Agents IA
TradingAgents-astock
A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等)，7位分析师基于A股规则的辩论决策，基于TradingAgents深度改造，适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear deb…
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Voir le guide →career-ops est un projet de agents IA open source, créé par career-ops-hq (career-ops-hq/career-ops sur GitHub). Il compte 73 398 étoiles sur GitHub et 13 797 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 3 octobre 2026.
Open-source AI job search agent and job finder: scan job boards, score each job 1-5 against your CV before you apply, tailor an ATS-friendly resume and cover…
Research, coding, browsing, or ops — agents work best with a clear goal.
From no-code builders to code-first SDKs, match complexity to the task.
Web search, code execution, and APIs are what make agents useful.
Watch the trace, approve consequential actions, iterate.
Scriptable from the terminal, so it drops straight into existing workflows.
Traces show exactly what the agent did and why.
Approval gates for actions that matter.
Long-term memory across sessions, not goldfish chat.
Specialized agents collaborate on bigger jobs.
Agents call real tools: browsers, terminals, APIs.
Download the source and move into the project folder.
git clone https://github.com/career-ops-hq/career-ops.git
cd career-opsEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at career-ops-hq/career-ops with 13,797 forks. Check the repo's contributors and recent commits to see how active maintenance is.
MIT licensed — use it commercially, no strings attached.
For bounded tasks with supervision, yes. Fully autonomous money-moves still need guardrails.
Sandboxing, approval gates, and least-privilege credentials.
Builders exist, but code-first frameworks go further.
A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等)，7位分析师基于A股规则的辩论决策，基于TradingAgents深度改造，适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear deb…
An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message…
Make humans and AI agents work as one team — open-source and self-hostable.
NVIDIA's security scanner for AI agent skills - check before you install
Scan your LLM for vulnerabilities before attackers do.
Exa's MCP server for web search and crawling — give your AI agent a live, high-quality web index.
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Convert PDFs, DOCX, and HTML into clean, AI-ready documents.
Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.