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- OpenAI API keys with available credits. See [How to Obtain API Keys](#how-to-obtain-api-keys).
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- OpenAI API keys with available credits. See [How to Obtain API Keys](https://svilupp.github.io/PromptingTools.jl/dev/frequently_asked_questions#Creating-OpenAI-API-Key).
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```julia
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using AIHelpMe
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using AIHelpMe: pprint, load_index!
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#Either use the index explicitly
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aihelp(index_path, "what is DocsScraper.jl?")
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#set it as the "default" index, then it will be automatically used for every question
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load_index!(index_path)
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# or set it as the "default" index, then it will be automatically used for every question
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AIHelpMe.load_index!(index_path)
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pprint(aihelp("what is DocsScraper.jl?"))
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aihelp("what is DocsScraper.jl?") |> pprint
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```
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```julia
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[ Info: Updated RAG pipeline to `:bronze` (Configuration key:"textembedding3large-1024-Bool").
@@ -96,8 +94,9 @@ PromptingTools.jl, creates a vector store that can be utilized in RAG (Retrieval
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AIHelpMe.jl and PromptingTools.jl to provide efficient and relevant query retrieval, ensuring that the responses generated by the system are specific to the content in the created database.
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```
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Tip: Use `pprint` for nicer outputs with sources
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Tip: Use `pprint` for nicer outputs with sources and `last_result` for more detailed outputs (with sources).
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```julia
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using AIHelpMe: pprint, last_result
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print(last_result)
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using AIHelpMe: last_result
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# last_result() returns the last result from the RAG pipeline, ie, same as running aihelp(; return_all=true)
Copy file name to clipboardExpand all lines: docs/src/index.md
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## DocsScraper: "A document scraping and parsing tool used to create a custom RAG database for AIHelpMe.jl"
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# DocsScraper
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DocsScraper is a package designed to create "knowledge packs" from online documentation sites for the Julia language.
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It scrapes and parses the URLs and with the help of PromptingTools.jl, creates an index of chunks and their embeddings that can be used in RAG applications. It integrates with AIHelpMe.jl and PromptingTools.jl to offer highly efficient and relevant query retrieval, ensuring that the responses generated by the system are specific to the content in the created database.
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## Installation
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To install DocsScraper, use the Julia package manager and the package name:
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To install DocsScraper, use the Julia package manager and the package name (it's not registered yet):
- OpenAI API keys with available credits. See [How to Obtain API Keys](#how-to-obtain-api-keys).
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- OpenAI API keys with available credits. See [How to Obtain API Keys](https://svilupp.github.io/PromptingTools.jl/dev/frequently_asked_questions#Creating-OpenAI-API-Key).
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## Building the Index
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```julia
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using AIHelpMe
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using AIHelpMe: pprint, load_index!
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# Either use the index explicitly
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aihelp(index_path, "what is DocsScraper.jl?")
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-
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# or set it as the "default" index, then it will be automatically used for every question
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AIHelpMe.load_index!(index_path)
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# set it as the "default" index, then it will be automatically used for every question
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load_index!(index_path)
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pprint(aihelp("what is DocsScraper.jl?"))
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aihelp("what is DocsScraper.jl?")|> pprint
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```
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```julia
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[ Info: Updated RAG pipeline to `:bronze` (Configuration key:"textembedding3large-1024-Bool").
@@ -93,8 +92,8 @@ PromptingTools.jl, creates a vector store that can be utilized in RAG (Retrieval
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AIHelpMe.jl and PromptingTools.jl to provide efficient and relevant query retrieval, ensuring that the responses generated by the system are specific to the content in the created database.
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```
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Tip: Use `pprint` for nicer outputs with sources
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Tip: Use `pprint` for nicer outputs with sources and `last_result` for more detailed outputs (with sources).
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