Third-Party Notices

This page summarizes the licenses for NeMo Labs Voice Agent and the third-party source code and data fixtures redistributed in the repository.

The authoritative document is THIRD_PARTY_NOTICES.md at the repository root. It reproduces the full license text of every redistributed upstream project. If this summary and that file disagree, follow the root file.

Project License

Use the repository files and package metadata in this table as the authoritative project-license references:

Every *.py file in the repository, except __init__.py, carries an SPDX and Apache header in its first lines. A copyright check runs on every pull request and fails without it. Refer to Contributing.

Redistributed Third-Party Code and Data

THIRD_PARTY_NOTICES.md covers only upstream material whose source or data is copied into this repository. Regular runtime dependencies, including Pipecat, NeMo, PyTorch, vLLM, and the rest of the pyproject.toml dependency tree, are installed from PyPI. They retain their own licenses, which are not reproduced in that file. The repository redistributes the following sources:

eva (MIT, ServiceNow)

Used for the eva_airline evaluation domain (50 scenarios). Adapted code covers the database-hash canonicalization module (nemo_voice_agent/evaluation/db_hash.py), the airline tool and parameter definitions (eva_airline_tools.py, eva_airline_params.py), and the scenario package under nemo_voice_agent/evaluation/scenarios/data/eva_airline/. The scenario databases and dataset index under nemo_voice_agent/evaluation/data/eva_airline/ are copied verbatim. The upstream airline_agent.yaml is also included there with only trailing whitespace normalized. Its role and instructions provide the eva agent policy.

tau2-bench (MIT, Sierra Research)

Used for the tau2_airline (50 tasks), tau2_retail (114 tasks), and tau2_telecom (114 tasks) domains. A parallel tau2_telecom_workflow registration uses the same telecom tasks.

Adapted code covers the per-domain tool, parameter, predicate, and initialization-function modules under nemo_voice_agent/evaluation/tools/. It also covers the shared write-tool base (_write_tool_base.py) and the scenario packages under nemo_voice_agent/evaluation/scenarios/data/. Databases, task definitions, split lists, and agent policy Markdown under nemo_voice_agent/evaluation/data/tau2_*/ are copied verbatim or format-converted. The telecom upstream db.toml and user_db.toml files are converted to JSON, and the single large airline db.json is sharded by table.

Pipecat (BSD 2-Clause, Daily)

The example browser client was adapted from Pipecat’s RTVI client sample. The file examples/generic_voice_agent/client/src/app.ts retains its original Daily copyright line and SPDX-License-Identifier: BSD 2-Clause License header.

Attribution Conventions

The repository records attribution at the following levels:

For the reader-facing version of the provenance table, refer to Fixture Data & Provenance.

GPL Avoidance in the Dependency Tree

Two dependency overrides in pyproject.toml keep the resolved dependency graph free of copyleft packages that would be incompatible with the project’s Apache-2.0 license:

Because misaki.espeak imports phonemizer and espeakng_loader at module load time, nemo_voice_agent/pipecat/services/nemo/_espeak_gpl_shim.py registers no-op substitutes in sys.modules. This allows the import to succeed. Constructing the real espeak backend then raises an error, which kokoro.KPipeline catches before falling back to misaki’s dictionary-only G2P. The shim does not shadow a real phonemizer installation.

Adding a New Upstream Source

When importing new evaluation data or porting upstream code, update all three of the following in the same change:

1. Add a section to THIRD_PARTY_NOTICES.md with the project name, upstream URL, pinned version or commit, license identifier, the list of files it maps to, and the verbatim license text.
2. Add a matching section to nemo_voice_agent/evaluation/data/README.md describing each imported file and whether it is verbatim, filtered, or format-converted.
3. Add an inline # Adapted from <upstream-url> attribution to the top of every ported source file, below the SPDX header.

Refer to Importing Evaluation Data for the full import workflow, including the scaffold generators under scripts/.