0d9b574d09
# Azure AI Search Tool Implementation
This PR adds a new tool for Azure AI Search integration to autogen-ext,
enabling agents to search and retrieve information from Azure AI Search
indexes.
## Why Are These Changes Needed?
AutoGen currently lacks native integration with Azure AI Search, which
is a powerful enterprise search service that supports semantic, vector,
and hybrid search capabilities. This integration enables agents to:
1. Retrieve relevant information from large document collections
2. Perform semantic search with AI-powered ranking
3. Execute vector similarity search using embeddings
4. Combine text and vector approaches for optimal results
This tool complements existing retrieval capabilities and provides a
seamless way to integrate with Azure's search infrastructure.
## Features
- **Multiple Search Types**: Support for text, semantic, vector, and
hybrid search
- **Flexible Configuration**: Customizable search parameters and fields
- **Robust Error Handling**: User-friendly error messages with
actionable guidance
- **Performance Optimizations**: Configurable caching and retry
mechanisms
- **Vector Search Support**: Built-in embedding generation with
extensibility
## Usage Example
```python
from autogen_ext.tools.azure import AzureAISearchTool
from azure.core.credentials import AzureKeyCredential
from autogen import AssistantAgent, UserProxyAgent
# Create the search tool
search_tool = AzureAISearchTool.load_component({
"provider": "autogen_ext.tools.azure.AzureAISearchTool",
"config": {
"name": "DocumentSearch",
"description": "Search for information in the knowledge base",
"endpoint": "https://your-service.search.windows.net",
"index_name": "your-index",
"credential": {"api_key": "your-api-key"},
"query_type": "semantic",
"semantic_config_name": "default"
}
})
# Create an agent with the search tool
assistant = AssistantAgent(
"assistant",
llm_config={"tools": [search_tool]}
)
# Create a user proxy agent
user_proxy = UserProxyAgent(
"user_proxy",
human_input_mode="TERMINATE",
max_consecutive_auto_reply=10,
code_execution_config={"work_dir": "coding"}
)
# Start the conversation
user_proxy.initiate_chat(
assistant,
message="What information do we have about quantum computing in our knowledge base?"
)
```
## Testing
- Added unit tests for all search types (text, semantic, vector, hybrid)
- Added tests for error handling and cancellation
- All tests pass locally
## Documentation
- Added comprehensive docstrings with examples
- Included warnings about placeholder embedding implementation
- Added links to Azure AI Search documentation
## Related issue number
Closes #5419
## Checks
- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.
---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
|
||
|---|---|---|
| .. | ||
| packages | ||
| samples | ||
| templates/new-package | ||
| .gitignore | ||
| README.md | ||
| check_md_code_blocks.py | ||
| fixup_generated_files.py | ||
| pyproject.toml | ||
| run_task_in_pkgs_if_exist.py | ||
| shared_tasks.toml | ||
| uv.lock | ||
README.md
AutoGen Python packages
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-extraswill create a.venvdirectory at the current level and install packages from the current directory along with any other dependencies. Theall-extrasflag adds optional dependencies.source .venv/bin/activateactivates 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-checkAlternatively, 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/