Skip to main content

For assessing question answering systems' final answers and intermediate steps, against a given set of questions, reference answers and steps.

Project description

Graphwise Logo

QA Evaluation

This is a Python library for assessing the quality of question-answering systems, such as systems built with LLM-based agents. It is agnostic to the agent implementation and the LLM it uses.

The evaluation is based on a user-provided reference dataset containing queries, reference responses, and optional reference steps, such as expected tool uses. The evaluator compares these references with the agent's actual responses and executed steps. Reference steps can be grouped to allow some expected steps to occur in any order.

The library provides built-in evaluation metrics and supports user-defined custom metrics (§ Metrics).

Documentation

Maintainers

Developed and maintained by Graphwise. For issues and feature requests, please open a GitHub issue.

License

Apache-2.0 License. See the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

graphrag_eval-6.3.0.tar.gz (20.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

graphrag_eval-6.3.0-py3-none-any.whl (26.4 kB view details)

Uploaded Python 3

File details

Details for the file graphrag_eval-6.3.0.tar.gz.

File metadata

  • Download URL: graphrag_eval-6.3.0.tar.gz
  • Upload date:
  • Size: 20.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.4 CPython/3.12.13 Linux/6.17.0-1018-azure

File hashes

Hashes for graphrag_eval-6.3.0.tar.gz
Algorithm Hash digest
SHA256 64bce095832247b6e0d99a6cef56ed88c58039cbea7806dc328f2bec2ee8d612
MD5 80d4e5e65db52d7b629e2461014b8b82
BLAKE2b-256 48fdafc0191ba235a7c387eaac81b135f1dc7c61543096d24ec562890c237c8e

See more details on using hashes here.

File details

Details for the file graphrag_eval-6.3.0-py3-none-any.whl.

File metadata

  • Download URL: graphrag_eval-6.3.0-py3-none-any.whl
  • Upload date:
  • Size: 26.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.4 CPython/3.12.13 Linux/6.17.0-1018-azure

File hashes

Hashes for graphrag_eval-6.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 13e4b496e6c9b77ca962d1619a51ec3ce4866e4077dcfe1dc757c15fecfdb987
MD5 d9b842a8ee42b2f3000c2f3570daad77
BLAKE2b-256 0a292b50b474a035af2557ffe6d93b84a2d1486454f90353d908105a3817e9f0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page