{
  "generated_at": "2026-08-13T19:31:03.163686Z",
  "comparison": "last_24_hours",
  "window_start": "2026-08-12T19:31:03.163686Z",
  "counts": {
    "new_tools": 12,
    "model_releases": 0,
    "moved_up": 0,
    "downgraded": 0,
    "risk_labels_changed": 0,
    "new_try_now_picks": 12
  },
  "highlights": [
    {
      "title": "Arize-ai/openinference",
      "url": "https://github.com/Arize-ai/openinference",
      "item_url": "/item/arize-ai-openinference/",
      "score": 8.5,
      "tier": "Gold",
      "risk": "low",
      "type": "Framework",
      "section": "Evaluation / Observability",
      "summary": "Arize-ai/openinference is a 1,140-star, Apache-2.0 OpenTelemetry SDK that instruments every major LLM / agent / vector-store framework (OpenAI, Anthropic, Gemini / Vertex, LangChain, LangGraph, LlamaIndex, Haystack, OpenAI Agents, Vercel AI, Pydantic AI, smolagents, MCP) and emits OTLP-compatible traces to any OTEL-compatible collector; native OTel semconv gen_ai.* span attributes"
    },
    {
      "title": "infiniflow/infinity",
      "url": "https://github.com/infiniflow/infinity",
      "item_url": "/item/infiniflow-infinity/",
      "score": 8.5,
      "tier": "Gold",
      "risk": "low",
      "type": "Framework",
      "section": "RAG / Vector / Retrieval",
      "summary": "infiniflow/infinity is a 4,669-star, Apache-2.0 AI-native database built for LLM applications that delivers incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text in a single C++20 system from the same team that built RAGFlow; HNSW indexing, BM25 + dense + sparse + multi-vector + tensor + native full-text combined; Python + C++ + Rust + TypeScript"
    },
    {
      "title": "AI-Hypercomputer/maxtext",
      "url": "https://github.com/AI-Hypercomputer/maxtext",
      "item_url": "/item/ai-hypercomputer-maxtext/",
      "score": 8.4,
      "tier": "Gold",
      "risk": "none",
      "type": "Framework",
      "section": "Training & Post-Training",
      "summary": "AI-Hypercomputer/maxtext is a 2,387-star, Apache-2.0 Google Cloud reference JAX LLM training stack -- the canonical TPU-native implementation that ships reference training + inference recipes for every major open model (Llama 2/3/4, DeepSeek V3.2 / R1 0528 / V3 0324, Qwen 2.5 / 3 MoE 30B/235B/480B / 3 Dense, Kimi K2 / K2-Thinking / K2.5 / K2.6, Mixtral, Mistral, Gemma 2/3, GPT-OSS 20B/120B)"
    },
    {
      "title": "compozy/compozy",
      "url": "https://github.com/compozy/compozy",
      "item_url": "/item/compozy-compozy/",
      "score": 8.4,
      "tier": "Gold",
      "risk": "low",
      "type": "Framework",
      "section": "Agent Infrastructure",
      "summary": "compozy/compozy is a 2,530-star, MIT 'operating system for AI agents' (CompozyOS) that wraps Claude Code, OpenClaw, Hermes, and Codex into a single Go-runtime agent OS handling loops / triggers / cron / memory / permissions / approvals / observability / glue scripts without hand-rolling each; browser-based supervisor, project-level shared memory, parallel loops; pkg.go.dev published; 144 forks"
    },
    {
      "title": "vshulcz/deja-vu",
      "url": "https://github.com/vshulcz/deja-vu",
      "item_url": "/item/vshulcz-deja-vu/",
      "score": 8.2,
      "tier": "Silver",
      "risk": "low",
      "type": "Tool",
      "section": "Agent Memory",
      "summary": "vshulcz/deja-vu is a 628-star, MIT agent-session search engine that indexes the months of session history Claude Code / Codex / Pi / Aider / etc. already wrote to disk before the user installed it; 84.9% hit@1 on LongMemEval-S, no LLM, no embeddings, no API key, fully local; single zero-dependency binary exposed over MCP for any agent harness; npm @vshulcz/deja-vu for the npm install path; 43"
    }
  ],
  "moved_up": [],
  "downgraded": [],
  "risk_changes": [],
  "build_id": "rr-20260813T19310316368-ce6328a012cd"
}