Coding suggestion with my personal GPT using Open AI

Question

We have created our private GPT using our documents in Azure Open AI and Open AI Search. Now I would like it should search my documents (which it is doing) but I would also like to it should write down code in any language as per my prompt. Do you think it will be still Private to company or for code it is going to internet?

Answer 1

Hi @Rajeev Kumar Dave

Thank you for using the Microsoft Q&A forum.

The completions API provided by Azure OpenAI Service generates code based on the prompt provided by the user and the model trained on your private data.

As per the Transparency Note for Azure OpenAI Service, While the model's exposure to internet data during training may have some influence on its behavior, this influence can generally be made limited by Securely using Azure OpenAI On Your Data.

The GPT-3 series of models are pretrained on a wide body of publicly available free text data. This data is sourced from a combination of web crawling (specifically, a filtered version of Common Crawl, which includes a broad range of text from the internet and comprises 60 percent of the weighted pretraining dataset) and higher-quality datasets, including an expanded version of the WebText dataset, two internet-based books corpora and English-language Wikipedia. The GPT-4 base model was trained using publicly available data (such as internet data) and data that was licensed by OpenAI. The model was fine-tuned using reinforcement learning with human feedback (RLHF).

That said, Azure OpenAI Service offers Runtime parameters such as strictness that allow users to tailor the model's responses according to their specific requirements and data constraints. By adjusting the strictness parameter, you can fine-tune the model's behavior to prioritize adherence to your data and minimize external influences.

Determines the system's aggressiveness in filtering search documents based on their similarity scores. The system queries Azure Search or other document stores, then decides which documents to provide to large language models like ChatGPT. Filtering out irrelevant documents can significantly enhance the performance of the end-to-end chatbot. Some documents are excluded from the top-K results if they have low similarity scores before forwarding them to the model. This is controlled by an integer value ranging from 1 to 5. Setting this value to 1 means that the system will minimally filter documents based on search similarity to the user query. Conversely, a setting of 5 indicates that the system will aggressively filter out documents, applying a very high similarity threshold. If you find that the chatbot omits relevant information, lower the filter's strictness (set the value closer to 1) to include more documents. Conversely, if irrelevant documents distract the responses, increase the threshold (set the value closer to 5). This is the strictness parameter in the API, and set to 3 by default.

I hope the provided information helps in your use case. Thank you.

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Answer 2

Thank you for your explanation. This resolved my questions