Added
pw.xpacks.llm.prompts.RAGPromptTemplate
, set of prompt utilities that enable verifying templates and creating UDFs from prompt strings or callables.pw.xpacks.llm.question_answering.BaseContextProcessor
streamlines development and tuning of representing retrieved context documents to the LLM.pw.io.kafka.read
now supportswith_metadata
flag, which makes it possible to attach the metadata of the Kafka messages to the table entries.pw.io.deltalake.read
can now stream the tables with deletions, if no deletion vectors were used.
Changed
pw.io.sharepoint.read
now explicitly terminates with an error if it fails to read the data the specified number of times per row (the default is8
).pw.xpacks.llm.prompts.prompt_qa
, and other prompts expect 'context' and 'query' fields instead of 'docs'.- Removed support for
short_prompt_template
andlong_prompt_template
inpw.xpacks.llm.question_answering.BaseRAGQuestionAnswerer
. These prompt variants are no longer accepted during construction or in requests. pw.xpacks.llm.question_answering.BaseRAGQuestionAnswerer
allows setting user created prompts. Templates are verified to include 'context' and 'query' placeholders.pw.xpacks.llm.question_answering.BaseRAGQuestionAnswerer
can take aBaseContextProcessor
that represents context documents to the LLM. Defaults topw.xpacks.llm.question_answering.SimpleContextProcessor
which filters metadata fields and joins the documents with new lines.
Fixed
- The input of
pw.io.fs.read
andpw.io.s3.read
is now correctly persisted in case deletions or modifications of already processed objects take place.