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chore: typos in documentation (#55353)
<!-- Thank you for your contribution! Please review https://github.com/ray-project/ray/blob/master/CONTRIBUTING.rst before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? Fixes a few typos in the documentation. <!-- Please give a short summary of the change and the problem this solves. --> ## Related issue number <!-- For example: "Closes #1234" --> ## Checks - [x] I've signed off every commit(by using the -s flag, i.e., `git commit -s`) in this PR. - [ ] I've run `scripts/format.sh` to lint the changes in this PR. - [x] I've included any doc changes needed for https://docs.ray.io/en/master/. - [ ] I've added any new APIs to the API Reference. For example, if I added a method in Tune, I've added it in `doc/source/tune/api/` under the corresponding `.rst` file. - [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/ - Testing Strategy - [ ] Unit tests - [ ] Release tests - [ ] This PR is not tested :( --------- Signed-off-by: Pavitra Bhalla <[email protected]> Signed-off-by: pavitrabhalla <[email protected]>
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doc/source/ray-overview/examples/e2e-rag/notebooks/05_Improve_RAG_with_Prompt_Engineering.ipynb

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"This section provides detailed guidance on prompt engineering specifically tailored for Retrieval-Augmented Generation (RAG) applications. Here, we explore best practices, strategies, and tips for designing effective prompts that optimize the integration of external knowledge sources with generative models.\n",
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"The purose of this tutorial is to build a RAG that can answer questions related to Ray or Anyscale, but note that **we have ingested 100 docs in Notebook #2, but we only have 5 documents of Anyscale which are all related to the `Anyscale Jobs`.**. this is just for demo pupose But in real production, it's very easy to ingest more doucments and build a production ready RAG application using this improved prompts showed in the tutorial."
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"The purpose of this tutorial is to build a RAG that can answer questions related to Ray or Anyscale, but note that **we have ingested 100 docs in Notebook #2, but we only have 5 documents of Anyscale which are all related to the `Anyscale Jobs`.**. this is just for demo pupose But in real production, it's very easy to ingest more doucments and build a production ready RAG application using this improved prompts showed in the tutorial."
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"## Initlize the RAG components\n",
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"## Initialize the RAG components\n",
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"### Problem 2: Irerelvant User Request\n",
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"### Problem 2: Irrelevant User Request\n",
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"Users may sometimes ask irrelevant questions, which could lead to misuse of the chatbot. A basic prompt may not be sufficient to handle such requests effectively. Therefore, it is important to define the scope of the LLM’s responses to ensure appropriate and meaningful interactions."
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"### 2. Irerelvant user request - Handled\n",
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"### 2. Irrelevant user request - Handled\n",
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"Now RAG can handle and deflect the Irerelvant user request."
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"Now RAG can handle and deflect the Irrelevant user request."
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"## Obeservations\n",
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"## Observations\n",
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"As you can see above, the content of the response is rendered correctly with citations.\n",
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