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Add semantic kernel vector store approaches #106

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@milderhc milderhc commented Dec 4, 2024

Purpose

  • Adding vector store functionality to the Ask and Chat sections. Using hybrid search + semantic ranker, query captions are not available as the semantic kernel maps the documents and returns them without that extra info.
  • Updated Azure AI Search SDK version

Does this introduce a breaking change?

[ ] Yes
[x] No

Pull Request Type

What kind of change does this Pull Request introduce?

[ ] Bugfix
[x] Feature
[ ] Code style update (formatting, local variables)
[ ] Refactoring (no functional changes, no api changes)
[ ] Documentation content changes
[ ] Other... Please describe:

How to Test

  • Get the code
git clone [repo-address]
cd [repo-name]
git checkout [branch-name]
npm install
  • Test the code

What to Check

Verify that the following are valid

  • ...

Other Information

@milderhc milderhc requested a review from brunoborges as a code owner December 4, 2024 22:09
String indexName;

@Value("${openai.chatgpt.deployment}")
private String gptChatDeploymentModelId;
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not required. we can delete this

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I still use these variables. The embedding generation service and chat completion service in SK need their models as input.

);

// STEP 3: Retrieve relevant documents using keywords extracted from the chat history
String conversationString = ChatGPTUtils.formatAsChatML(questionOrConversation.toOpenAIChatMessages());
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I think this is a duplication. let's use SK ChatHistory we have in conversation variable at line 72

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Not in this case, ChatGPTUtils.formatAsChatML receives a list of List<ChatRequestMessage> which is not available from the ChatHistory. ChatHistory has List<ChatMessageTextContent>.

app/frontend/src/pages/chat/Chat.tsx Outdated Show resolved Hide resolved
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2 participants