Impressive Performance Metrics
-
890+ Trusted Users: A growing user base that relies on Exthalpy's capabilities.
-
85% Reduced Latency: Significant improvement in response times.
-
88% Less Computation: Efficient use of computational resources.
-
178K+ Queries Processed: Demonstrating the platform's robust processing capacity.
Advanced Retrieval Techniques
Asynchronous Retrieval
Exthalpy employs parallel processing to request multiple webpages simultaneously, significantly speeding up data collection.
Data Preprocessing & Merging
High concurrency settings allow the crawler to handle multiple tasks at once, enhancing overall efficiency.
Local Embedding Setup
Utilizes HyperLLM to reduce resource consumption by reusing existing connections.
Dense Vector Semantic Retrieval
Implements memory of visited URLs to avoid redundant processing, saving time and resources.
Historical Dataset Management
Versatile design allows operation in various environments like Google Colab or Jupyter notebook without event loop issues.
Flexible Deployment Options
-
Cloud or Local Deployment: Available as both an API and an open-source Python library.
-
Easy Access: Accessible via API or installable through pip.
Community-Driven Development
Provides resources and community support for users to learn and maximize the use of Exthalpy.