70 lines
2.2 KiB
Markdown
70 lines
2.2 KiB
Markdown
# agent-harness
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Companion code for the [ruxu.dev](https://www.ruxu.dev) blog post series on building a simple AI agent harness from scratch.
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## Blog Post Series
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1. [Build a Basic AI Agent](https://www.ruxu.dev/articles/ai/build-a-basic-ai-agent/): A minimal conversational agent with a message loop, powered by a local model via Ollama.
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2. [Build an AI Agent with Tools](https://www.ruxu.dev/articles/ai/build-an-ai-agent-with-tools/): Extends the agent with a tool registry so the LLM can read/write files, search the filesystem, run shell commands, and fetch web pages.
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3. `agent-memory/`: Adds durable agent and user memory plus searchable, resumable sessions to the sandboxed agent.
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## Structure
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```
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simple-agent/ # Part 1: bare-bones agent loop
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agent.py
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agent-with-tools/ # Part 2: agent with tool-calling support
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agent.py
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tools/
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filesystem.py # read, write, search files
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shell.py # run shell commands
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web.py # fetch web pages
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registry.py # tool registry & schemas
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agent-memory/ # Persistent memory and session continuation
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agent.py
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memory.py # File-backed notes and conversation sessions
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```
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## Requirements
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- Python 3.12+
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- [uv](https://github.com/astral-sh/uv) (recommended) or pip
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## Setup
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```bash
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uv sync
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```
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You can also change the current Ollama agent running gemma4 for any model of your choice.
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### simple-agent
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```bash
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uv run simple-agent/agent.py
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```
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### agent-with-tools
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```bash
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uv run agent-with-tools/agent.py
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```
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Type `\exit` to quit either agent.
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### agent-memory
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```bash
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uv run agent-memory/agent.py
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```
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Memory is stored outside the repository by default in `~/.agent-harness/memory`:
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- The agent reads and appends durable `personal` notes (lessons and environment facts) and `user` notes (preferences) through host-side memory tools.
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- Each conversation is saved as a transcript and should receive an LLM-written summary; a fallback summary is generated on exit if needed.
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- Type `\sessions` during a conversation, or run `uv run agent-memory/agent.py --list-sessions`, to list saved sessions.
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- Resume a conversation with `uv run agent-memory/agent.py --resume SESSION_ID`.
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- Change the storage location with `--memory-dir PATH`.
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