AI Agent Generation Library — Agents Building Agents
Project description
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 normalizationAgentResponsewithcontent["answer"](string)- File creation agents return
file_path+file_name - Search agents return
fileslist 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:
- Extract functions (AST-based, handles any code structure)
- StrategyAgent checks 174 slices — reuse if matched, LLM if not
- Regenerate only the broken function
- Replace in original code (other functions untouched)
- ErrorHealerAgent heals syntax (3 experts)
- Validate through multiple execution paths (best-match)
- New LLM-generated functions auto-registered to slice library (Self-Growing)
Supports large agents (15KB+) with size-based strategy and dynamic timeouts.
Domain Expert Review (v0.2.12)
Pipeline Stage 6.5 — after code assembly, a dynamically created domain expert reviews the generated code:
- Automatic domain detection (finance, healthcare, legal, etc.)
- Confidence gate: low confidence → expert feedback injected into retry loop
- Enable/disable via YAML config (
domain_review.enabled)
Function Intelligence
- Telemetry: per-function call count, success rate, error types (SQLite)
- Version Management: auto-increment versions, quality comparison, rollback
- Composition Learning: tracks which functions work well together (function pairs)
- Pattern-Based Generation: successful functions as reference for new domains
- Quality Gate: success rate < 0.70 → blocked from library admission
- Function Graph: unified ontology connecting templates, pairs, metrics, and type compatibility
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
- Context Manager for priority-based LLM token fitting
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_KEYenvironment variable) - LogosAI framework (optional, for agent execution)
License
Source code will be open-sourced after paper publication. Part of the LogosAI ecosystem.
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