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Source channel @githubtrending · Post #15523 · Feb 25

#typescript#agent#agentic#agentic_framework#agentic_workflow#ai#ai_agents#bytedance#deep_research#harness#langchain#langgraph#langmanus#llm#multi_agent#nodejs#podcast#python#superagent#typescript DeerFlow 2.0 is an open-source super agent harness that orchestrates multiple sub-agents, memory systems, and sandboxed execution environments to accomplish complex tasks. Built on LangGraph and LangChain, it combines research, coding, and content creation capabilities with extensible skills and tools. The platform features isolated Docker containers for safe execution, long-term memory that learns your preferences, and the ability to spawn sub-agents that work in parallel on different task angles. You benefit from dramatically reduced research and automation time—tasks that typically take hours complete in minutes—while maintaining full transparency and control over agent decisions through human-in-the-loop collaboration. Whether you need deep research reports, data analysis, slide decks, or custom workflows, DeerFlow handles multi-step complexity without requiring extensive coding knowledge. https://github.com/bytedance/deer-flow

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Libreware

@libreware · Post #1330 · 09/05/2024, 08:53 PM

Interactive PDF Analysis (also called IPA) allows any researcher to explore the inner details of any PDF file. PDF files may be used to carry malicious payloads that exploit vulnerabilities, and issues of PDF viewer, or may be used in phishing campaigns as social engineering artefacts. The goal of this software is to let any analyst go deep on its own the PDF file. Via IPA, you may extract important payload from PDF files, understand the relationship across objects, and infer elements that may be helpful for triage of malicious or untrusted payloads. IPA/README.md at main · seekbytes/IPA · GitHub #PDF#PDFanalysis#Malware#Security