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Update README.md
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mmabrouk authored Dec 20, 2023
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Expand Up @@ -101,7 +101,7 @@ Agenta allows developers and product teams to collaborate and build robust AI ap

| Using an LLM App Template (For Non-Technical Users) | Starting from Code |
| ------------- | ------------- |
|1. [Create an application using a pre-built template from our UI](https://cloud.agenta.ai?utm_source=github&utm_medium=readme&utm_campaign=github)br />2. Access a playground where you can test and compare different prompts and configurations side-by-side.<br /> 3. Systematically evaluate your application using pre-built or custom evaluators.<br /> 4. Deploy the application to production with one click. |1. [Add a few lines to any LLM application code to automatically create a playground for it](https://docs.agenta.ai/tutorials/first-app-with-langchain) <br />2. Experiment with prompts and configurations, and compare them side-by-side in the playground. <br />3. Systematically evaluate your application using pre-built or custom evaluators. <br />4. Deploy the application to production with one click. |
|1. [Create an application using a pre-built template from our UI](https://cloud.agenta.ai?utm_source=github&utm_medium=readme&utm_campaign=github)<br />2. Access a playground where you can test and compare different prompts and configurations side-by-side.<br /> 3. Systematically evaluate your application using pre-built or custom evaluators.<br /> 4. Deploy the application to production with one click. |1. [Add a few lines to any LLM application code to automatically create a playground for it](https://docs.agenta.ai/tutorials/first-app-with-langchain) <br />2. Experiment with prompts and configurations, and compare them side-by-side in the playground. <br />3. Systematically evaluate your application using pre-built or custom evaluators. <br />4. Deploy the application to production with one click. |

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