3 个仓库
Platforms for moving and syncing data between systems.
Explore 3 awesome GitHub repositories matching part of an awesome list · Data Integration Tools. Refine with filters or upvote what's useful.
LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows that manage state, memory, and tool execution. The project distinguishes itself through a durable execution runtime that maintains persistent state across long-running processes by checkpointing progress to external storage. It models agent workflows as directed graphs, allowing
Framework for developing applications powered by language models.
LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters
Syncs and exchanges data with external data engineering tools and columnar processing engines.
AdalFlow 是一个自主 AI 代理框架和 LLM 应用库,旨在构建模块化工作流。它作为一个模型无关的接口和 RAG 流水线编排器,允许用户开发 ReAct 代理,利用迭代推理和外部工具执行来解决复杂任务。 该项目通过一个提示词优化系统脱颖而出,该系统使用文本梯度下降自动优化提示词模板和少样本示例。它将模型反馈视为可微分信号,实现了一种 LLM 反向传播形式,从而根据评估指标迭代提高输出质量。 该框架涵盖了广泛的功能面,包括带有语义向量搜索和重排序的检索增强生成、用于可观测性的基于跨度的执行追踪,以及模式驱动的结构化解析。它为众多专有和开源模型提供商提供了统一的通信层,并支持将 Python 函数转换为标准化的工具接口。 该系统使用 Python 实现,并与 MLflow 集成以进行工作流跟踪和分析。
Modular library for building LLM-powered data applications.