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Source channel @githubtrending · Post #15399 · Jan 7

#python#agent#agent_framework#browsecomp#deep_research#futurex#gaia#hle#research_agent#search_agent#xbench MiroThinker v1.5 is the top open-source AI search agent with a 256K context window and up to 400 tool calls per task for deep web research, code execution, and multi-step reasoning. It leads benchmarks like HLE-Text (39.2%), BrowseComp (69.8%), and GAIA (80.8%), beating other free agents at low cost. You benefit by getting accurate, real-world research help—like finding arXiv papers or solving complex queries—faster and cheaper than paid tools, with full open-source access on GitHub and Hugging Face. https://github.com/MiroMindAI/MiroThinker

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djangoproject

@djangoproject · Post #153 · 09/03/2016, 08:20 PM

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http://wla.berkeley.edu/~cs61a/fa11/lectures/streams.html In this chapter, we continue our discussion of real-world applications by developing new tools to process #sequential#data. In Chapter 2, we introduced a sequence interface, implemented in Python by built-in data types such as #tuple and #list. #Sequences supported two operations: querying their length and accessing an element by index. In Chapter 3, we developed a user-defined implementations of the sequence interface, the Rlist class for representing recursive lists. These sequence types proved effective for representing and accessing a wide variety of sequential #datasets.

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