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AI Agent Framework

$29

Python framework for building AI agents with tool use, planning loops, memory, and multi-step reasoning.

📁 11 files
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📁 File Structure 11 files

ai-agent-framework/ ├── LICENSE ├── README.md ├── examples/ │ ├── basic_usage.py │ └── custom_tools.json ├── free-sample.zip ├── guide/ │ ├── 01_features.md │ ├── 02_project-structure.md │ ├── 03_usage-examples.md │ └── 04_license.md ├── index.html └── src/ └── ai_agent_framework.py

📖 Documentation Preview README excerpt

AI Agent Framework

Python framework for building AI agents with tool use, planning loops, memory management, multi-step reasoning, and structured output parsing. Zero dependencies.

Part of the AI Toolkit collection by [CodeVault](https://ai-toolkit.codevault.dev).

Features

  • ReAct loop — Thought → Action → Observation reasoning loop (same pattern as LangChain/AutoGPT)
  • Tool system — Register custom tools with parameter schemas and callable functions
  • Memory manager — Sliding-window context management with intelligent trimming
  • Output parser — Parses structured Thought/Action/Final Answer format from LLM responses
  • Built-in tools — Search, calculator, and JSON formatter included as examples
  • LLM-agnostic — Abstract LLMInterface — wire to OpenAI, Anthropic, or any API
  • Safety limits — Configurable max_steps prevents infinite loops
  • Full trace — Every step recorded with thought, action, observation
  • Config export — Export agent configuration as JSON

Quick Start


# Run the demo with a simulated agent
python src/ai_agent_framework.py --demo

# List all registered tools
python src/ai_agent_framework.py --list-tools

# Export agent config
python src/ai_agent_framework.py --export-config my_agent.json

# Run agent on a task (uses simulated LLM)
python src/ai_agent_framework.py --task "What is the population of Helsinki?"

Project Structure


ai-agent-framework/
├── README.md
├── LICENSE
├── src/
│   └── ai_agent_framework.py    # Core engine (~420 lines)
└── examples/
    ├── basic_usage.py             # Build a custom agent
    └── custom_tools.json          # Tool definition examples

CLI Reference

FlagDescription
--demoRun simulated agent demo
--list-toolsList all registered tools
--export-config FILEExport agent config to JSON
--task TEXTRun agent on a task (simulated LLM)

Usage Examples

Wire to a Real LLM

... continues with setup instructions, usage examples, and more.

📄 Code Sample .py preview

examples/basic_usage.py#!/usr/bin/env python3 """ Basic usage example for the AI Agent Framework. Demonstrates: - Running the built-in demo agent - Registering custom tools - Inspecting the agent's reasoning trace - Exporting agent configuration - Using the MemoryManager and OutputParser directly """ import json import sys from pathlib import Path # Allow running from the examples/ directory sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src")) from ai_agent_framework import ( Agent, AgentState, MemoryManager, MemoryType, OutputParser, SimulatedLLM, ToolDefinition, ) def demo_basic_agent() -> None: """Run the default agent with the simulated LLM.""" print("=== Basic Agent Run ===\n") agent = Agent(name="DemoAgent") result = agent.run("What is the population of Helsinki?") print(f" Success: {result.success}") print(f" Steps: {result.total_steps}") print(f" Time: {result.elapsed_seconds}s") print(f" Answer: {result.answer[:100]}...") print()
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