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V5.0.0

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@whitead whitead released this 11 Sep 16:25
· 320 commits to main since this release
45b206d

New Features

  • Automatic population of metadata: PDF metadata is automatically retrieved from a variety of providers, including adding bibtex, citation counts, journal quality assessments, and noting retractions
  • full-text search: A major difference between our published work and this repo is ability to search over all of scientific literature. We've brought the OSS version closer by adding full-text keyword search via tantivy. Now you can index and search many papers before embdding, making it feasible to ingest many papers.
  • unified settings management: You can now save/load settings and that makes it easier for us to distribute settings reflecting various tasks with PaperQA2. Examples are writing wikipedia articles, identifying contradictions, and obtaining structured data
  • CLI: We've made a CLI that uses persistent parsings/indexes and makes it much easier to just ask questions of a folder of PDFs
  • Litellm: We've adopted litellm as the LLM wrapper of choice. This means we now support many LLM APIs directly with only the model string changing. It also means we have "routers" now that can do fallbacks, api rate limiting, and retries.

Improvements

  • More modern agent frameworks
  • Reduction in dependencies
  • Removed code duplicated by litellm
  • Many improvements on code style and best practices

Regressions/Deprecation

We've removed the following features to keep our library focused:

  • doc_match - we do not have enough data to support that this method actually helps for very large corpuses
  • LangchainVectorStore - We no longer support more complex vector stores via Langchain like FAISS. Instead, we only support Numpy vector stores. We never found the paradigm of very large vector stores to be better than keyword search -> vector search -> LLM reranking and thus removed the code

Detailed Changes:

New Contributors

Full Changelog: v4.9.0...vnew