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Source channel @olddriverGDstudy · Post #10 · Mar 17

#语录 请大家做个素质狼友: 1 人和人需要的是相互尊重的,希望我们群的狼友能尊重老师。在相互尊重的情况下我相信大家会得到更好的体验。 2 请大家预约老师后如有变化应该尽快,提前的告知老师,因为老师每天的课时都是有限的。如果不提前告知也很可能再也约不到这位老师或者进入妹子们的黑名单。 3 请大家遵守行规(按照行规S了但是可以待够时间,享受下老师的服务和老师聊聊天。就算时间到了没S也算是课时结束了,如果第一次结束了又做第二次那么不管S没有都应该按PP付费。),一般情况下P是60分钟 PP是90分钟 时间没到老师赶你走是老师的问题,但是超时就是狼友的问题,关于超时最好和老师协商一下,因为老师如果后面有学生,那么超时就会影响到后面的学生,很可能会给老师带来不必要的麻烦。如果想约PP的学生最好在预约的时候就给老师讲清楚。 4 关于等候的时间,有些时候有很多不可控因素比如学生迟到,学生学习时间长等因素,希望大家在等候的时候能稍微耐心点,个人感觉等候时间在20-30分钟还是可接受的。 5 希望我们群的兄弟都能做个素质狼友,当然我们也会对群里的各位老师有所要求,大家对老师有什么不满意的都可以在群里直接投诉,或者找管理员投诉。

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GitHub Trends

@githubtrending · Post #14706 · 05/14/2025, 02:30 PM

#python#agents#knowledge_graph#llm#llm_agent#rag#search#search_agent#vector_database Airweave is a tool that helps make information from apps and databases easily accessible to AI agents. It connects over 100 data sources with minimal coding, allowing for fast data synchronization and semantic search. This means you can quickly turn app data into useful knowledge for AI agents, making them smarter and more efficient. It's especially helpful for tasks like customer support or generating reports, as it ensures AI agents have the most accurate and up-to-date information. https://github.com/airweave-ai/airweave

GitHub Trends

@githubtrending · Post #15547 · 03/07/2026, 01:30 PM

#python#agent_memory#financial_forecasting#future_prediction#knowledge_graph#llms#multi_agent_simulation#public_opinion_analysis#python3#social_prediction#swarm_intelligence MiroFish is a simple AI tool that predicts anything by creating a digital world from your data like news, policies, or stories. Upload seed info and describe what you want to predict; it builds thousands of smart agents with personalities and memories to interact, simulate futures, and give you a detailed report plus chat access. You benefit by testing decisions risk-free—like policy impacts or story endings—making smart choices or fun ideas win through safe, accurate previews. https://github.com/666ghj/MiroFish

GitHub Trends

@githubtrending · Post #15168 · 09/25/2025, 12:30 PM

#python#ai#context#embedded#faiss#knowledge_base#knowledge_graph#llm#machine_learning#memory#nlp#offline_first#opencv#python#rag#retrieval_augmented_generation#semantic_search#vector_database#video_processing Memvid lets you store millions of text pieces inside a single MP4 video file using QR codes, making your data 50-100 times smaller than usual databases. You can search this video instantly in under 100 milliseconds without needing servers or internet after setup. It works offline, is easy to use with simple Python code, and supports PDFs and chat with your data. The upcoming version 2 will add features like continuous memory updates, shareable capsules, fast local caching, and better video compression, making your AI memory smarter, faster, and more flexible. This means you get a powerful, portable, and efficient way to manage and search huge knowledge bases quickly and easily. https://github.com/Olow304/memvid

GitHub Trends

@githubtrending · Post #15350 · 12/21/2025, 11:30 AM

#rust#ai#change_data_capture#context_engineering#data#data_engineering#data_indexing#data_infrastructure#data_processing#etl#hacktoberfest#help_wanted#indexing#knowledge_graph#llm#pipeline#python#rag#real_time#rust#semantic_search **CocoIndex** is a fast, open-source Python tool (Rust core) for transforming data into AI formats like vector indexes or knowledge graphs. Define simple data flows in ~100 lines of code using plug-and-play blocks for sources, embeddings, and targets—install via `pip install cocoindex`, add Postgres, and run. It auto-syncs fresh data with minimal recompute on changes, tracking lineage. **You save time building scalable RAG/semantic search pipelines effortlessly, avoiding complex ETL and stale data issues for production-ready AI apps.** https://github.com/cocoindex-io/cocoindex

GitHub Trends

@githubtrending · Post #14791 · 06/05/2025, 12:30 PM

#python#ai#ai_agents#ai_memory#cognitive_architecture#cognitive_memory#contributions_welcome#good_first_issue#good_first_pr#graph_database#graph_rag#graphrag#help_wanted#knowledge#knowledge_graph#neo4j#open_source#openai#rag#vector_database Cognee is an open-source AI memory engine that helps improve how AI systems understand and process data. It mimics human cognitive processes, creating "memories" from various data types like text and images. This enhances the accuracy of large language models (LLMs) and allows them to recall past interactions and documents. Cognee is scalable, cost-effective, and integrates easily with existing systems, making it a valuable tool for developers seeking to boost AI performance without relying on expensive APIs. https://github.com/topoteretes/cognee