Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

llmdbg

llmdbg is an early-stage debugger for stepping through language-model layers and presenting human-readable interpretations of internal vectors. It speaks the Debug Adapter Protocol so editor integrations can use a standard debugger UI.

The current prototype includes real GPT-2 Small loading, layer-state capture, logit-lens interpretations, and a VS Code debug extension. A deterministic built-in trace remains available when no model is configured.

pip install --pre llmdbg
llmdbg --version

VS Code prototype

Build and install the extension:

cd vscode-extension
npm install
npm run package
code --install-extension llmdbg-0.0.1.vsix

Create a gpt2.llmdbg file in the workspace:

model = "openai-community/gpt2"
revision = "main"
device = "cuda"
dtype = "bfloat16"
prompt = "The capital of France is"
token = 3
stop_on_entry = false

submodule = "token_embedding"

layer = 0
submodule = "transformer.h.0.attention"
submodule = "transformer.h.0.mlp"

layer = 1
submodule = "transformer.h.1.attention"
submodule = "transformer.h.1.mlp"

Open that file and press F5. If VS Code asks for a debugger, choose llmdbg. No launch.json is required. If a workspace launch configuration is preferred, the complete minimal version is:

{
  "version": "0.2.0",
  "configurations": [
    {
      "type": "llmdbg",
      "request": "launch",
      "name": "llmdbg: Active file",
      "config": "${file}"
    }
  ]
}

On first use, the extension creates a private Python environment in VS Code's extension storage. It does not install anything into the workspace. The first GPT-2 run downloads and loads the model, then keeps its tensors resident in a persistent model-host process. Stopping and restarting the debugger reuses the resident model and runs only a new forward pass. Closing/reloading VS Code stops the host and releases the model. Each submodule statement is an authored model execution stop. Set breakpoints on these statements or use Step Over to advance through them. Runtime vectors appear in debugger scopes; the source file is never rewritten.

token = 3 makes token position 3 the default for every ordinary source breakpoint. To override it for one breakpoint, use the shorter conditional expression token=4. Positions are zero-based. The debugger prefills tokens before the selected position into the KV cache, then captures that token with a one-token forward pass. Stepping beyond the last selected layer advances to the next token using the updated cache.

Watch one zero-based dimension with residual_stream[42], input[42], output[42], or delta[42]. The Residual stream (output) debugger scope exposes the current hidden representation explicitly. Run llmdbg: Plot Current Vector from the Command Palette or debug toolbar to inspect the full vector as a dimension plot, histogram, or top-activation chart. An open plot updates automatically after each debugger stop.

License

MIT

Metadata

Release files for llmdbg 0.0.3a9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for llmdbg 0.0.3a9
File Size Uploaded Provenance
llmdbg-0.0.3a9.tar.gz 42.3 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for llmdbg 0.0.3a9
File Interpreter ABI Platform
llmdbg-0.0.3a9-py3-none-any.whl Python 3 none any Details

Total release size: 60.3 kB

Release files / llmdbg-0.0.3a9.tar.gz

Download URL llmdbg-0.0.3a9.tar.gz
Size 42.3 kB
Tags Source
SHA-256 checksum
How to use checksums
eef55d4ad188edea480d474ecfbfaa399bf87ca2a3bd05dbb5b4c5dca850a87b
BLAKE2b-256 checksum
How to use checksums
9f42069e351e42ba6448a5db2ca24788299917925c8e0411afbb3b21b8be5df6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.3

Release files / llmdbg-0.0.3a9-py3-none-any.whl

Download URL llmdbg-0.0.3a9-py3-none-any.whl
Size 17.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
5aa458109ddff73d79f567186df527b8b2f5f842b54de07248d414f79e1414bf
BLAKE2b-256 checksum
How to use checksums
f3e1b872328c7083323bde18f9525f8973fc7117a9ebbe141a5b6155d9fb92be
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.3

Security for llmdbg 0.0.3a9

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Release history Release notifications | RSS feed

This release
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page