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It allows integration with Saga to enable the usage of On-prem language models as well as all of the out of the box Saga NLP algorithms to process natural language content.
It allows to calculate embedding vector from the query for semantic search, it can be used with Saga or directly with models like: Open AI and Sentence Transformer GTR.
Use Azure OpenAI chat-completion models (like gpt-35-turbo or ChatGPT) to answering user requests and queries with summaries, content classification, data extraction, etc. You design and configure the prompts and include whatever metadata or content from the user query to generate answers.
It is the executor of the semantic search in the search engine to fetch relevant data that could provide context for the prompt creation.
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