* Migrate to uv and poe for workspace management and task running
* install python
* try fix
* ensure workspace venv in used
* package dir
* move nbqa to mypy task
* separate sync, clarify docs
* intial commit for aws-bedrock
* format
* converse setup for model req-response
* Renamed to bedrock.py, updated parameter parsing, system message extraction, client class incorporation
* Established Bedrock class based on @astroalek and @ChristianT's code, added ability to disable system prompt separation
* Image parsing and removing access credential checks
* Added tests, added additional parameter support
* Amazon Bedrock documentation
* Moved client parameters to init, align parameter names with Anthropic, spelling fix, remove unnecessary imports, use base and additional parameters, update documentation
* Tidy up comments
* Minor typo fix
* Correct comment re aws_region
---------
Co-authored-by: Mark Sze <mark@sze.family>
Co-authored-by: Mark Sze <66362098+marklysze@users.noreply.github.com>
Co-authored-by: Li Jiang <bnujli@gmail.com>
* +mdb atlas
* Update test/agentchat/contrib/vectordb/test_mongodb.py
Co-authored-by: HRUSHIKESH DOKALA <96101829+Hk669@users.noreply.github.com>
* update test_mongodb.py; we dont need to do the assert .collection_name vs .name
* Try fix mongodb service
* Try fix mongodb service
* Update username and password
* Update autogen/agentchat/contrib/vectordb/mongodb.py
* closer --- but im not super thrilled about the solution...
* PYTHON-4506 Expanded tests and simplified vector search pipelines
* Update mongodb.py
* Update mongodb.py - Casey
* search_index_magic
index_name change; keeping track of lucene indexes is tricky
* Fix format
* Fix tests
* hacking trying to figure this out
* Streamline checks for indexes in construction and restructure tests
* Add tests for score_threshold, embedding inclusion, and multiple query tests
* refactored create_collection to meet base object requirements
* lint
* change the localhost port to 27017
* add test to check that no embedding is there unless explicitly provided
* Update logger
* Add test get docs with ids=None
* Rename and update notebook
* have index management include waiting behaviors
* Adds further optional waits or users and tests. Cleans up upsert.
* ensure the embedding size for multiple embedding inputs is equal to dimensions
* fix up tests and add configuration to ensure documents and indexes are READY for querying
* fix import failure
* adjust typing for 3.9
* fix up the notebook output
* changed language to communicate time taken on first init_chat call
* replace environment variable usage
---------
Co-authored-by: Fabian Valle <fabian.valle-simmons@mongodb.com>
Co-authored-by: HRUSHIKESH DOKALA <96101829+Hk669@users.noreply.github.com>
Co-authored-by: Li Jiang <bnujli@gmail.com>
Co-authored-by: Casey Clements <casey.clements@mongodb.com>
Co-authored-by: Jib <jib.adegunloye@mongodb.com>
Co-authored-by: Jib <Jibzade@gmail.com>
Co-authored-by: Cozypet <yanhan860711@gmail.com>
* basic CI WIP
* change authors to Microsoft
* add Aspire workload
* artificial commit to trigger workflow
* only publish packages if on main branch
* comment out the publishing jobs
* Remove publish from main dotnet CI workflow
* Initial check-in of agbench
* Moved agbench to intended directory.
* Removed pyautogen dependency
* moved to using process_until_idle
* Added TeamOne template.
* User TeamOne agent classes.
* migrate to hatch, move benchmarks out, add CI (#166)
* Resolve type issues (#168)
Thanks for fixing types.
* Fixed import.
---------
Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
* Groq Client Class - main class and setup, except tests
* Change pricing per K, added tests
* Streaming support, including with tool calling
* Used Groq retries instead of loop, thanks Gal-Gilor!
* Fixed bug when using logging.
---------
Co-authored-by: Qingyun Wu <qingyun0327@gmail.com>
* First pass together.ai client class
* Config handling, models and cost
* Added tests, moved param management to create function
* Tests, parameter, validation, logging updates
* Added use of client_utils PR 2949
* Updated to return OAI response
* Notebook example
* Improved function calling, updated tests, updated notebook with Chess example
* Tidied up together client class, better parameter handling, simpler exception capture, warning for no cost, reuse in tests, cleaner tests
* Update of documentation notebook, replacement of old version
* Fix of messages parameter for hide_tools function call
* Update autogen/oai/together.py
Co-authored-by: Qingyun Wu <qingyun0327@gmail.com>
* Update together.py to fix text
---------
Co-authored-by: Qingyun Wu <qingyun0327@gmail.com>
Co-authored-by: Yiran Wu <32823396+yiranwu0@users.noreply.github.com>
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
* Initial commit of Mistral client class
* Updated to manage final system message for reflection_with_llm
* Add Mistral support to client class
* Add Mistral support across the board (based on Gemini changes)
* Test file for Mistral client
* Updated handling of config, added notebook for documentation
* Added support for additional API parameters
* Remove unneeded code, updated exception raising
* Updated handling of keywords, including type checks, defaults, warnings. Updated notebook example to remove logging warnings.
* Added class description.
* Updated tests to support new config handling.
* Moved parameter parsing to create function, minimised init, added parameter tests
* Refined parameter validation
* Correct spacing
* Fixed string concat in parameter validation
* Corrected upper/lower bound warning
* Use client_tools, tidy up Mistral create, better handle tool call response, tidy tests
* Update of documentation notebook, replacement of old version
* Update to handle multiple tool_call recommendations in a message
* Updated tests to accommodate multiple tool_calls as well as content in message
* Update autogen/oai/mistral.py comment
Co-authored-by: Qingyun Wu <qingyun0327@gmail.com>
* cleanup, rewrite mock
* update
---------
Co-authored-by: Qingyun Wu <qingyun0327@gmail.com>
Co-authored-by: kevin666aa <yrwu000627@gmail.com>
* intial setup for the anthropic client with cost config
* update: other methods added
* fix: formatting
* fix: config unused
* update: changes made in the client
* update: test added to the workflow
* update: added tests to the anthropic client
* fix: errors in workflows and client
* fix
* fix: anthropic tools type
* update: notebook anthropic
* Nonetype fixed
* fix-tests config
* update: tests and client issues
* logger support
* remove sys path
* updated the functioning of the client
* update: type hints and stream
* skip tests- importerror
* fix: anthropic client and tests
* none fix
* Alternating roles, parameter keywords, cost on response,
* update: anthropic notebook
* update: notebook with more details
* devcontainer
* update: added validate_params from the client_utils
* fix: formatting
* fix: minor comment
---------
Co-authored-by: Mark Sze <mark@sze.family>
* white spaces
* add llamaindex agent wrapper for autogen
* formatting
* formatting fixes
* add support for llamaindex agents
* fix style
* fix style
* delete file
* re-add file
* fixes pre-commit errors
* feat: Add agentchat_group_chat_with_llamaindex_agents notebook
This commit adds the notebook "agentchat_group_chat_with_llamaindex_agents.ipynb" which demonstrates how to integrate Llamaindex agents into Autogen. The notebook includes code for setting up the API endpoint, creating Llamaindex agents, and setting up a group chat.
* Refactor code
* feat: Add test for LLamaIndexConversableAgent
This commit adds a new test file `test_llamaindex_conversable_agent.py` that contains a test case for the `LLamaIndexConversableAgent` class. The test verifies the functionality of group chat with two MultimodalConversable Agents, limiting the chat by the `max_round` parameter. It also checks if the number of rounds does not exceed the maximum specified rounds.
The purpose of this change is to ensure that the `LLamaIndexConversableAgent` behaves as expected and correctly handles group chats with limited rounds.
Note: This commit includes import statements and setup code necessary for running the test case.
* fix formatting
* feat: Add LlamaIndexAgent job to GitHub Actions workflow
This commit adds a new job called "LlamaIndexAgent" to the GitHub Actions workflow. The job runs on multiple operating systems (ubuntu-latest, macos-latest, windows-2019) and uses Python version 3.11. It sets up the Python environment, installs necessary packages and dependencies for LMM, performs coverage testing using pytest, and uploads the coverage report to Codecov.
The commit also includes changes to the test_llamaindex_conversable_agent.py file. It imports os and sys modules, appends a path to sys.path, and adds skip conditions for tests based on certain conditions.
These changes improve the CI/CD pipeline by adding a new job for LlamaIndexAgent and enhancing test conditions in test_llamaindex_conversable_agent.py.
* fix test yaml
* cleanup tests
* fix test run
* formatting
* add test
* fix yaml
* pr feedback
* add documentation to website
* fixed style
* edit to document page
* newline
* make skip reason easier to see
* compose skip reasons
* fix env variable name
* refactor: Update package installation in contrib workflows
- Replaced specific package installations with more general ones
- Updated the installation of llama-index packages and dependencies
- Added new packages for llama-index and Wikipedia tools
* Update dependencies and add new agents for group chat
- Update dependencies to specific versions
- Add new agent `entertainent_specialist` for discovering entertainment opportunities in a location
- Modify the `test_group_chat_with_llama_index_conversable_agent` function to include the new agent in the group chat
* Update pydantic version requirement in setup.py
- Update pydantic version requirement from "pydantic>=1.10,<3,!=2.6.0" to "pydantic>=1.10,<3"
- Remove comment about issue with pydantic 2.6.0
* Refactor ChatMessage instantiation in _extract_message_and_history()
- Refactored the instantiation of ChatMessage in the _extract_message_and_history() function.
- Added an empty dictionary as additional_kwargs to the ChatMessage constructor.
* Refactor test_llamaindex_conversable_agent.py
- Removed unused import and variable
- Updated OpenAI model to gpt-4
- Reduced max_iterations for location_specialist and entertainment_specialist from 30 to 5
- Changed human_input_mode for user_proxy to "NEVER"
- Added assertion for max_rounds in entertainent_assistant
These changes improve code efficiency and ensure proper functionality.
* Remove entertainment_specialist agent and update user_proxy settings in test_llamaindex_conversable_agent.py
- Remove the creation of entertainent_specialist agent
- Update the max_consecutive_auto_reply setting for user_proxy to 10
- Update the default_auto_reply setting for user_proxy to "Thank you. TERMINATE"
* Refactor installation of LlamaIndex packages and dependencies
- Simplify installation commands for LlamaIndex packages
- Remove specific version numbers from pip install commands
* Update test_llamaindex_conversable_agent.py to include verbose output during pytest.
- Add the -v flag to the pytest command in contrib-openai.yml.
- Print a message when skipping the test due to missing dependencies or key.
* Refactor OpenAI workflow, remove LlamaIndexAgent
This commit removes the LlamaIndexAgent from the OpenAI workflow in order to streamline and simplify the code. The LlamaIndexAgent was no longer necessary and its removal improves overall code organization and maintainability.
* feat: Add test for group chat functionality with LLamaIndexConversableAgent
use mock reactagent in test
* Update Dockerfile for devcontainer
- Updated the Dockerfile for the devcontainer environment.
- Added installation of build-essential, npm, git-lfs, and other packages.
- Upgraded pip and installed pydoc-markdown, pyyaml, and colored libraries.
* Update devcontainer.json with new VS Code extensions and terminal settings
- Updated the list of VS Code extensions in devcontainer.json to include "GitHub.copilot"
- Added a new terminal profile for Linux with the path set to "/bin/bash"
- Set the default Linux terminal profile to "bash"
* removeall
* feat: Add Dockerfiles and devcontainer configurations
This commit adds Dockerfiles and devcontainer configurations for different use cases in the `.devcontainer` directory. The following changes were made:
- Added `Dockerfile` for basic setups (`base`)
- Added `Dockerfile` for advanced features (`full`)
- Added `Dockerfile` for AutoGen project developers (`dev`)
- Added `Dockerfile` for AutoGen project developers using Studio (`studio`)
- Updated existing files with necessary dependencies and configurations
- Modified README.md to provide instructions on customizing Dockerfiles and managing the Docker environment
These changes allow users to easily set up their AutoGen development environment using Docker containers.
* delete
* Add authors.yml file with author information
This commit adds the authors.yml file, which contains information about various authors contributing to the project. Each author entry includes their name, title, URL, and image URL. This file will be used to display author information on the website.
* delete
* Add test cases for agent chat functionality
This commit adds new test cases for the agent chat functionality. The test cases include scenarios such as auto feedback from code execution, function calls, currency calculator, async function calls, group chat finite state machine, cost token tracking, and group chat state flow. These test cases cover different versions of Python (3.10, 3.11, and 3.12) and are skipped if OpenAI is not installed or the Python version does not match.
* delete
* feat: Add LLM configuration documentation
This commit adds documentation for configuring an agent's access to LLMs. It includes information on the `llm_config` argument, `config_list`, and other configuration parameters. The commit also provides examples of filtering the `config_list` based on model names and tags. Additionally, it demonstrates how to add an HTTP client in `llm_config` for proxy usage. Finally, it mentions helper functions for loading a config list from API keys, environment variables, files, or `.env` files.
Closes#1234
* delete
* feat: Add LLM configuration documentation
This commit adds documentation for configuring an agent's access to LLMs. It includes information on the `llm_config` argument, `config_list`, and other configuration parameters. The commit also provides examples of filtering the `config_list` based on model names and tags. Additionally, it demonstrates how to add an HTTP client in `llm_config` for proxy usage. Finally, it mentions helper functions for loading a config list from various sources.
Closes#1234
* delete
* adding back notebooks
* reset
* feat: Add setup.py for package installation
This commit adds a new file, `setup.py`, which is used for installing the package. The `setup.py` file includes information such as the author, description, and dependencies of the package. This allows users to easily install and use the package in their projects.
The `setup.py` file also includes different extra requirements for specific functionalities, such as retrieving chat data or running Jupyter notebooks. These extra requirements are installed when specified during installation.
Overall, this addition improves the usability and installation process of the package.
* improved deprecation warnings
* compressible_agent test fix
* fix retrieve chat history test
---------
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
* first pass at offline agent eval integration
* Integrating AgentEval for offline scenarios
* removing old changes
* fixing notebook, updating docs
* fixing subcriteria bug
* updating class comment
* cleaning up agent constructors
* moving AgentEval agents to separate folder and adding a brief README
* fixing build breaks
* fixing formatting break
* fixing comments
* consolidating files in the agenteval folder under contrib and cleaning up imports
* fixing import ordering
* adding basic agenteval tests and fixing criteria parsing bug
* first try at adding openai agenteval tests to build process
* adding non-openai agenteval tests to build process
* updating test settings
* updating openai test
* Update test/agentchat/contrib/agent_eval/test_agent_eval.py
Co-authored-by: Wael Karkoub <wael.karkoub96@gmail.com>
* Update .github/workflows/contrib-openai.yml
Co-authored-by: Wael Karkoub <wael.karkoub96@gmail.com>
* test commit
* updating typing and converting to pydantic objects
* fixing test file
---------
Co-authored-by: Beibin Li <BeibinLi@users.noreply.github.com>
Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Wael Karkoub <wael.karkoub96@gmail.com>
