TrendRadar
sansan0/TrendRadar
A news and trend monitor combining multi-source aggregation, AI analysis and notifications.
ToolAI.io · Chaîne GitHub
Suivez les dépôts AI open source actifs dans les domaines des LLM, des agents, de MCP, de RAG et du code, avec leur nombre d’étoiles et des informations vérifiées sur les projets.
Données du dépôt public
sansan0/TrendRadar
A news and trend monitor combining multi-source aggregation, AI analysis and notifications.
666ghj/MiroFish
Explore scenarios with interacting AI agents, knowledge graphs and generated reports.
jeecgboot/JeecgBoot
An enterprise low-code platform combining code generation, business workflows and AI features.
microsoft/graphrag
A graph-based text indexing and question-answering research project, now largely in maintenance mode.
Panniantong/Agent-Reach
A toolkit giving AI agents access to reading and search workflows across websites.
TauricResearch/TradingAgents
A multi-agent framework using language models to organize financial research workflows.
google/langextract
LLM-based structured extraction with source-text alignment and visualization for reviewable document processing.
berriai/litellm
The fastest, litest AI Gateway. Rust core with Python SDK. Call 100+ LLM APIs in OpenAI (or native) format with cost tracking, guardrails, load balancing, and logging [Bedrock, Azure, OpenAI, Anthropic, OpenAI, VertexAI, vLLM, Nvidia NIM]
theopenco/llmgateway
Route, manage, and analyze your LLM requests across multiple providers with a unified API interface.
vllm-project/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
taichuy/1flowbase
An open-source AI gateway that allows local agent clients to publish fusion-style multi-model workflows as OpenAI and Claude-compatible virtual models, providing full observability into traces, tokens, latency, and costs.
NVIDIA/TensorRT-LLM
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way
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