Merge branch 'main' into selectspeakertransforms

.devcontainer/README.md

@@ -29,15 +29,6 @@ These configurations can be used with Codespaces and locally.
 - **Before using**: We highly encourage all potential contributors to read the [AutoGen Contributing](https://autogen-ai.github.io/autogen/docs/Contribute) page prior to submitting any pull requests.
 
 
-### studio
-
-- **Purpose**: Tailored for AutoGen project developers, this Dockerfile, i.e., `./studio/Dockerfile`, includes tools and configurations aiding in development and contribution.
-- **Usage**: Recommended for developers who are contributing to the AutoGen project.
-- **Building the Image**: Run `docker build -f studio/Dockerfile -t autogen_studio_img .`.
-- **Using with Codespaces**: `Code > Codespaces > Click on ...> New with options > Choose "studio" as devcontainer configuration`.
-- **Before using**: We highly encourage all potential contributors to read the [AutoGen Contributing](https://autogen-ai.github.io/autogen/docs/Contribute) page prior to submitting any pull requests.
-
-
 ## Customizing Dockerfiles
 
 Feel free to modify these Dockerfiles for your specific project needs. Here are some common customizations:
@@ -49,7 +40,7 @@ Feel free to modify these Dockerfiles for your specific project needs. Here are
 - **Setting Environment Variables**: Add environment variables using the `ENV` command for any application-specific configurations. We have prestaged the line needed to inject your OpenAI_key into the docker environment as a environmental variable. Others can be staged in the same way. Just uncomment the line.
     `# ENV OPENAI_API_KEY="{OpenAI-API-Key}"` to `ENV OPENAI_API_KEY="{OpenAI-API-Key}"`
 - **Need a less "Advanced" Autogen build**: If the `./full/Dockerfile` is to much but you need more than advanced then update this line in the Dockerfile file.
-`RUN pip install pyautogen[teachable,lmm,retrievechat,mathchat,blendsearch] autogenra` to install just what you need. `RUN pip install pyautogen[retrievechat,blendsearch] autogenra`
+`RUN pip install autogen[teachable,lmm,retrievechat,mathchat,blendsearch] autogenra` to install just what you need. `RUN pip install autogen[retrievechat,blendsearch] autogenra`
 - **Can't Dev without your favorite CLI tool**: if you need particular OS tools to be installed in your Docker container you can add those packages here right after the sudo for the `./base/Dockerfile` and `./full/Dockerfile` files. In the example below we are installing net-tools and vim to the environment.
 
     ```code

.devcontainer/full/Dockerfile

@@ -22,7 +22,7 @@ WORKDIR /home/autogen-ai
 
 # Install Python packages
 RUN pip install --upgrade pip
-RUN pip install pyautogen[teachable,lmm,retrievechat,mathchat,blendsearch] autogenra
+RUN pip install autogen[teachable,lmm,retrievechat,mathchat,blendsearch] autogenra
 RUN pip install numpy pandas matplotlib seaborn scikit-learn requests urllib3 nltk pillow pytest beautifulsoup4
 
 # Expose port

.gitignore

@@ -187,6 +187,5 @@ local_cache
 
 
 notebook/result.png
-samples/apps/autogen-studio/autogenstudio/models/test/
 
 notebook/coding

README.md

@@ -1,20 +1,31 @@
 <a name="readme-top"></a>
 
-[![PyPI version](https://badge.fury.io/py/pyautogen.svg)](https://badge.fury.io/py/pyautogen)
+[![PyPI version](https://badge.fury.io/py/autogen.svg)](https://badge.fury.io/py/autogen)
 [![Build](https://github.com/autogen-ai/autogen/actions/workflows/python-package.yml/badge.svg)](https://github.com/autogen-ai/autogen/actions/workflows/python-package.yml)
 ![Python Version](https://img.shields.io/badge/3.8%20%7C%203.9%20%7C%203.10%20%7C%203.11%20%7C%203.12-blue)
-[![Downloads](https://static.pepy.tech/badge/pyautogen/month)](https://pepy.tech/project/pyautogen)
 [![Discord](https://img.shields.io/discord/1153072414184452236?logo=discord&style=flat)](https://discord.gg/pAbnFJrkgZ)
 [![Twitter](https://img.shields.io/twitter/url/https/twitter.com/cloudposse.svg?style=social&label=Follow%20%40Chi_Wang_)](https://x.com/Chi_Wang_)
 
 [![NuGet version](https://badge.fury.io/nu/AutoGen.Core.svg)](https://badge.fury.io/nu/AutoGen.Core)
 
-# AutoGen
+# [AutoGen](https://github.com/autogen-ai/autogen)
+
 [📚 Cite paper](#related-papers).
 <!-- <p align="center">
     <img src="https://github.com/autogen-ai/autogen/blob/main/website/static/img/flaml.svg"  width=200>
     <br>
 </p> -->
+:fire: :tada: Sep 06, 2024: AutoGen now available as `autogen` on PyPI! We're excited to announce a more convenient package name for AutoGen: Starting with version 0.3.0, you can now install AutoGen using:
+```
+pip install autogen
+```
+We extend our sincere gratitude to the original owner of `autogen` pypi package for generously transferring it to us.
+
+**Note:** The previous package name `pyautogen` will remain valid for a transitional period. However, we encourage users to switch to the new, more intuitive `autogen` package name, as `pyautogen` will eventually be deprecated.
+
+📄 **License Change:**
+With this new release and package name, we are officially switching to the Apache 2.0 license. This enhances our commitment to open-source collaboration while providing additional protections for contributors and users alike.
+
 :fire: Aug 24, 2024: A new organization [autogen-ai](https://github.com/autogen-ai) is created to host the development of AutoGen and related projects with open governance. We invite collaborators from all organizations and individuals.
 
 :tada: May 29, 2024: DeepLearning.ai launched a new short course [AI Agentic Design Patterns with AutoGen](https://www.deeplearning.ai/short-courses/ai-agentic-design-patterns-with-autogen), made in collaboration with Microsoft and Penn State University, and taught by AutoGen creators [Chi Wang](https://github.com/sonichi) and [Qingyun Wu](https://github.com/qingyun-wu).
@@ -117,14 +128,14 @@ Find detailed instructions for users [here](https://autogen-ai.github.io/autogen
 AutoGen requires **Python version >= 3.8, < 3.13**. It can be installed from pip:
 
 ```bash
-pip install pyautogen
+pip install autogen
 ```
 
 Minimal dependencies are installed without extra options. You can install extra options based on the feature you need.
 
 <!-- For example, use the following to install the dependencies needed by the [`blendsearch`](https://microsoft.github.io/FLAML/docs/Use-Cases/Tune-User-Defined-Function#blendsearch-economical-hyperparameter-optimization-with-blended-search-strategy) option.
 ```bash
-pip install "pyautogen[blendsearch]"
+pip install "autogen[blendsearch]"
 ``` -->
 
 Find more options in [Installation](https://autogen-ai.github.io/autogen/docs/Installation#option-2-install-autogen-locally-using-virtual-environment).
@@ -177,7 +188,7 @@ After the repo is cloned.
 The figure below shows an example conversation flow with AutoGen.
 ![Agent Chat Example](https://github.com/autogen-ai/autogen/blob/main/website/static/img/chat_example.png)
 
-Alternatively, the [sample code](https://github.com/autogen-ai/autogen/blob/main/samples/simple_chat.py) here allows a user to chat with an AutoGen agent in ChatGPT style.
+Alternatively, the [sample code](https://github.com/autogen-ai/build-with-autogen/blob/main/samples/simple_chat.py) here allows a user to chat with an AutoGen agent in ChatGPT style.
 Please find more [code examples](https://autogen-ai.github.io/autogen/docs/Examples#automated-multi-agent-chat) for this feature.
 
 <p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
@@ -233,6 +244,12 @@ In addition, you can find:
   </a>
 </p>
 
+## CookBook
+
+Explore detailed implementations with sample code and applications to help you get started with AutoGen.
+[Cookbook](https://github.com/autogen-ai/build-with-autogen)
+
+
 ## Related Papers
 
 [AutoGen](https://arxiv.org/abs/2308.08155)

TRANSPARENCY_FAQS.md

@@ -31,6 +31,8 @@ While AutoGen automates LLM workflows, decisions about how to use specific LLM o
 -	Current version of AutoGen was evaluated on six applications to illustrate its potential in simplifying the development of high-performance multi-agent applications. These applications are selected based on their real-world relevance,  problem difficulty and problem solving capabilities enabled by AutoGen, and innovative potential.
 -	These applications involve using AutoGen to solve math problems, question answering, decision making in text world environments, supply chain optimization, etc. For each of these domains AutoGen was evaluated on various success based metrics (i.e., how often the AutoGen based implementation solved the task). And, in some cases, AutoGen based approach was also evaluated on implementation efficiency (e.g., to track reductions in developer effort to build). More details can be found at: https://aka.ms/AutoGen/TechReport
 - The team has conducted tests where a “red” agent attempts to get the default AutoGen assistant to break from its alignment and guardrails. The team has observed that out of 70 attempts to break guardrails, only 1 was successful in producing text that would have been flagged as problematic by Azure OpenAI filters. The team has not observed any evidence that AutoGen (or GPT models as hosted by OpenAI or Azure) can produce novel code exploits or jailbreak prompts, since direct prompts to “be a hacker”, “write exploits”, or “produce a phishing email” are refused by existing filters.
+- We also evaluated [a team of AutoGen agents](https://github.com/microsoft/autogen/tree/gaia_multiagent_v01_march_1st/samples/tools/autogenbench/scenarios/GAIA/Templates/Orchestrator) on the [GAIA benchmarks](https://arxiv.org/abs/2311.12983), and got [SOTA results](https://huggingface.co/spaces/gaia-benchmark/leaderboard) as of
+ March 1, 2024.
 
 ## What are the limitations of AutoGen? How can users minimize the impact of AutoGen’s limitations when using the system?
 AutoGen relies on existing LLMs. Experimenting with AutoGen would retain common limitations of large language models; including:

autogen/agentchat/contrib/agent_builder.py

@@ -109,7 +109,7 @@ class AgentBuilder:
 """
 
     AGENT_NAME_PROMPT = """# Your task
-Suggest no more then {max_agents} experts with their name according to the following user requirement.
+Suggest no more than {max_agents} experts with their name according to the following user requirement.
 
 ## User requirement
 {task}

autogen/agentchat/contrib/capabilities/text_compressors.py

@@ -10,9 +10,7 @@
 try:
     import llmlingua
 except ImportError:
-    IMPORT_ERROR = ImportError(
-        "LLMLingua is not installed. Please install it with `pip install pyautogen[long-context]`"
-    )
+    IMPORT_ERROR = ImportError("LLMLingua is not installed. Please install it with `pip install autogen[long-context]`")
     PromptCompressor = object
 else:
     from llmlingua import PromptCompressor

autogen/agentchat/contrib/retrieve_user_proxy_agent.py

@@ -15,7 +15,7 @@
 try:
     import chromadb
 except ImportError as e:
-    raise ImportError(f"{e}. You can try `pip install pyautogen[retrievechat]`, or install `chromadb` manually.")
+    raise ImportError(f"{e}. You can try `pip install autogen[retrievechat]`, or install `chromadb` manually.")
 from autogen.agentchat import UserProxyAgent
 from autogen.agentchat.agent import Agent
 from autogen.agentchat.contrib.vectordb.base import Document, QueryResults, VectorDB, VectorDBFactory

autogen/coding/func_with_reqs.py

@@ -12,7 +12,7 @@
 from dataclasses import dataclass, field
 from importlib.abc import SourceLoader
 from textwrap import dedent, indent
-from typing import Any, Callable, Generic, List, TypeVar, Union
+from typing import Any, Callable, Generic, List, Set, TypeVar, Union
 
 from typing_extensions import ParamSpec
 
@@ -165,12 +165,12 @@ def _build_python_functions_file(
     funcs: List[Union[FunctionWithRequirements[Any, P], Callable[..., Any], FunctionWithRequirementsStr]]
 ) -> str:
     # First collect all global imports
-    global_imports = set()
+    global_imports: Set[str] = set()
     for func in funcs:
         if isinstance(func, (FunctionWithRequirements, FunctionWithRequirementsStr)):
-            global_imports.update(func.global_imports)
+            global_imports.update(map(_import_to_str, func.global_imports))
 
-    content = "\n".join(map(_import_to_str, global_imports)) + "\n\n"
+    content = "\n".join(global_imports) + "\n\n"
 
     for func in funcs:
         content += _to_code(func) + "\n\n"

autogen/coding/local_commandline_code_executor.py

@@ -227,7 +227,12 @@ def _setup_functions(self) -> None:
             cmd = [py_executable, "-m", "pip", "install"] + required_packages
             try:
                 result = subprocess.run(
-                    cmd, cwd=self._work_dir, capture_output=True, text=True, timeout=float(self._timeout)
+                    cmd,
+                    cwd=self._work_dir,
+                    capture_output=True,
+                    text=True,
+                    timeout=float(self._timeout),
+                    encoding="utf-8",
                 )
             except subprocess.TimeoutExpired as e:
                 raise ValueError("Pip install timed out") from e
@@ -309,7 +314,13 @@ def _execute_code_dont_check_setup(self, code_blocks: List[CodeBlock]) -> Comman
 
             try:
                 result = subprocess.run(
-                    cmd, cwd=self._work_dir, capture_output=True, text=True, timeout=float(self._timeout), env=env
+                    cmd,
+                    cwd=self._work_dir,
+                    capture_output=True,
+                    text=True,
+                    timeout=float(self._timeout),
+                    env=env,
+                    encoding="utf-8",
                 )
             except subprocess.TimeoutExpired:
                 logs_all += "\n" + TIMEOUT_MSG

autogen/oai/bedrock.py

@@ -204,13 +204,7 @@ def create(self, params):
         if len(tool_config["tools"]) > 0:
             request_args["toolConfig"] = tool_config
 
-        try:
-            response = self.bedrock_runtime.converse(
-                **request_args,
-            )
-        except Exception as e:
-            raise RuntimeError(f"Failed to get response from Bedrock: {e}")
-
+        response = self.bedrock_runtime.converse(**request_args)
         if response is None:
             raise RuntimeError(f"Failed to get response from Bedrock after retrying {self._retries} times.")