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_(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`
Building the AutoGen Documentation
AutoGen documentation is based on the sphinx documentation system and uses the myst-parser to render markdown files. It uses the pydata-sphinx-theme to style the documentation.
Prerequisites
Ensure you have all of the dev dependencies for the autogen-core package installed. You can install them by running the following command from the root of the python repository:
uv sync
source .venv/bin/activate
Building Docs
To build the documentation, run the following command from the root of the python repository:
poe --directory ./packages/autogen-core/ docs-build
To serve the documentation locally, run the following command from the root of the python repository:
poe --directory ./packages/autogen-core/ docs-serve
[!NOTE]
Sphinx will only rebuild files that have changed since the last build. If you want to force a full rebuild, you can delete the ./packages/autogen-core/docs/build directory before running the docs-build command.
Versioning the Documentation
The current theme - pydata-sphinx-theme - supports switching between versions of the documentation.
To version the documentation, you need to create a new version of the documentation by copying the existing documentation to a new directory with the version number. For example, to create a new version of the documentation for version 0.1.0, you would run the following command:
How are various versions built? - TBD.