[EP] Develop RAG Tool

[antfin]

Enable developers to create a RAG tool by selecting the LLM model and required prompts, choosing RAG techniques and parameters for parsing, cleaning, and enriching documents with metadata, and selecting the storage type for document handling.

As a developer, I want to select the LLM model and define the necessary prompts so that I can configure the RAG tool's foundational behavior.
•The system provides a list of available LLM models to choose from.
•The developer can define and configure prompts specific to the RAG tool.

As a developer, I want to select the RAG techniques and parameters for parsing, cleaning, and enriching documents with metadata so that the documents are processed accurately and comprehensively.
•The system allows the developer to choose from various RAG techniques.
•The developer can set parameters for parsing, cleaning, and metadata enrichment.

As a developer, I want to select the storage type for handling documents so that the RAG tool can efficiently store and retrieve data.
•The system provides options for different storage types (e.g., vector indexes, vector dbs…).
•The selected storage type is integrated with the RAG tool for data handling.

As a developer, I want to design a custom user interface for my LLM tool so that users can interact with it intuitively.
•The system offers tools for designing user interfaces, including forms and interactive elements.
•The designed interface can be linked to the LLM tool and prompt chain.

As a developer, I want to preview and test the RAG tool so that I can ensure it works as intended before deployment.
•The system provides a preview mode to test the RAG tool.
•Developers can interact with the tool in preview mode to verify functionality.

As a developer, I want to save my RAG tool configuration and deploy it so that users can start using it.
•The system allows developers to save their RAG tool configurations.
•The tool can be deployed and made accessible to users.