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https://github.com/prajwalsrinvas/building_ai_applications_with_haystack

Code files from the deeplearning.ai short course on Haystack
https://github.com/prajwalsrinvas/building_ai_applications_with_haystack

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Code files from the deeplearning.ai short course on Haystack

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# Building AI Applications With Haystack 🛠️🤖

- Code files from the deeplearning.ai [short course](https://www.deeplearning.ai/short-courses/building-ai-applications-with-haystack) on [Haystack](https://docs.haystack.deepset.ai/docs/intro)
- [Certificate](https://learn.deeplearning.ai/accomplishments/104da721-2f22-4998-b7c1-c111d75165b9)

## Course content:

- Learn about the [core abstractions](Lesson_1.ipynb) and unique building blocks of the Haystack framework and see how these elements can be combined for various AI use cases.
- Build a [RAG pipeline](Lesson_2.ipynb) by using Haystack components, pipelines, and document stores.
- Create custom components in your pipeline by building a [Hacker News summarizer](Lesson_3.ipynb) that extends your app’s ability to access APIs.
- Use [conditional routing](Lesson_4.ipynb) to create a branching pipeline with a fall back to web-search when the LLM does not have the context needed to fully respond to the user’s query.
- Build a [self-reflecting agent](Lesson_5.ipynb) for named entity recognition with a Haystack pipeline that is able to loop using an output validator custom component.
- Create a [chat agent using OpenAI’s function-calling capabilities](Lesson_6.ipynb) which allow you to provide Haystack pipelines as tools to the LLM, enhancing that agent’s capabilities.