Releasesby Glyphspark-nlp 6.2.0
📢 Spark NLP 6.2.0: A new stage for unstructured document ingestion and processing at scale Spark NLP 6.2.0 introduces key upgrades across entity extraction, document normalization, HTML reading, and GGUF-based models.
Also shipped Oct 22, 2025John Snow Labs in October 2025 →
OTLP Ingestion Endpoints for Traces and Logs are in Open Beta
You can send your OTLP traces and logs directly to Sentry using our new ingestion endpoints
SolarWinds Enterprise data source for Grafana
Introducing SolarWinds data source plugin. SolarWinds is a network and infrastructure monitoring platform that provides tools to monitor, manage network performance, server health, and application availability.
Modal 1.2.1
- It's now possible to override the default -dev suffix applied to the autogenerated URLs for ephemeral Apps (i.e., when using modal serve) via a new dev_suffix field in the .modal.toml config file, or equivalently with the MODAL_DEV_SUFFIX environment variable.
Added support for retrieving log probabilities via the logprobs parameter for the Completions endpoint
Added support for retrieving log probabilities via the logprobs parameter for the Completions endpoint. Set to an integer (0-20) to return the most likely alternative tokens at each position, or null to disable.
Prisma ORM 6.18.0, Postgres Database Metrics and Config Modernization
Prisma ORM 6.18.0 includes updates for database metrics and configuration modernization for Prisma Postgres.
Sentry Ruby SDK 6.0.0
The new SDK allows ignoring status codes for Performance, setting a custom sampling interval for profiling and drops the async option.
More from spark-nlpEvery spark-nlp release →
spark-nlp 6.1.5
📢 Spark NLP 6.1.5: Smarter Readers and More Resilient Pipelines Spark NLP 6.1.5 focuses on improving data ingestion reliability and pipeline flexibility. This release enhances reader components with better fault tolerance, broader input support, and introduces a new ReaderAssembler annotator for streamlined integration.
spark-nlp 6.2.1
📢 Spark NLP 6.2.1: Enhanced hierarchical document processing and training optimizations Spark NLP 6.2.1 brings significant improvements to document ingestion with expanded hierarchical support, XML processing enhancements, and optimizations for NerDL training.
spark-nlp 6.2.2
📢 Spark NLP 6.2.2: Bugfix Release Spark NLP 6.2.2 brings bug fixes to WordEmbeddings and NerDLApproach logging. 🐛 Bug Fixes - WordEmbeddings: Fixed a bug where WordEmbeddings would duplicate input tokens in the output - NerDLApproach: Fixed a bug during logging, that would show inaccurate training/validation counts.
spark-nlp 6.2.3
📢 Spark NLP 6.2.3: Further Improvements for NerDL Spark NLP 6.2.3 introduces targeted improvements to training performance and stability of NerDLApproach and bug fixes for CamemBertForTokenClassification. NerDLApproach now uses new internal data-loading behavior, and improving training speed and preventing out-of-memory errors.
spark-nlp 6.3.1
📢 Spark NLP 6.3.1: LLM Backend Upgrade and Document Processing Improvements Spark NLP 6.3.1 focuses on strengthening distributed local LLM inference by upgrading the jsl-llamacpp backend to a newer llama.cpp release, while also delivering important improvements in document structure handling and metadata consistency.
spark-nlp 6.3.2
📢 Spark NLP 6.3.2: Scala 2.13 Support, Layout-Aware Images, and Enhanced LightPipeline Tracking Spark NLP 6.3.2 is a foundational release that introduces official support for Scala 2.13, alongside important improvements in document layout understanding and lightweight inference workflows.
spark-nlp 6.3.3
📢 Spark NLP 6.3.3: ModernBERT Embeddings, Vector DB Integration, and Layout-Aware Document Processing Spark NLP 6.3.3 is a feature-packed release aimed at practitioners building modern NLP and multimodal document pipelines.
spark-nlp 6.4.0
📢 Spark NLP 6.4.0: LLM-Powered Entity Extraction, Expanded Document Readers, and Pipeline Robustness Spark NLP 6.4.0 is a feature-rich release focused on bringing LLM-powered extraction into standard NLP pipelines, dramatically expanding the document reader ecosystem, and hardening production ingestion workflows.