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Victor Dibia 9494ac97a0
AGS Improvements (Add Test Button in Team Builder View + Others) (#5416) 
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https://microsoft.github.io/autogen/docs/Contribute before opening a
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## Why are these changes needed?

- Add ability to test teams in Team Builder view 
- Update Gallery (add deep research default team, fix bug with gallery
serialization)
- UI fixes 
   -  improve drag drop component experience 
- improve new session experience (single click rather than 3 clicks to
create a session)
   - fix bug with stop reason not being shown in some cases

<img width="1738" alt="Image"
src="https://github.com/user-attachments/assets/4b895df2-3bad-474e-bec6-4fbcbf1c4346"
/>

<img width="1761" alt="Image"
src="https://github.com/user-attachments/assets/65f52eb9-e926-4168-88fb-d2496c159474"
/>

<!-- Please give a short summary of the change and the problem this
solves. -->

## Related issue number

Closes #5392

<!-- For example: "Closes #1234" -->

## Checks

- [ ] I've included any doc changes needed for
https://microsoft.github.io/autogen/. See
https://microsoft.github.io/autogen/docs/Contribute#documentation to
build and test documentation locally.
- [ ] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [ ] I've made sure all auto checks have passed.
 		2025-02-07 23:37:44 +00:00
..
docs AGS Improvements (Add Test Button in Team Builder View + Others) (#5416) 2025-02-07 23:37:44 +00:00
src/autogen_core Added the Claude family of models to ModelFamily (#5443) 2025-02-07 23:27:14 +00:00
tests Memory component base (#5380) 2025-02-05 16:07:27 -08:00
.gitignore API documentation page flattening (#4556) 2024-12-04 18:24:07 -08:00
LICENSE-CODE Include license file in package (#3703) 2024-10-09 15:01:09 -04:00
README.md Make package readmes slightly less empty (#4961) 2025-01-09 10:44:13 -08:00
pyproject.toml chore: update package versions to 0.4.5 and remove deprecated requirements (#5280) 2025-01-31 01:52:45 +00:00

README.md

AutoGen Core

AutoGen core offers an easy way to quickly build event-driven, distributed, scalable, resilient AI agent systems. Agents are developed by using the Actor model. You can build and run your agent system locally and easily move to a distributed system in the cloud when you are ready.