GroundX: Building a RAG (Retrieval Augmentation) API Based on Real, Illusion-Free Data

General Introduction

GroundX is a full-stack solution designed for building real-data based LLM (Large Language Model) applications, specializing in building a full suite of services for RAG applications. It solves the phantom problem created by traditional vector databases when dealing with complex documents through dynamic chunking and context generation, helping developers parse, clean, introduce and store data, connect to data storage points, automatically generate metadata, and more.

GroundX offers powerful search and retrieval capabilities using an advanced search and sorting system to find hard-to-find content in the knowledge base. Its main commitment is to use encrypted cloud storage to keep users' data safe at rest and in transit. Additionally, with up to 12 million API calls, it processes data very quickly, making it ideal for smaller companies building segmentation models with complex documents.GroundX divides documents into coherent chunks through dynamic chunking technology and automatically generates the required context to help deep learning models understand the data.

Function List

• Dynamic chunking and context generation: Automatically chunks content and generates context to help LLM understand the data.
• Proprietary Search and Ranking: Provides high quality search results through proprietary search and ranking algorithms.
• Multi-format data support: Supports cloud storage and local files for multiple data formats.
• data security: Data is encrypted at rest and during transmission to ensure data security.
• Full Stack RAG Application Building: Provides a one-stop solution from data parsing, cleansing, storage to retrieval.
• Scoring of search results: Returns proprietary scores for each search, ensuring high quality results for LLM generation.

Using Help

Installation and Configuration

1. register an account: Visit the official GroundX website and register a new account.
2. Download SDK: Log in and download the SDK for your development environment.
3. Installing the SDK: Follow the instructions in the downloaded SDK package to install it.
4. Configuring the API Key: Configure the API key obtained from GroundX in your development environment.

data processing

1. Data upload: Upload your documents to GroundX's cloud storage or via the API interface.
2. data parsing: Use the parsing tools provided by GroundX to parse the document to produce a format suitable for LLM processing.
3. Dynamic chunking: GroundX automatically chunks document content and generates contextual information.

Search and retrieval

1. Building an Index: Build document indexes using GroundX's API to ensure fast retrieval.
2. Perform a search: Send search requests through the API to get high-quality retrieval results.
3. Scoring of results: Each search returns results with a proprietary score to help you filter for high-quality content.

Security and Privacy

1. data encryption: All uploaded data is encrypted at rest and in transit.
2. access control: Set strict access control policies to ensure that only authorized users can access the data.
3. Log Audit: Enable the log auditing function to record all data access and operation behaviors.

sample code (computing)

import groundx
# Initialize the client
client = groundx.Client(api_key='YOUR_API_KEY')
# Upload document
client.upload_document('path/to/your/document.pdf')
# search document
results = client.search('your search query')
# print results
for result in results.
print(result)

GroundX Payment Plan

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