LLM-powered Crypto Trading Framework with Vision AI chart analysis, real-time Neural Engine, and a live monitoring dashboard at semanticsignal.qrak.org. Features memory-augmented reasoning and professional risk metrics.
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+10
STARS · LAST 30 DAYS
1
PER DAY
#1,804
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +10 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +3 | +10 |
LLM_trader gained 10 stars in the last 30 days, about 1 a day, and now has 133. It is about 2 years old and has averaged roughly 67 stars a year. It ranks #1,804 among Python repositories and #14,410 across all languages on GitHubRepo.
Trending Record
1
DAYS ON TRENDING
#13511
BEST RANK
Oct 14, 2026
FIRST APPEARANCE
Active
STATUS TODAY
LLM_trader has maintained a continuous presence across global trending indexes, peaking at #13511. Below is the 30-day activity profile:
💡 Overview
LLM_trader is an open-source project written in Python: LLM-powered Crypto Trading Framework with Vision AI chart analysis, real-time Neural Engine, and a live monitoring dashboard at semanticsignal.qrak.org. Features memory-augmented reasoning and professional risk metrics.
Engineered for speed, consistency, and developer ease, it solves common hurdles in ai, algorithmic-trading, algorythmic-trading. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install LLM_trader⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
LLM_trader coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with LLM_trader.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install LLM_trader using your package manager: `pip install LLM_trader`
Initialize your project workspace or configuration file for LLM_trader.
Import LLM_trader into your codebase or invoke it directly from your terminal.
Execute your test suite or run `LLM_trader --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
qrak/LLM_trader is currently ranked #14,410 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #14,360 | paddor/omq.rs | Rust | ★ 134 | Compare ↗ |
| #14,360 | Tomotsugu-dev/Hindsight | Rust | ★ 134 | Compare ↗ |
| #14,360 | goduni/unissh | Rust | ★ 134 | Compare ↗ |
| #14,360 | huanglvjing/spotpatch | TypeScript | ★ 134 | Compare ↗ |
| #14,360 | fzakaria/omnibin | Python | ★ 134 | Compare ↗ |
| #14,410 | qrak/LLM_trader This Project | Python | ★ 133 | |
| #14,410 | springbok/smerf | Ruby | ★ 133 | Compare ↗ |
| #14,410 | simonw/djng | Python | ★ 133 | Compare ↗ |
| #14,410 | ntoll/workflow | Python | ★ 133 | Compare ↗ |
| #14,410 | apache/roller | Java | ★ 133 | Compare ↗ |
| #14,410 | ericholscher/django-kong | Python | ★ 133 | Compare ↗ |
Frequently Asked Questions
What does LLM_trader do? +
LLM-powered Crypto Trading Framework with Vision AI chart analysis, real-time Neural Engine, and a live monitoring dashboard at semanticsignal.qrak.org. Features memory-augmented reasoning and professional risk metrics.
What language is LLM_trader written in? +
The primary language is Python. Topics include: ai, algorithmic-trading, algorythmic-trading, anthropic, cryptocurrency.
Is LLM_trader actively maintained? +
Yes, the last recorded push was on Oct 14, 2026 with 0 open issues being tracked.
How many stars does LLM_trader have? +
LLM_trader has 133 stars and 46 forks on GitHub.
How does LLM_trader rank among GitHub repositories? +
With 133 stars, qrak/LLM_trader is ranked #14,410 globally across all repositories tracked on GitHubRepo and #1,804 among Python projects.
What license is LLM_trader distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
