Chinese Financial Trading Decision-Making Framework Based on Multi-Agent Large Language Models | Open Source Daily No.773
hsliuping/TradingAgents-CN
Stars: 7.8k | License: Apache-2.0
TradingAgents-CN is a Chinese-language financial trading decision framework built on multi‑agent large language models and tailored specifically for Chinese users. It supports stock analysis and investment decision-making in the A-share, Hong Kong, and US stock markets.
Key Features
- Multi-agent collaborative architecture
- Integrates fundamental, technical, news, and social media analysts for structured debate and strong risk management.
- Cross-ecosystem support
- Native integration with OpenAI and Google AI, plus a multi-vendor, multi-model unified adapter architecture.
- Enterprise-grade toolchain
- Includes branch protection, security policies, test coverage, and deployment guidelines.
- Intelligent news filtering
- Multi-layered quality assessment ensures reliable information.
- Modern responsive web UI
- Offers real-time tracking, multidimensional reporting, and one-click export.
- Multi-market stock code formats
- Choice of research depth: quick analysis or comprehensive study.
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google/tunix
Stars: 844 | License: Apache-2.0
tunix is a JAX-based LLM post-training library designed for flexible fine-tuning and alignment.
Key Features
- Multiple post-training methods
- Supervised fine-tuning, reinforcement learning (RL), and knowledge distillation.
- Fine-tuning options
- Full-weight or parameter-efficient fine-tuning (PEFT), with LoRA/Q-LoRA layer support.
- Diverse RL algorithms
- PPO, GRPO, GSPO-token, and DPO for preference-based alignment.
- Advanced knowledge distillation
- Includes logits, attention transfer, and feature projection for model architecture alignment.
- Modular, reusable components
- Built-in distributed training support: data parallelism, FSDP, tensor parallelism — optimized for TPU acceleration.
Upcoming Enhancements:
Asynchronous rollout, multi-step interactions, new RL algorithms, improved scalability, and comprehensive tutorials.
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kyegomez/LongNet
Stars: 711 | License: Apache-2.0
LongNet implements "LongNet: Scaling Transformers to 1,000,000,000 Tokens".
Key Features
- Handles sequences > 1 billion tokens without degrading short-sequence performance.
- Linear complexity with logarithmic dependency on token count.
- Distributed trainer for ultra-long sequences.
- Sparse attention that replaces standard attention seamlessly.
- Strong performance on long sequence modeling and general language tasks.
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apache/cordova
Stars: 671 | License: NOASSERTION
Apache Cordova is a mobile application development framework for building cross-platform apps with HTML, CSS, and JavaScript.
Key Features
- Single codebase → multiple platforms
- Rich core plugins to extend capabilities
- Active community with CI/CD monitoring
- Comprehensive documentation and dedicated website
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Projects like TradingAgents-CN, tunix, and LongNet showcase advances in finance, training, and scalability.
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terhechte/Ebou
Stars: 609 | License: GPL-3.0
Ebou is a cross-platform Mastodon client written in Rust.
Key Features
- macOS Stable, Windows Beta, and theoretical Linux support
- Groups new messages by author, resembling modern messaging UIs
- Conversation view shows replies in context
- Supports timelines, notifications, and posts with video/image attachments
- Built with Dioxus UI — enabling functional cross-platform design
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