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Join us at the upcoming Developer Roundtable on March 26th at 11 am ET | 4 pm CET. 📍
We will have 2 topics covered by the invited experts and open discussion as always!

Talks:

Demo on Documenting and Testing REST Call's by generating documentation and making scenario's for integration tests - presented by @Danny Wijnschenk , Application Developer, Winfo.
Cypress for web application testing - presented by @Pravin Barton , Senior Applications Developer, InterSystems

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Dear,

I'm trying to configure a new interface that reads HL7, transform them into FHIR messages and then send POST or PUT or DELETE depending on HL7 doc type.

1-I added an HL7 TCP service that reads ADTs messages

2a-Send ADTs to a process to transform them into SDA (using the following command: do ##class(HS.Gateway.HL7.HL7ToSDA3).GetSDA(request,.con))

2b-Extract the patient MRN and add it to the AdditionalInfo property (using the following request message class: HS.Message.XMLMessage)

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Hi Community!

As an AI language model, ChatGPT is capable of performing a variety of tasks like language translation, writing songs, answering research questions, and even generating computer code. With its impressive abilities, ChatGPT has quickly become a popular tool for various applications, from chatbots to content creation.
But despite its advanced capabilities, ChatGPT is not able to access your personal data. So we need to build a custom ChatGPT AI by using LangChain Framework:

Below are the steps to build a custom ChatGPT:

  • Step 1: Load the document

  • Step 2: Splitting the document into chunks

  • Step 3: Use Embedding against Chunks Data and convert to vectors

  • Step 4: Save data to the Vector database

  • Step 5: Take data (question) from the user and get the embedding

  • Step 6: Connect to VectorDB and do a semantic search

  • Step 7: Retrieve relevant responses based on user queries and send them to LLM(ChatGPT)

  • Step 8: Get an answer from LLM and send it back to the user

For more details, please Read this article

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