To enhance the responses of popular LLMs like OpenAI's chatGPT with organization-specific information, organizations require a process known as grounding. This involves using knowledge bases to ensure the information provided is relevant and authentic to the organization in question.
Integrating an organization's knowledge base with LLMs allows for more accurate and tailored responses, which is crucial for maintaining trust and reliance on AI systems in sensitive applications.
The grounding of LLMs not only improves their utility for organizational purposes but also enhances the overall user experience, as individuals feel more confident in the responses tailored for their specific context.
To start working with grounding in machine learning applications, you need libraries like openai and faiss-cpu, which facilitate the interaction and management of data, including the essential setting up of environment variables.
Collection
[
|
...
]