​From sgcWebSockets 2024.10.0 you can use the OpenAI Assistants to search in your own files instead of using the generic model.

File Search augments the Assistant with knowledge from outside its model, such as proprietary product information or documents provided by your users. OpenAI automatically parses and chunks your documents, creates and stores the embeddings, and use both vector and keyword search to retrieve relevant content to answer user queries.

Supported Files

Supported files

For text/ MIME types, the encoding must be one of utf-8, utf-16, or ascii.

File format	MIME type
.c	text/x-c
.cpp	text/x-c++
.cs	text/x-csharp
.css	text/css
.doc	application/msword
.docx	application/vnd.openxmlformats-officedocument.wordprocessingml.document
.go	text/x-golang
.html	text/html
.java	text/x-java
.js	text/javascript
.json	application/json
.md	text/markdown
.pdf	application/pdf
.php	text/x-php
.pptx	application/vnd.openxmlformats-officedocument.presentationml.presentation
.py	text/x-python
.py	text/x-script.python
.rb	text/x-ruby
.sh	application/x-sh
.tex	text/x-tex
.ts	application/typescript
.txt	text/plain

Step 1: Create a new Assistant with File Search Enabled

Create a new assistant with file_search enabled in the tools parameter of the Assistant. 

Once the file_search tool is enabled, the model decides when to retrieve content based on user messages.

Step 2: Upload files and add them to a Vector Store​

To access your files, the file_search tool uses the Vector Store object. Upload your files and create a Vector Store to contain them. 

Step 3: Create a run and check the output​

Now, create a Run and observe that the model uses the File Search tool to provide a response to the user's question. 

Video

Sample Delphi Project