Showing 4 open source projects for "report builder python"

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  • Context for your AI agents Icon
    Context for your AI agents

    Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.

    Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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  • 1
    tuptime

    tuptime

    Total uptime command

    Report historical and statistical running time of system and other components, keeping it between reboots. Like uptime command but with more interesting output. NOTE: Tuptime was completely rewriten in python and now its available in https://github.com/rfrail3/tuptime
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  • 2
    Analysis tools for scale test data generated by The Grinder.
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  • 3
    Testing of the stability and quality of a network connection. This application helps users in testing the quality of a network connection and in sending feedback to the ISP.
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  • 4
    ClusterScores is a cluster benchmarking tool which automate compile, benchmark, and report benchmarking on cluster. This tool integrates other standard cluster benchmark tools such as HPL, Stream, Netpipe, Iperf, Bonnie, IOZone, etc...
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  • Cloud data warehouse to power your data-driven innovation Icon
    Cloud data warehouse to power your data-driven innovation

    BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.

    BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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