: An AI Agent Code Builder — agents that create, fix, and evolve other agents.

15 agentic AI agents collaborate to autonomously generate, improve, enhance, and self-evolve agent code.

Installation

pip install logosai-forge

Quick Start

import asyncio
from logosai_forge import ForgeClient

async def main():
    forge = ForgeClient()

    # Generate a new agent
    result = await forge.create_agent(
        "Calculate BMI from weight and height",
        test_cases=[{
            "input": {"weight_kg": 70, "height_m": 1.75},
            "expected": {"bmi": 22.9, "category": "normal"}
        }]
    )
    print(result.code)

    # Fix a broken agent
    result = await forge.improve_agent(agent_code, {
        "error_type": "logic_error",
        "error_message": "Condition is inverted — score>700 should approve",
        "test_input": {"credit_score": 750},
        "expected_output": {"decision": "approved"},
        "actual_output": {"decision": "denied"},
    })
    print(result.changes)

    # Add missing functions
    result = await forge.enhance_agent(
        existing_code,
        "Add multiply and divide methods"
    )
    print(result.added_functions)  # ['_multiply', '_divide']

asyncio.run(main())

Features

Method	Purpose	Example
create_agent()	Generate new agent from query	"Calculate shipping cost"
improve_agent()	Fix bugs from failure feedback	Inverted condition, wrong formula
enhance_agent()	Add missing logic/functions	"Add caching", "Add error handling"

ACP-Compliant Code Generation

Generated agents automatically follow the ACP Agent Interface Specification:

• process(query, context) with query str/dict normalization
• AgentResponse with content["answer"] (string)
• File creation agents return file_path + file_name
• Search agents return files list with absolute paths
• Uses python-pptx, openpyxl, subprocess (mdfind, pdfgrep) when appropriate

Function Slice Architecture

Agents are built by combining reusable function slices (174 slices), not writing entire code from scratch.

improve_agent() works at function granularity:

1. Extract functions (AST-based, handles any code structure)
2. StrategyAgent checks 174 slices — reuse if matched, LLM if not
3. Regenerate only the broken function
4. Replace in original code (other functions untouched)
5. ErrorHealerAgent heals syntax (3 experts)
6. Validate through multiple execution paths (best-match)
7. New LLM-generated functions auto-registered to slice library (Self-Growing)

Supports large agents (15KB+) with size-based strategy and dynamic timeouts.

Persistent Memory & Observability

• Learned patterns survive server restarts (SQLite-backed)
• All reasoning traces persisted and queryable (agent, time, success)
• Configuration via YAML (config/agentic_pipeline.yaml) + env var overrides
• Tool Registry for LLM/library dependency injection

Setup

Google API Key (required)

FORGE uses Gemini LLM for code generation. A Google API Key is required.

export GOOGLE_API_KEY="your-google-api-key-here"

Get your API key: https://aistudio.google.com/apikey

Requirements

• Python 3.10+
• Google API Key (GOOGLE_API_KEY environment variable)
• LogosAI framework (optional, for agent execution)

License

Source code will be open-sourced after paper publication. Part of the LogosAI ecosystem.