jamesob
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local-llm
A comprehensive guide for building and configuring a high-end local machine to run state-of-the-art LLMs, with detailed hardware choices, BIOS tuning, and Docker-based model serving.
AI repository intelligence
FR-AI / ANALYSISWhy it is worth attention
It addresses AI session context limits with automated monitoring and cost optimization for DeepSeek APIs, packed in a one-click install and recovery workflow.
Who it is for
- Developers using Claude Code for long or interrupted sessions
- DeepSeek V4 users who want to manage token costs based on peak pricing
- Users needing a repeatable setup across multiple machines
- Developers who value real-time visibility into context window usage
Use cases
- Handing off a complex conversation to a new Claude Code session without losing progress
- Monitoring context usage to avoid hitting the limit unexpectedly
- Estimating runtime costs using DeepSeek V4 dynamic pricing
- Quickly restoring the same tooling on a different computer
Strengths
- Real-time context progress bar with threshold-based warnings (60%, 75%, 85%)
- Built-in DeepSeek V4 peak/off-peak pricing calculation for cost awareness
- One-command install and computer migration script that preserves safety (no token backup)
- Modular design: separate skill and status line, no automatic clear/compact to avoid data loss
Considerations
- Only supports models mapped to DeepSeek Flash/Pro (not generic Claude models)
- Does not auto‑trigger clear, compact, or handoff commands – user must act on warnings
- Install script assumes PowerShell on Windows or bash on Unix; no native macOS graphical installer
README quick start
快速开始
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