Pathway

Added
- `pw.reducers.latest` and `pw.reducers.earliest` that return the value with respectively maximal and minimal processing time assigned.
- `pw.io.kafka.write` can now produce messages containing raw bytes in case the table consists of a single binary column and `raw` mode is specified. Similarly, this method will provide plaintext messages if `plaintext` mode is chosen and the table consists of a single string-typed column.
- `pw.io.pubsub.write` connector for publishing Pathway tables into Google PubSub.
- Argument `strict_prompt` to `answer_with_geometric_rag_strategy` and `answer_with_geometric_rag_strategy_from_index` that allows optimizing prompts for smaller open-source LLM models.
- Temporarily switch LiteLLMChat's generation method to sync version due to a bug while using `json` mode with Ollama.

Changed
- **BREAKING**: `pw.io.kafka.read` will not parse the messages from UTF-8 in case `raw` mode was specified. To preserve this behavior you can use the `plaintext` mode.
- **BREAKING**: `Table.flatten` now flattens one column and spreads every other column of the table, instead of taking other columns from the argument list.

Added
- `pw.io.bigquery.write` connector for writing Pathway tables into Google BigQuery.
- parameter `filepath_globpattern` to `query` method in `VectorStoreClient` for specifying which files should be considered in the query.
- Improved compatibility of `pw.Json` with standard methods such as `len()`, `int()`, `float()`, `bool()`, `iter()`, `reversed()` when feasible.

Changed
- `pw.io.postgres.write` can now parallelize writes to several threads if several workers are configured.
- Pathway now checks types of pointers rigorously. Indexing table with mismatched number/types of columns vs what was used to create index will now result in a TypeError.
- `pw.Json.as_float()` method now supports integer JSON values.

Added
- New function `answer_with_geometric_rag_strategy_from_index`, which allows to use `answer_with_geometric_rag_strategy` without the need to first retrieve documents from index.
- Added support for custom state serialization to `udf_reducer`.
- Introduced `instance` parameter in `AsyncTransformer`. All calls with a given `(instance, processing_time)` pair are returned at the same processing time. Ordering is preserved within a single instance.
- Added `successful`, `failed`, `finished` properties to `AsyncTransformer`. They return tables with successful calls, failed calls and all finished calls, respectively.

Changed
- Property `result` of `AsyncTransformer` is deprecated. Property `successful` should be used instead.
- `pw.io.csv.read`, `pw.io.jsonlines.read`, `pw.io.fs.read`, `pw.io.plaintext.read` now handle `path` as a glob pattern and read all matched files and directories recursively.

Fixed
- Pathway will only require `LiteLLM` package, if you use one of the wrappers for `LiteLLM`.
- Retries are implemented in `pw.io.airbyte.read`.
- State processing protocol is updated in `pw.io.airbyte.read`.

Added
- New parameters of `pw.UDF` class and `pw.udf` decorator: `return_type`, `deterministic`, `propagate_none`, `executor`, `cache_strategy`.
- The LLM Xpack now provides integrations with LlamaIndex and LangChain for running the Pathway VectorStore server.

Changed
- Subclassing `UDFSync` and `UDFAsync` is deprecated. `UDF` should be subclassed to create a new UDF.
- Passing keyword arguments to `pw.apply`, `pw.apply_with_type`, `pw.apply_async` is deprecated. In the future, they'll be used for configuration, not passing data to the function.

Fixed
- Fixed a minor bug with `Table.groupby()` method which sometimes prevented of accessing certain columns in the following `reduce()`.
- Fixed warnings from using OpenAI Async embedding model in the VectorStore in Colab.

Added
- `%:z` timezone format code to `strptime`.
- Support for Airbyte connectors `pw.io.airbyte`.