343 lines
4.2 KiB
Markdown
343 lines
4.2 KiB
Markdown
# Local AI Coding Environment Implementation Plan
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## Objective
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Build a local-first AI coding environment on a Windows 11 workstation with the following requirements:
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### Hardware
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* NVIDIA RTX 5070 Ti 12GB VRAM
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* 64GB+ system RAM (if available)
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* Windows 11
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* WSL2 Ubuntu
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* VS Code
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### Existing Software
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* Ollama installed and operational
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* Qwen3-Coder 30B installed in Ollama
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* Claude Code CLI installed
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* Git installed
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### Constraints
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* Source code is confidential.
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* All code must remain local by default.
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* Cloud models may be used only as an optional fallback.
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* Minimize API costs.
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* Support large codebases.
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---
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# Target Architecture
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```text
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VS Code
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+---- Continue Extension
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+---- Claude Code CLI
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+---- Aider
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v
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Ollama
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v
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Qwen3-Coder 30B
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```
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---
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# Project Goals
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Implement and validate the following workflows.
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## Workflow 1: Local Chat
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Developer can:
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* Ask coding questions
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* Explain code
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* Generate code
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* Review code
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using:
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```text
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VS Code
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+
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Continue
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+
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Ollama
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+
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Qwen3-Coder 30B
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```
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---
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## Workflow 2: Local Agent
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Developer can:
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* Refactor code
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* Create files
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* Modify files
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* Run git-aware edits
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using:
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```text
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Aider
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+
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Ollama
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+
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Qwen3-Coder 30B
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```
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---
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## Workflow 3: Claude Code Optional
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Developer can:
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* Use Claude Code against local Ollama models
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* Compare behavior against Aider
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* Determine whether Claude Code provides additional value
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using:
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```text
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Claude Code
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+
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Ollama
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+
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Qwen3-Coder 30B
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```
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---
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# Deliverables
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Produce the following:
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## Deliverable 1
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Environment verification script.
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Verify:
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* Ollama installed
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* NVIDIA GPU visible
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* CUDA available
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* WSL functioning
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* Qwen3-Coder model available
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Expected output:
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```text
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PASS: Ollama
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PASS: GPU
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PASS: CUDA
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PASS: Qwen3-Coder
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```
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---
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## Deliverable 2
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Aider installation guide.
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Include:
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### Linux / WSL installation
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Commands:
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```bash
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pipx install aider-chat
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```
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or preferred installation method.
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### Ollama integration
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Configuration examples.
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### Verification steps
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Simple repository test.
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---
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## Deliverable 3
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Continue configuration.
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Create:
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### VS Code setup instructions
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Install Continue extension.
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### Model configuration
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Configure Continue to use:
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```text
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Ollama
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Qwen3-Coder 30B
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```
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### Example config files
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Include complete examples.
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---
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## Deliverable 4
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Claude Code local model integration.
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Research and implement the best available approach for:
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```text
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Claude Code
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->
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OpenAI-compatible endpoint
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->
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Ollama
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```
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Requirements:
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* Use officially supported methods where possible.
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* Avoid unsupported hacks.
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* Document limitations.
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* Provide rollback procedure.
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---
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## Deliverable 5
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Performance optimization.
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Analyze:
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### VRAM usage
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Qwen3-Coder 30B on RTX 5070 Ti 12GB.
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### Recommended quantization
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Evaluate:
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* Q4
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* Q5
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* IQ3
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Recommend the best balance between:
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* Quality
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* Speed
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* Memory usage
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---
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## Deliverable 6
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Benchmark suite.
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Create repeatable tests:
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### Test 1
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Generate a REST API.
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### Test 2
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Refactor a medium-sized module.
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### Test 3
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Write unit tests.
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### Test 4
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Debug a failing application.
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Measure:
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* Completion time
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* Accuracy
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* Token throughput
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* User effort
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Compare:
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```text
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Aider + Qwen3-Coder 30B
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Claude Code + Qwen3-Coder 30B
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Continue + Qwen3-Coder 30B
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```
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---
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# Preferred Outcome
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Primary development workflow:
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```text
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VS Code
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+
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Continue
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+
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Qwen3-Coder 30B
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```
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Agent workflow:
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```text
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Aider
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+
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Qwen3-Coder 30B
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```
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Optional advanced workflow:
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```text
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Claude Code
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+
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Qwen3-Coder 30B
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```
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---
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# Success Criteria
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The project is successful if:
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1. All code remains local.
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2. No cloud services are required.
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3. Developer can perform daily coding tasks locally.
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4. Aider successfully edits repositories.
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5. Continue provides a productive IDE experience.
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6. Claude Code local integration is evaluated and documented.
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7. Setup can be reproduced on a fresh machine.
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---
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# Final Report
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Produce a final report containing:
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* Architecture diagram
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* Installation steps
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* Configuration files
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* Benchmark results
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* Known limitations
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* Recommended workflow
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* Future upgrade path
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The report should be suitable for long-term maintenance and onboarding of additional developers.
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