TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @githubtrending · Post #15558 · Mar 12

#python#agentic_ai#agents#memory Hindsight is a top agent memory system that helps AI agents learn over time by storing facts, experiences, and mental models like human memory, beating rivals on LongMemEval benchmarks with 91.4% accuracy. Add it easily with 2 lines of code via Python or Node.js clients, using simple retain, recall, and reflect operations for Docker or embedded setups. You benefit by building smarter, consistent agents that reduce errors, cut hallucinations, handle long-term tasks, and personalize chats—saving time and boosting performance in production. https://github.com/vectorize-io/hindsight

Results

1 similar post found

Search: #parallelism

当前筛选 #parallelism清除筛选
djangoproject

@djangoproject · Post #118 · 08/08/2016, 11:44 AM

https://docs.python.org/3/library/multiprocessing.html multiprocessing is a package that supports spawning processes using an API similar to the threading module. The multiprocessing package offers both local and remote concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows. The #multiprocessing module also introduces #APIs which do not have analogs in the #threading#module. A prime example of this is the Pool object which offers a convenient means of parallelizing the execution of a function across multiple input values, distributing the input data across processes (data #parallelism). The following example demonstrates the common practice of defining such functions in a module so that child processes can successfully import that module. This basic example of data parallelism using Pool,