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docs: correct privacy and diagnostics claims
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README.md

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* **Verify before accepting.** Generated code can be compiled, tested, and corrected inside an isolated execution environment.
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* **Spend compute where it matters.** Straightforward edits take a shorter path, while harder tasks receive more candidates, reasoning, and validation.
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* **Run your own model.** Use a compatible GGUF model on NVIDIA, AMD, Apple Silicon, Vulkan, or CPU-supported hardware.
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* **Keep everything local.** Your repository, inference, test execution, and learned artifacts stay on your machine.
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* **Own the full stack.** ATLAS is open source, self-hosted, and has no required hosted API or per-token fee.
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* **Keep control local.** ATLAS does not intentionally upload your repository or prompts to a hosted model or ATLAS-operated service. Sandbox commands have outbound network access by default; set `ATLAS_SANDBOX_NET_INTERNAL=true` to disable it.
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* **Own the full stack.** ATLAS is open source and self-hosted. It requires no hosted model or third-party model-provider API key; a local per-installation service token authenticates ATLAS services.
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2. **[atlas-proxy](docs/ARCHITECTURE.md#3-atlas-proxy-outer-layer)** - Go agent loop that orchestrates the system.
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- [Tool-call routing](docs/ARCHITECTURE.md#tools) - classifies file operations by complexity tier
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- [Grammar enforcement](docs/ARCHITECTURE.md#grammar-enforcement) - GBNF schemas keep JSON output valid
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- [Grammar enforcement](docs/ARCHITECTURE.md#grammar-enforcement) - GBNF schemas strongly steer output toward the expected JSON shapes, with proxy-side recovery for malformed or truncated output
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- [BiasBusters](docs/ARCHITECTURE.md#tool-selection-bias-mitigations) - four composed mitigations (descriptions, grammar bans, system notes, ASA steering) that push the model toward `ast_edit` for structural code edits
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- [Safety limits](docs/ARCHITECTURE.md#safety-limits) - turn caps, token budgets, timeouts
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docs/GETTING_STARTED.md

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ATLAS is a local coding agent: a model running on your own GPU, wrapped in
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machinery that plans changes, verifies generated code in an isolated sandbox,
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and repairs what fails. Everything — inference, scoring, test execution, and
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learned state — stays on your machine. It is not a hosted service, there is
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no API key, and nothing is billed per token.
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and repairs what fails. ATLAS runs locally and does not require a hosted model
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or third-party model-provider API key. It creates a local per-installation
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service token for communication between ATLAS services, and nothing is billed
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per token.
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One expectation to set: a compact local model with verification is a
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different experience from a frontier hosted model. It shines on bounded,
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pinned-release and review-before-running variants if you'd rather not pipe a
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script into bash.
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One security fact worth knowing before your first task: the agent executes
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model-authored shell commands inside a locked-down sandbox container (not on
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your host), and your code never leaves the machine — but generated code is
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still code; review diffs before you commit them.
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One security fact worth knowing before your first task: ATLAS does not
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intentionally upload your repository or prompts to a hosted model or
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ATLAS-operated service. Model-authored shell commands run inside a locked-down
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sandbox container rather than on your host, but sandbox commands have outbound
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network access by default so toolchains can fetch dependencies. Set
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`ATLAS_SANDBOX_NET_INTERNAL=true` to disable sandbox egress. Review generated
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code, commands, and diffs before you commit them.
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## Install
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docs/README.md

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- **V3 pipeline / inner layer** — multi-candidate generation, scoring,
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sandbox verification, and repair for non-trivial files
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([ARCHITECTURE.md](ARCHITECTURE.md), [reports/V3_ABLATION_STUDY.md](reports/V3_ABLATION_STUDY.md)).
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- **Tiers (T0–T2)** — per-message and per-file complexity classification;
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T1 writes directly, T2 runs V3 ([ARCHITECTURE.md](ARCHITECTURE.md)).
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- **Tiers (T0–T3)** — per-message and per-file complexity classification;
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T0 is conversational, T1 writes directly, and T2/T3 use the V3 pipeline
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([ARCHITECTURE.md](ARCHITECTURE.md)).
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- **Geometric Lens, C(x) / G(x)** — energy-based candidate scoring over the
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model's own embeddings; per-model trained bundle
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([ARCHITECTURE.md](ARCHITECTURE.md), [../SUPPORT_MATRIX.md](../SUPPORT_MATRIX.md)).
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- **ASA** — activation-steering control vector nudging tool selection;
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per-model, opt-in until validated ([CLI.md](CLI.md), [PUBLISHING.md](PUBLISHING.md)).
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- **Sandbox** — isolated multi-language execution used for verification
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([ARCHITECTURE.md](ARCHITECTURE.md), [API.md](API.md)).
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- **GBNF grammar enforcement** — token-level constrained decoding that keeps
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tool calls valid JSON ([ARCHITECTURE.md](ARCHITECTURE.md)).
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- **GBNF grammar enforcement** — token-level constrained decoding that strongly
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steers tool calls toward the expected JSON schema, with proxy-side recovery
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for malformed or truncated output ([ARCHITECTURE.md](ARCHITECTURE.md)).
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docs/TROUBLESHOOTING.md

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## Quick Diagnostics
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Run these first to identify where the problem is:
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Start with `atlas doctor`, then use Compose status and logs to identify where
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the problem is:
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```bash
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# Docker Compose — check all services at once
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atlas doctor
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docker compose ps
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# GPU status
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nvidia-smi
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# Docker Compose logs (last 50 lines per service)
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docker compose logs --tail 50
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```
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`atlas doctor` is the preferred first diagnostic because it checks the host,
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configuration, and service health together. `docker compose ps` identifies
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services that failed to start, and the logs provide the next level of detail.
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Use a hardware-specific check only when the first results point to the
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inference backend:
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| Backend | Diagnostic command or check |
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|---|---|
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| NVIDIA CUDA | `nvidia-smi` |
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| AMD ROCm | Run `rocm-smi` and verify `/dev/kfd` exists. |
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| Apple Silicon / Metal | Run `atlas doctor`; if the native server is not listening, start `./scripts/atlas-llama-macos.sh` and inspect its foreground launcher output as described in [SETUP_MACOS.md](SETUP_MACOS.md#troubleshooting). |
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| Vulkan | Verify `/dev/dri` exists, then run `docker compose -f docker-compose.yml -f docker-compose.vulkan.yml exec llama-server vulkaninfo --summary`. |
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| CPU-only | Confirm the `docker-compose.vulkan.yml` and `docker-compose.cpu.yml` overlays are active. `atlas doctor` should warn and exit successfully rather than fail solely because no GPU exists. |
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For the per-service health-check curls, see [SETUP.md § Verify Installation](SETUP.md#verify-installation). The atlas-proxy health endpoint is the most useful for triage — it reports the status of all upstream services:
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```json
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{

proxy/README.md

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called to seed an explicit step list. 3 candidates sampled, scored
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heuristically, best plan pinned. The active step is injected into
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the system prompt every turn (`plan_reminder.go`).
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2. **Grammar-constrained generation**`llama-server` produces a JSON
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envelope: `tool_call`, `text`, or `done`. GBNF + `response_format:
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json_object` makes invalid output unrepresentable.
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2. **Grammar-constrained generation**`llama-server` is strongly steered
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toward a JSON envelope: `tool_call`, `text`, or `done`. GBNF +
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`response_format: json_object` constrains decoding, while the proxy recovers
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malformed or truncated output and treats parsing as fallible.
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3. **Tool dispatch + validation** — 14 tools (`read_file`,
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`outline_file`, `search_files`, `list_directory`, `find_file`,
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`write_file`, `edit_file`, `ast_edit`, `delete_file`, `move_file`,

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