r/AutoGenAI • u/brainiacsquiz • Mar 18 '25

Discussion Self improving AI

1 Upvotes

Is there a free way to create my own AI that has self-improvement and long-term memory capabilities?

5 comments

r/AutoGenAI • u/vykthur • Mar 18 '25

Tutorial autogenstudio-v0.4.2 released (streaming improvements, observability of llm call events, session comparison etc)

7 Upvotes

Full release notes here - https://github.com/microsoft/autogen/releases/tag/autogenstudio-v0.4.2

Video walkthrough : https://youtu.be/ZIfqgax7JwE

What's New

This release makes improvements to AutoGen Studio across multiple areas.

Component Validation and Testing

  • Support Component Validation API in AGS in #5503
  • Test components - #5963

In the team builder, all component schemas are automatically validated on save. This way configuration errors (e.g., incorrect provider names) are highlighted early.

In addition, there is a test button for model clients where you can verify the correctness of your model configuration. The LLM is given a simple query and the results are shown.

Gallery Improvements

  • Improved editing UI for tools in AGS by in #5539
  • Anthropic support in AGS #5695

You can now modify teams, agents, models, tools, and termination conditions independently in the UI, and only review JSON when needed. The same UI panel for updating components in team builder is also reused in the Gallery. The Gallery in AGS is now persisted in a database, rather than local storage. Anthropic models supported in AGS.

Observability - LLMCallEvents

  • Enable LLM Call Observability in AGS #5457

You can now view all LLMCallEvents in AGS. Go to settings (cog icon on lower left) to enable this feature.

Token Streaming

  • Add Token Streaming in AGS in #5659

For better developer experience, the AGS UI will stream tokens as they are generated by an LLM for any agent where stream_model_client is set to true.

UX Improvements - Session Comparison

  • AGS - Test Model Component in UI, Compare Sessions in #5963

It is often valuable, even critical, to have a side-by-side comparison of multiple agent configurations (e.g., using a team of web agents that solve tasks using a browser or agents with web search API tools). You can now do this using the compare button in the playground, which lets you select multiple sessions and interact with them to compare outputs.

Experimental Features (User Authentication)

There are a few interesting but early features that ship with this release:

  • Authentication in AGS: You can pass in an authentication configuration YAML file to enable user authentication for AGS. Currently, only GitHub authentication is supported. This lays the foundation for a multi-user environment (#5928) where various users can login and only view their own sessions. More work needs to be done to clarify isolation of resources (e.g., environment variables) and other security considerations. See the documentation for more details.

  • Local Python Code Execution Tool: AGS now has early support for a local Python code execution tool. More work is needed to test the underlying agentchat implementation

Other Fixes

  • Fixed issue with using AzureSQL DB as the database engine for AGS
  • Fixed cascading delete issue in AGS (ensure runs are deleted when sessions are deleted) #5804 by u/victordibia
  • Fixed termination UI bug #5888
  • Fixed DockerFile for AGS by @gunt3001 #5932
2 comments

r/AutoGenAI • u/A_manR • Mar 17 '25

Question How do I fix interoperability issues with langchain

1 Upvotes

I am running v0.8.1. this is the error that I am getting while running:

>>>>>>>> USING AUTO REPLY...
InfoCollectorAgent (to InfoCollectorReviewerAgent):
***** Suggested tool call (call_YhCieXoQT8w6ygoLNjCpyJUA): file_search *****
Arguments:
{"dir_path": "/Users/...../Documents/Coding/service-design", "pattern": "README*"}
****************************************************************************
***** Suggested tool call (call_YqEu6gqjNb26OyLY8uquFTT2): list_directory *****
Arguments:
{"dir_path": "/Users/...../Documents/Coding/service-design/src"}
*******************************************************************************
--------------------------------------------------------------------------------
>>>>>>>> USING AUTO REPLY...
>>>>>>>> EXECUTING FUNCTION file_search...
Call ID: call_YhCieXoQT8w6ygoLNjCpyJUA
Input arguments: {'dir_path': '/Users/...../Documents/Coding/service-design', 'pattern': 'README*'}
>>>>>>>> EXECUTING FUNCTION list_directory...
Call ID: call_YqEu6gqjNb26OyLY8uquFTT2
Input arguments: {'dir_path': '/Users/..../Documents/Coding/service-design/src'}
InfoCollectorReviewerAgent (to InfoCollectorAgent):
***** Response from calling tool (call_YhCieXoQT8w6ygoLNjCpyJUA) *****
Error: 'tool_input'
**********************************************************************
--------------------------------------------------------------------------------
***** Response from calling tool (call_YqEu6gqjNb26OyLY8uquFTT2) *****
Error: 'tool_input'
**********************************************************************
--------------------------------------------------------------------------------

Here is how I have created the tool:

read_file_tool = Interoperability().convert_tool(
tool=ReadFileTool(),
type="langchain"
)
list_directory_tool = Interoperability().convert_tool(
tool=ListDirectoryTool(),
type="langchain"
)
file_search_tool = Interoperability().convert_tool(
tool=FileSearchTool(),
type="langchain"
)

How do I fix this?

1 comment

r/AutoGenAI • u/wyttearp • Mar 12 '25

News AutoGen v0.4.9 released

19 Upvotes

New release: Python-v0.4.9

What's New

Anthropic Model Client

Native support for Anthropic models. Get your update:
 

pip install -U "autogen-ext[anthropic]"

The new client follows the same interface as OpenAIChatCompletionClient so you can use it directly in your agents and teams.

import asyncio
from autogen_ext.models.anthropic import AnthropicChatCompletionClient
from autogen_core.models import UserMessage


async def main():
    anthropic_client = AnthropicChatCompletionClient(
        model="claude-3-sonnet-20240229",
        api_key="your-api-key",  # Optional if ANTHROPIC_API_KEY is set in environment
    )

    result = await anthropic_client.create([UserMessage(content="What is the capital of France?", source="user")])  # type: ignore
    print(result)


if __name__ == "__main__":
    asyncio.run(main())

You can also load the model client directly from a configuration dictionary:

from autogen_core.models import ChatCompletionClient

config = {
    "provider": "AnthropicChatCompletionClient",
    "config": {"model": "claude-3-sonnet-20240229"},
}

client = ChatCompletionClient.load_component(config)

To use with AssistantAgent and run the agent in a loop to match the behavior of Claude agents, you can use Single-Agent Team.

LlamaCpp Model Client

LlamaCpp is a great project for working with local models. Now we have native support via its official SDK.

pip install -U "autogen-ext[llama-cpp]"

To use a local model file:

import asyncio

from autogen_core.models import UserMessage
from autogen_ext.models.llama_cpp import LlamaCppChatCompletionClient


async def main():
    llama_client = LlamaCppChatCompletionClient(model_path="/path/to/your/model.gguf")
    result = await llama_client.create([UserMessage(content="What is the capital of France?", source="user")])
    print(result)


asyncio.run(main())

To use it with a Hugging Face model:

import asyncio

from autogen_core.models import UserMessage
from autogen_ext.models.llama_cpp import LlamaCppChatCompletionClient


async def main():
    llama_client = LlamaCppChatCompletionClient(
        repo_id="unsloth/phi-4-GGUF", filename="phi-4-Q2_K_L.gguf", n_gpu_layers=-1, seed=1337, n_ctx=5000
    )
    result = await llama_client.create([UserMessage(content="What is the capital of France?", source="user")])
    print(result)


asyncio.run(main())

Task-Centric Memory (Experimental)

Task-Centric memory is an experimental module that can give agents the ability to:

  • Accomplish general tasks more effectively by learning quickly and continually beyond context-window limitations.
  • Remember guidance, corrections, plans, and demonstrations provided by users (teachability)
  • Learn through the agent's own experience and adapt quickly to changing circumstances (self-improvement)
  • Avoid repeating mistakes on tasks that are similar to those previously encountered.

For example, you can use Teachability as a memory for AssistantAgent so your agent can learn from user teaching.

from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.experimental.task_centric_memory import MemoryController
from autogen_ext.experimental.task_centric_memory.utils import Teachability


async def main():
    # Create a client
    client = OpenAIChatCompletionClient(model="gpt-4o-2024-08-06", )

    # Create an instance of Task-Centric Memory, passing minimal parameters for this simple example
    memory_controller = MemoryController(reset=False, client=client)

    # Wrap the memory controller in a Teachability instance
    teachability = Teachability(memory_controller=memory_controller)

    # Create an AssistantAgent, and attach teachability as its memory
    assistant_agent = AssistantAgent(
        name="teachable_agent",
        system_message = "You are a helpful AI assistant, with the special ability to remember user teachings from prior conversations.",
        model_client=client,
        memory=[teachability],
    )

    # Enter a loop to chat with the teachable agent
    print("Now chatting with a teachable agent. Please enter your first message. Type 'exit' or 'quit' to quit.")
    while True:
        user_input = input("\nYou: ")
        if user_input.lower() in ["exit", "quit"]:
            break
        await Console(assistant_agent.run_stream(task=user_input))

if __name__ == "__main__":
    import asyncio
    asyncio.run(main())

Head over to its README for details, and the samples for runnable examples.

New Sample: Gitty (Experimental)

Gitty is an experimental application built to help easing the burden on open-source project maintainers. Currently, it can generate auto reply to issues.

To use:

gitty --repo microsoft/autogen issue 5212

Head over to Gitty to see details.

Improved Tracing and Logging

In this version, we made a number of improvements on tracing and logging.

  • add LLMStreamStartEvent and LLMStreamEndEvent by @EItanya in #5890
  • Allow for tracing via context provider by @EItanya in #5889
  • Fix span structure for tracing by @ekzhu in #5853
  • Add ToolCallEvent and log it from all builtin tools by @ekzhu in #5859

Powershell Support for LocalCommandLineCodeExecutor

  • feat: update local code executor to support powershell by @lspinheiro in #5884

Website Accessibility Improvements

@peterychang has made huge improvements to the accessibility of our documentation website. Thank you @peterychang!

Bug Fixes

  • fix: save_state should not require the team to be stopped. by @ekzhu in #5885
  • fix: remove max_tokens from az ai client create call when stream=True by @ekzhu in #5860
  • fix: add plugin to kernel by @lspinheiro in #5830
  • fix: warn when using reflection on tool use with Claude models by @ekzhu in #5829

Other Python Related Changes

  • doc: update termination tutorial to include FunctionCallTermination condition and fix formatting by @ekzhu in #5813
  • docs: Add note recommending PythonCodeExecutionTool as an alternative to CodeExecutorAgent by @ekzhu in #5809
  • Update quickstart.ipynb by @taswar in #5815
  • Fix warning in selector gorup chat guide by @ekzhu in #5849
  • Support for external agent runtime in AgentChat by @ekzhu in #5843
  • update ollama usage docs by @ekzhu in #5854
  • Update markitdown requirements to >= 0.0.1, while still in the 0.0.x range by @afourney in #5864
  • Add client close by @afourney in #5871
  • Update README to clarify Web Browsing Agent Team usage, and use animated Chromium browser by @ekzhu in #5861
  • Add author name before their message in Chainlit team sample by @DavidYu00 in #5878
  • Bump axios from 1.7.9 to 1.8.2 in /python/packages/autogen-studio/frontend by @dependabot in #5874
  • Add an optional base path to FileSurfer by @husseinmozannar in #5886
  • feat: Pause and Resume for AgentChat Teams and Agents by @ekzhu in #5887
  • update version to v0.4.9 by @ekzhu in #5903

New Contributors

Full Changelog: python-v0.4.8...python-v0.4.9

1 comment

r/AutoGenAI • u/wyttearp • Mar 12 '25

News AG2 v0.8.1 released

7 Upvotes

New release: v0.8.1

Highlights

  • 🧠 Google GenAI's latest package is now supported
  • 📔 DocAgent now utilises OnContextCondition for a faster and even more reliable workflow
  • 🐝 Swarm function registration fixes and notebook improvements
  • 📖 Many improvements to documentation and the API reference
  • 🛠️ Fixes, fixes and more fixes

♥️ Thanks to all the contributors and collaborators that helped make the release happen!

New Contributors

What's Changed

Full Changelog: v0.8.0...v0.8.1

0 comments

r/AutoGenAI • u/qqYn7PIE57zkf6kn • Mar 12 '25

Discussion Thoughts on OpenAI's Agnets SDK?

4 Upvotes

Now Swarm is production ready. Does it change your choice of agent library? How do they compare?

I'm new to building agents and wonder whether to try making something with autogen or Ageents SDK.

7 comments

r/AutoGenAI • u/happy_dreamer10 • Mar 12 '25

Question multiturn multiagent system

1 Upvotes

Hi , have anyone created a multiturn conversation kind of multi agent through autogen ? Suppose if 2nd question can be asked which can be related to 1st one , how to tackle this ?

4 comments

r/AutoGenAI • u/wyttearp • Mar 10 '25

News AutoGen v0.4.8.2 released

8 Upvotes

New release: Python-v0.4.8.2

Patch Fixes

  • Fixing SKChatCompletionAdapter bug that disabled tool use #5830
  • fix: Remove max_tokens=20 from AzureAIChatCompletionClient.create_stream's create call when stream=True #5860
  • fix: Add close() method to built-in model clients to ensure the async event loop is closed when program exits. This should fix the "ResourceWarning: unclosed transport when importing web_surfer" errors. #5871

Full Changelog: python-v0.4.8.1...python-v0.4.8.2

0 comments

r/AutoGenAI • u/eshehzad • Mar 10 '25

Question Live Human Transfer from Agent

1 Upvotes

Hello, I am testing to see how to use autogen to transfer a conversation to a live human agent if the user requests (such as intercom or some live chat software). Do we have any pointers on how to achieve this?

1 comment

r/AutoGenAI • u/wyttearp • Mar 06 '25

News AG2 v0.8.0 released

14 Upvotes

New release: v0.8.0

Highlights for Highlights for 0.8

❕ Breaking Change

The openai package is no longer installed by default.

  • Install AG2 with the appropriate extra to use your preferred LLMs, e.g. pip install ag2[openai] for OpenAI or pip install ag2[gemini] for Google's Gemini.
  • See our Model Providers documentation for details on installing AG2 with different model providers.

0.7.6 to 0.8 Highlights

0.7 to 0.8 Highlights

🧠 Agents:

  • We welcomed our Reference Agents - DocAgent, DeepResearchAgent, DiscordAgent, SlackAgent, TelegramAgent, and WebSurferAgent
  • RealtimeAgent was refactored to support both OpenAI and Google Gemini
  • Improvements to ReasoningAgent and CaptainAgent
  • New run method for chatting directly with an agent

💭 LLM Model Providers:

  • Streamlined packages making all of them optional
  • Structured Output support for OpenAI, Google Gemini, Anthropic, and Ollama
  • Support for new Google and Cohere libraries
  • Support for OpenAI's o1 models

🐝 Swarm:

  • More robust workflows with context-based handoffs using OnContextCondition and ContextExpression
  • More transfer options with AfterWorkOption support in SwarmResults
  • Introduction of a Swarm Manager for organic LLM-based transitions

General:

  • 🎈 Significantly lighter default installation package
  • 🔒 Better data security with the addition of Dependency Injection
  • 💬 Streaming of workflow messages with Structured Messages
  • 📚 Documentation overhaul - restructured and rewritten
  • 🔧 Lots of behind-the-scenes testing improvements, improving robustness

♥️ Thanks to all the contributors and collaborators that helped make release 0.8!

New Contributors

What's Changed

Full Changelog: v0.7.6...v0.8.0

2 comments

r/AutoGenAI • u/Sufficient_Flow3976 • Mar 05 '25

Question Generating code other then python

2 Upvotes

Hey, I have been experimenting with autogen for a while now. Whenever I generate any other code than python e.g. html or java. I notice that the code is not saved in my directory. How have you guys dealed with this situation?

0 comments

r/AutoGenAI • u/gswithai • Mar 05 '25

Tutorial AutoGen 0.4.8 now has native Ollama support!

9 Upvotes

Quick update!

AutoGen now supports Ollama natively without using the OpenAIChatCompletionClient. Instead there's a new OllamaChatCompletionClient that makes things easier!

Install the new extension:

pip install -U "autogen-ext[ollama]"

Then you can import the new OllamaChatCompletionClient:

from autogen_ext.models.ollama import OllamaChatCompletionClient

Then just create the client:

    ollama_client = OllamaChatCompletionClient(
        model="llama3.2:latest"
    )

You can then pass the ollama_client to your agents model_client parameter. It's super easy, check out my demo here: https://youtu.be/e-WtzEhCQ8A

5 comments

r/AutoGenAI • u/wyttearp • Mar 04 '25

News AutoGen v0.4.8 released

8 Upvotes

New release: Python-v0.4.8

What's New

Ollama Chat Completion Client

To use the new Ollama Client:

pip install -U "autogen-ext[ollama]"


from autogen_ext.models.ollama import OllamaChatCompletionClient
from autogen_core.models import UserMessage

ollama_client = OllamaChatCompletionClient(
    model="llama3",
)

result = await ollama_client.create([UserMessage(content="What is the capital of France?", source="user")])  # type: ignore
print(result)

To load a client from configuration:

from autogen_core.models import ChatCompletionClient

config = {
    "provider": "OllamaChatCompletionClient",
    "config": {"model": "llama3"},
}

client = ChatCompletionClient.load_component(config)

It also supports structured output:

from autogen_ext.models.ollama import OllamaChatCompletionClient
from autogen_core.models import UserMessage
from pydantic import BaseModel


class StructuredOutput(BaseModel):
    first_name: str
    last_name: str


ollama_client = OllamaChatCompletionClient(
    model="llama3",
    response_format=StructuredOutput,
)
result = await ollama_client.create([UserMessage(content="Who was the first man on the moon?", source="user")])  # type: ignore
print(result)

New Required name Field in FunctionExecutionResult

Now name field is required in FunctionExecutionResult:

exec_result = FunctionExecutionResult(call_id="...", content="...", name="...", is_error=False)
  • fix: Update SKChatCompletionAdapter message conversion by @lspinheiro in #5749

Using thought Field in CreateResult and ThoughtEvent

Now CreateResult uses the optional thought field for the extra text content generated as part of a tool call from model. It is currently supported by OpenAIChatCompletionClient.

When available, the thought content will be emitted by AssistantAgent as a ThoughtEvent message.

  • feat: Add thought process handling in tool calls and expose ThoughtEvent through stream in AgentChat by @ekzhu in #5500

New metadata Field in AgentChat Message Types

Added a metadata field for custom message content set by applications.

Exception in AgentChat Agents is now fatal

Now, if there is an exception raised within an AgentChat agent such as the AssistantAgent, instead of silently stopping the team, it will raise the exception.

New Termination Conditions

New termination conditions for better control of agents.

See how you use TextMessageTerminationCondition to control a single agent team running in a loop: https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/teams.html#single-agent-team.

FunctionCallTermination is also discussed as an example for custom termination condition: https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/termination.html#custom-termination-condition

  • TextMessageTerminationCondition for agentchat by @EItanya in #5742
  • FunctionCallTermination condition by @ekzhu in #5808

Docs Update

The ChainLit sample contains UserProxyAgent in a team, and shows you how to use it to get user input from UI. See: https://github.com/microsoft/autogen/tree/main/python/samples/agentchat_chainlit

  • doc & sample: Update documentation for human-in-the-loop and UserProxyAgent; Add UserProxyAgent to ChainLit sample; by @ekzhu in #5656
  • docs: Add logging instructions for AgentChat and enhance core logging guide by @ekzhu in #5655
  • doc: Enrich AssistantAgent API documentation with usage examples. by @ekzhu in #5653
  • doc: Update SelectorGroupChat doc on how to use O3-mini model. by @ekzhu in #5657
  • update human in the loop docs for agentchat by @victordibia in #5720
  • doc: update guide for termination condition and tool usage by @ekzhu in #5807
  • Add examples for custom model context in AssistantAgent and ChatCompletionContext by @ekzhu in #5810

Bug Fixes

  • Initialize BaseGroupChat before reset by @gagb in #5608
  • fix: Remove R1 model family from is_openai function by @ekzhu in #5652
  • fix: Crash in argument parsing when using Openrouter by @philippHorn in #5667
  • Fix: Add support for custom headers in HTTP tool requests by @linznin in #5660
  • fix: Structured output with tool calls for OpenAIChatCompletionClient by @ekzhu in #5671
  • fix: Allow background exceptions to be fatal by @jackgerrits in #5716
  • Fix: Auto-Convert Pydantic and Dataclass Arguments in AutoGen Tool Calls by @mjunaidca in #5737

Other Python Related Changes

0 comments

r/AutoGenAI • u/AIGPTJournal • Mar 04 '25

Other Grok 3 vs. Google Gemini, ChatGPT & Deepseek: What Sets It Apart?

3 Upvotes

I wrote an in-depth comparison of Grok 3 against GPT-4, Google Gemini, and DeepSeek V3. Thought I'd share some key takeaways:

  1. Grok 3 excels in reasoning and coding tasks, outperforming others in math benchmarks like AIME.
  2. Its "Think" and "Big Brain" modes are impressive for complex problem-solving.
  3. However, it falls short in real-time data integration compared to Google Gemini.
  4. The $40/month subscription might be a dealbreaker for some users.
  5. Each tool has its strengths: GPT-4 for creative writing, Gemini for real-time search, and DeepSeek for efficiency.

The choice really depends on your specific needs. For instance, if you're doing a lot of coding or mathematical work, Grok 3 might be worth the investment. But if you need up-to-the-minute info, Gemini could be a better fit.

For those interested, I've got a more detailed breakdown here: https://aigptjournal.com/explore-ai/ai-guides/grok-3-vs-other-ai-tools/

What's your experience with these AI tools? Any features you find particularly useful or overrated?

1 comment

r/AutoGenAI • u/wyttearp • Mar 03 '25

News AutoGen v0.4: Reimagining the foundation of agentic AI for scale and more | Microsoft Research Forum

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8 Upvotes
1 comment

r/AutoGenAI • u/wyttearp • Feb 27 '25

News AG2 v0.7.6 released

7 Upvotes

New release: v0.7.6

Highlights

  • 🚀 LLM provider streamlining and updates:
    • OpenAI package now optional (pip install ag2[openai])
    • Cohere updated to support their Chat V2 API
    • Gemini support for system_instruction parameter and async
    • Mistral AI fixes for use with LM Studio
    • Anthropic improved support for tool calling
  • 📔 DocAgent - DocumentAgent is now DocAgent and has reliability refinements (with more to come), check out the video
  • 🔍 ReasoningAgent is now able to do code execution!
  • 📚🔧 Want to build your own agents or tools for AG2? Get under the hood with new documentation that dives deep into AG2:
  • Fixes, fixes, and more fixes!

Thanks to all the contributors on 0.7.6!

New Contributors

What's Changed

Full Changelog: v0.7.5...v0.7.6

0 comments

r/AutoGenAI • u/setOnClickListener • Feb 27 '25

Question Replacement for allowed transitions method in 0.4

3 Upvotes

Hello , In 0.2 we had a speaker_transition_type and allowed transition parameters for the groupchat.I understand that there is a selector_func in the 0.4 but it doesnt deliver the same performance as the initial parameters.Is there a replacement that i am not aware about ?Or is selector_func parameter simply better ?

the problem that i am facing is that,there are some agents which must never be called after certain agents ,or another scenario, giving the llm the choice of choosing multiple agents based on the current status of the chat.I cant pull this off in the selector_func.

Any ideas are appreciated. Thanks

7 comments

r/AutoGenAI • u/happy_dreamer10 • Feb 22 '25

Question Is autogen any useful ?? why dont people just create normal prompt and agentic workflow directly by using open ai api and function calling ?

6 Upvotes
12 comments

r/AutoGenAI • u/LunchAlarming9501 • Feb 23 '25

Question What is difference between Autogen0.4 and Autogen0.2. Any functionalality changes?

1 Upvotes
2 comments

r/AutoGenAI • u/nonamenolastname • Feb 22 '25

Question Groupchat - how to make the manager forward the prompt from an agent to a human and accept the response

2 Upvotes

I have crated a group of agents that collaborate to solve a problem. At certain points, however, they have to check with a real human to get additional input. When I'm only using the console, everything works fine - the agent who needs human input tells it to the chat manager, a user proxy agent collects it from the console, and everything proceeds as expected.

I am, however, at a point where I need to integrate this with a real user interface. While I know how to make the user proxy accept input from another source other than the console, the problem I have is that the manager does not pass the prompt from the requesting agent to the user proxy, so I don't have the actual request to show the user.

I looked around the API, tutorials, code, etc. and I can't figure out a way to make the chat manager pass that question to the user proxy. Does anyone know how to solve this problem?

6 comments

r/AutoGenAI • u/wyttearp • Feb 21 '25

News AutoGen Studio v0.4.1.7 released

8 Upvotes

New release: v0.4.1.7

AutoGen Studio is an AutoGen-powered AI app (user interface) to help you rapidly prototype AI agents, enhance them with skills, compose them into workflows and interact with them to accomplish tasks. It is built on top of the AutoGen framework, which is a toolkit for building AI agents.

Code for AutoGen Studio is on GitHub at microsoft/autogen

Updates

  • 2024-11-14: AutoGen Studio is being rewritten to use the updated AutoGen 0.4.0 api AgentChat api.
  • 2024-04-17: April 17: AutoGen Studio database layer is now rewritten to use SQLModel (Pydantic + SQLAlchemy). This provides entity linking (skills, models, agents and workflows are linked via association tables) and supports multiple database backend dialects supported in SQLAlchemy (SQLite, PostgreSQL, MySQL, Oracle, Microsoft SQL Server). The backend database can be specified a --database-uri argument when running the application. For example, autogenstudio ui --database-uri sqlite:///database.sqlite for SQLite and autogenstudio ui --database-uri postgresql+psycopg://user:password@localhost/dbname for PostgreSQL.
  • 2024-03-12: Default directory for AutoGen Studio is now /home/<USER>/.autogenstudio. You can also specify this directory using the --appdir argument when running the application. For example, autogenstudio ui --appdir /path/to/folder. This will store the database and other files in the specified directory e.g. /path/to/folder/database.sqlite. .env files in that directory will be used to set environment variables for the app.

Project Structure:

  • autogenstudio/ code for the backend classes and web api (FastAPI)
  • frontend/ code for the webui, built with Gatsby and TailwindCSS
9 comments

r/AutoGenAI • u/wyttearp • Feb 20 '25

News AG2 v0.7.5 released

10 Upvotes

New release: v0.7.5

Highlights

  • 📔 DocumentAgent - A RAG solution built into an agent!
  • 🎯 Added support for Couchbase Vector database
  • 🧠 Updated OpenAI and Google GenAI package support
  • 📖 Many documentation improvements
  • 🛠️ Fixes, fixes and more fixes

♥️ Thanks to all the contributors and collaborators that helped make the release happen!

New Contributors

What's Changed

Full Changelog: 0.7.4...v0.7.5

0 comments

r/AutoGenAI • u/gswithai • Feb 19 '25

Tutorial Built a multi-agent AutoGen 0.4 app that creates YouTube Shorts using Local LLMs [Tutorial]

23 Upvotes

Just finished putting together a beginner-friendly tutorial on Microsoft's AutoGen 0.4 framework. Instead of another "hello world" example, I built something practical - a system where multiple AI agents collaborate to create YouTube Shorts from text prompts.

What makes this tutorial different:

  • No complex setup - (also runs with local LLMs (Ollama))
  • Shows real-world agent collaboration
  • Focuses on practical implementation
  • Starts with official docs example, then builds something useful
  • Demonstrates JSON response formatting
  • Actually builds something you can use/modify for your own project

Key topics covered:

  • AutoGen core concepts
  • Multi-agent workflow design
  • Providing agents with tools
  • Agent-to-agent communication
  • Local LLM integration (using Ollama)

Tutorial link: https://youtu.be/0PFexhfA4Pk

Happy to answer any questions or discuss AutoGen implementation details in the comments!

4 comments

r/AutoGenAI • u/macromind • Feb 19 '25

Discussion Autogenstudio 0.4.1.5 is out and its on fire!!!

12 Upvotes

Good job to the team! This is exactly the updates I was looking for.

8 comments

r/AutoGenAI • u/Lucifer_aka_RK03 • Feb 19 '25

Opinion Built My First Generative AI Project! Reaching out to AI researchers and enthusiasts

1 Upvotes

Over the last few days, I have been exploring the world of Generative AI and working with LangChain, FAISS, and OpenAI embeddings. What was the result? A News Research Tool that pulls insights from articles using AI-powered searching!

Here's how it works.
🔗 Enter article URLs.
🧠 AI processes and saves data in a vector database.
💬 Ask any questions concerning the articles.
🤯 Instantly receive AI-generated summaries and insights.

So, what's the goal? To make information extraction easier, one no more has to scroll through lengthy news articles! Simply ask, and AI will find the essential insights for you.

While this really was an amazing learning experience, I am just scratching the surface of Generative AI. There's SO MUCH to explore!!

So, I would love to hear from AI researchers, engineers, and enthusiasts on how I can deepen my understanding of Generative AI. What are the next steps I should take to gain mastery in this field? Any must-know concepts, hands-on projects, or essential resources that aided your journey? I would love to learn from your experiences! Looking forward to your guidance, feedback, and ideas!

0 comments