This article explores TimeMixer, a new time series forecasting model, and its implementation. The article delves into its inner workings and provides a benchmark comparison with other models.
An extension for Oobabooga's Text-Generation Web UI that retrieves and adds web content to the context of prompts for more informative AI responses.
This article demonstrates how to use Pandas plotting capabilities for common data visualization tasks, suggesting that Pandas can be sufficient for routine EDA without relying on libraries like Matplotlib.
Explores the performance benefits of running Python without the Global Interpreter Lock (GIL), using the new experimental Python 3.13.0b4 pre-release with the --disable-gil flag. Discusses how this change can lead to faster execution times for CPU-intensive tasks in data science and machine learning.
This article explains how to run inference on a YOLOv8 object detection model using Docker and create a REST API to orchestrate the process. It includes code implementation and a detailed README in the author's GitHub repository for running the API via REST with Docker.
This JavaScript guide demonstrates the basics of E2B: connecting to an LLM, generating Python code, and executing it securely in an E2B sandbox.
- Composio: Streamline agent development with tool integrations.
- Julep: Build stateful AI agents with efficient context management.
- E2B: Secure sandbox for AI execution with code interpreter capabilities.
- Camel-ai: Framework for building and studying multi-agent systems.
- CopilotKit: Integrate AI copilot features into React applications.
- Aider: AI-powered pair-programmer for code assistance and repo management.
- Haystack: Composable pipeline framework for RAG applications.
- Pgvectorscale: High-performance vector database extension for PostgreSQL.
- GPTCache: Semantic caching solution for reducing LLM costs.
- Mem0 (EmbedChain): Add persistent memory to LLMs for personalized interactions.
- FastEmbed: Fast and lightweight library for embedding generation.
- Instructor: Streamline LLM output validation and extraction of structured data.
- LiteLLM: Drop-in replacement for OpenAI models, supporting various providers
- Julep: Build stateful AI agents with efficient context management.
- E2B: Secure sandbox for AI execution with code interpreter capabilities.
- Camel-ai: Framework for building and studying multi-agent systems.
- CopilotKit: Integrate AI copilot features into React applications.
- Aider: AI-powered pair-programmer for code assistance and repo management.
- Haystack: Composable pipeline framework for RAG applications.
- Pgvectorscale: High-performance vector database extension for PostgreSQL.
- GPTCache: Semantic caching solution for reducing LLM costs.
- Mem0 (EmbedChain): Add persistent memory to LLMs for personalized interactions.
- FastEmbed: Fast and lightweight library for embedding generation.
- Instructor: Streamline LLM output validation and extraction of structured data.
- LiteLLM: Drop-in replacement for OpenAI models, supporting various providers
This article introduces Path-Swarm and Super-Swarm, new techniques for creating swarm charts using circle arrangements for data visualization. The author, Nick Gerend, discusses two primary swarm techniques and some extensions for rapid visual exploration of data. Written for Towards Data Science.
Learn to build modular Flask applications using Jinja and templates. This article covers what Jinja is, how to create templates, and the benefits of using templates and the Jinja template engine. The article includes code examples and a GitHub link to the source code.
This article provides a guide on how to build routes in Flask, a Python web framework. It covers topics such as URL routing, the features of Flask, and its suitability for production-level web applications.
