Ricky Loynd 97536af7a3
Task-Centric Memory (#5227)
_(EXPERIMENTAL, RESEARCH IN PROGRESS)_

In 2023 AutoGen introduced [Teachable
Agents](https://microsoft.github.io/autogen/0.2/blog/2023/10/26/TeachableAgent/)
that users could teach new facts, preferences and skills. But teachable
agents were limited in several ways: They could only be
`ConversableAgent` subclasses, they couldn't learn a new skill unless
the user stated (in a single turn) both the task and how to solve it,
and they couldn't learn on their own. **Task-Centric Memory** overcomes
these limitations, allowing users to teach arbitrary agents (or teams)
more flexibly and reliably, and enabling agents to learn from their own
trial-and-error experiences.

This PR is large and complex. All of the files are new, and most of the
added components depend on the others to run at all. But the review
process can be accelerated if approached in the following order.
1. Start with the [Task-Centric Memory
README](https://github.com/microsoft/autogen/tree/agentic_memory/python/packages/autogen-ext/src/autogen_ext/task_centric_memory).
1. Install the memory extension locally, since it won't be in pypi until
it's merged. In the `agentic_memory` branch, and the `python/packages`
directory:
        - `pip install -e autogen-agentchat`
        - `pip install -e autogen-ext[openai]`
        - `pip install -e autogen-ext[task-centric-memory]`
2. Run the Quickstart sample code, then immediately open the
`./pagelogs/quick/0 Call Tree.html` file in a browser to view the work
in progress.
    3. Click through the web page links to see the details.
2. Continue through the rest of the main README to get a high-level
overview of the architecture.
3. Read through the [code samples
README](https://github.com/microsoft/autogen/tree/agentic_memory/python/samples/task_centric_memory),
running each of the 4 code samples while viewing their page logs.
4. Skim through the 4 code samples, along with their corresponding yaml
config files:
    1. `chat_with_teachable_agent.py`
    2. `eval_retrieval.py`
    3. `eval_teachability.py`
    4. `eval_learning_from_demonstration.py`
    5. `eval_self_teaching.py`
6. Read `task_centric_memory_controller.py`, referring back to the
previously generated page logs as needed. This is the most important and
complex file in the PR.
7. Read the remaining core files.
    1. `_task_centric_memory_bank.py`
    2. `_string_similarity_map.py`
    3. `_prompter.py`
8. Read the supporting files in the utils dir.
    1. `teachability.py`
    2. `apprentice.py`
    3. `grader.py`
    4. `page_logger.py`
    5. `_functions.py`
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..
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AutoGen Python packages

0.4 Docs PyPi autogen-core PyPi autogen-agentchat PyPi autogen-ext

This directory works as a single uv workspace containing all project packages. See packages to discover all project packages.

Migrating from 0.2.x?

Please refer to the migration guide for how to migrate your code from 0.2.x to 0.4.x.

Development

TL;DR, run all checks with:

uv sync --all-extras
source .venv/bin/activate
poe check

Setup

uv is a package manager that assists in creating the necessary environment and installing packages to run AutoGen.

Note: To prevent incompatibilities between versions the same UV version as is running in CI should be used. Check the version in CI by looking the setup-uv action, here for example.

For example, to change your version to 0.5.18, run:

uv self update 0.5.18

Virtual Environment

During development, you may need to test changes made to any of the packages.
To do so, create a virtual environment where the AutoGen packages are installed based on the current state of the directory.
Run the following commands at the root level of the Python directory:

uv sync --all-extras
source .venv/bin/activate
  • uv sync --all-extras will create a .venv directory at the current level and install packages from the current directory along with any other dependencies. The all-extras flag adds optional dependencies.
  • source .venv/bin/activate activates the virtual environment.

Common Tasks

To create a pull request (PR), ensure the following checks are met. You can run each check individually:

  • Format: poe format
  • Lint: poe lint
  • Test: poe test
  • Mypy: poe mypy
  • Pyright: poe pyright
  • Build docs: poe --directory ./packages/autogen-core/ docs-build
  • Auto rebuild+serve docs: poe --directory ./packages/autogen-core/ docs-serve
  • Check samples in python/samples: poe samples-code-check Alternatively, you can run all the checks with:
  • poe check

Note

These need to be run in the virtual environment.

Syncing Dependencies

When you pull new changes, you may need to update the dependencies. To do so, first make sure you are in the virtual environment, and then in the python directory, run:

uv sync --all-extras

This will update the dependencies in the virtual environment.

Creating a New Package

To create a new package, similar to autogen-core or autogen-chat, use the following:

uv sync --python 3.12
source .venv/bin/activate
cookiecutter ./templates/new-package/