AI Assistant
The AIAssistant
class, an alternative to the OpenAI Assistant API, is designed for those who prefer using large language models (LLMs) other than those provided by OpenAI. It facilitates the creation of AI Assistants with several key benefits:
-
Visibility into Citations: It offers transparent access to the sources and citations used by the AI, enhancing the understanding and trustworthiness of its responses.
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Debugging Capabilities: Users have the ability to delve into and debug the AIโs processes, allowing for a deeper understanding and fine-tuning of its performance.
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Customizable Prompts: The class provides the flexibility to modify and tailor prompts according to specific needs, enabling more precise and relevant interactions.
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Chain of Thought Integration: It supports the incorporation of a โchain of thoughtโ approach, which helps in breaking down complex queries into simpler, sequential steps, thereby improving the clarity and accuracy of responses.
It is ideal for those who value customization, transparency, and detailed control over their AI Assistantโs functionalities.
Arguments
Name for your AI assistant
How the Assistant and model should behave or respond
Load existing AI Assistant. If you pass this, you donโt have to pass other arguments.
Existing thread id if exists
Embedchain pipeline config yaml path to use. This will define the configuration of the AI Assistant (such as configuring the LLM, vector database, and embedding model)
Add data sources to your assistant. You can add in the following format: [{"source": "https://example.com", "data_type": "web_page"}]
Anonymous telemetry (doesnโt collect any user information or userโs files). Used to improve the Embedchain package utilization. Default is True
.
Usage
For detailed guidance on creating your own AI Assistant, click the link below. It provides step-by-step instructions to help you through the process:
Guide to Creating Your AI Assistant
Learn how to build a customized AI Assistant using the AIAssistant
class.
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