Update README.md #69
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Update README.md #69
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softchris
commented
Feb 24, 2025
softchris
commented
- addressing issues with the text
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👋 Thanks for contributing @softchris! We will review the pull request and get back to you soon. |
| - **Azure AI Agent Service**: Provides more flexible models, such as directly calling open-source LLMs like Llama 3, Mistral, and Cohere. It offers stronger enterprise security mechanisms and data storage methods, making it suitable for enterprise applications. | ||
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| - **AutoGen**: Is an experiementation framework focused on leading-edge research on multi-agent systems. It is the best place to experiment and prototype sophisticated multi-agent sytems. |
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The word 'experiementation' is misspelled. It should be 'experimentation'.
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| - **AutoGen**: Is an experiementation framework focused on leading-edge research on multi-agent systems. It is the best place to experiment and prototype sophisticated multi-agent sytems. | |
| - **AutoGen**: Is an experimentation framework focused on leading-edge research on multi-agent systems. It is the best place to experiment and prototype sophisticated multi-agent systems. |
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| - **Azure AI Agent Service**: Is a platform and deployment service in Azure Foundry for agents. It offers building connectivity to services support by Azure Found like Azure OpenAI, Azure AI Search, Bing Search and code exectuition. | ||
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The word 'exectuition' is misspelled. It should be 'execution'.
Suggested change
| - **Azure AI Agent Service**: Is a platform and deployment service in Azure Foundry for agents. It offers building connectivity to services support by Azure Found like Azure OpenAI, Azure AI Search, Bing Search and code exectuition. | |
| - **Azure AI Agent Service**: Is a platform and deployment service in Azure Foundry for agents. It offers building connectivity to services support by Azure Found like Azure OpenAI, Azure AI Search, Bing Search and code execution. |
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| > Q: What makes AutoGen a better choice than Semantic Kernel and Azure AI Agent Service for this use case? | ||
| > A: AutoGen would be a good choice for this scenario, as it focuses on experimentation and building applications using the latest multi-agent patterns | ||
| > Q: I'm designing a building a application that I want to scale and use production or within my enterprise |
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The phrase 'I'm designing a building a application' is incorrect. It should be 'I'm designing and building an application'.
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| > Q: I'm designing a building a application that I want to scale and use production or within my enterprise | |
| > Q: I'm designing and building an application that I want to scale and use production or within my enterprise |
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| > A: A create choice is to build you application in Semantic Kernel first, and use Azure AI Agent Service to deploy you agent. This means you can easily perist your agents while still having the power to build multi-agent systems in Semantic Kernel. Semantic also has a connector in AutoGen to make it easy to use both frameworks together. | ||
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The phrase 'A create choice is to build you application' is incorrect. It should be 'A great choice is to build your application'.
Suggested change
| > A: A create choice is to build you application in Semantic Kernel first, and use Azure AI Agent Service to deploy you agent. This means you can easily perist your agents while still having the power to build multi-agent systems in Semantic Kernel. Semantic also has a connector in AutoGen to make it easy to use both frameworks together. | |
| > A: A great choice is to build your application in Semantic Kernel first, and use Azure AI Agent Service to deploy your agent. This means you can easily persist your agents while still having the power to build multi-agent systems in Semantic Kernel. Semantic also has a connector in AutoGen to make it easy to use both frameworks together. |
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koreyspace
approved these changes
Feb 24, 2025
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