• core.window.Window: apply a processor to a rolling window across the stream.
• Models output dataclass Parts when constrained decoding is used. This greatly simplifies writing pipelines that extract data on intermediate steps. Now the whole response will be in a single Part and accessible as part.get_dataclass(MyData).
• Added a text-based turn-by-turn chat example with multimodal support through downloading images or PDFs by their URLs.
• Add GenAILangChainProcessor to contrib.

• CachedPartProcessor - support caching for PartProcessors: if the same part is received again, result can be taken from the cache.
• GlobProcessor - stream files from local filesystem in-to processors.
• Contrib processors: OpenRouterModel - add compatibility with a variety of LLMs available through OpenRouter.
• Numerous bugfixes.
• Added links to processors from @mbeacom: mbeacom/genai-processors-pydantic and mbeacom/genai-processors-url-fetch

• Initial Ollama support. Now processors work with local Gemma models.
• Cleaned up the codebase:
  • Added missing package dependencies dependencies
  • Reshuffled file structure for PYTHONPATH=. to work for local development.
  • Published unit tests.

Additions:

• processor sources as an easy way to add data sources (microphones, camera) to a processor chain.
• jinja template rendering of processor parts based on dataclasses.
• extra documentation.

Adds the Switch operation for processors, similar to a std switch statement.

Core processors additions:

• text_to_speech and speech_to_text processor using Google Cloud APIs
• realtime processor to create a live aka realtime processor from a turn-based LLM (audio in/out only)
• pdf processor to work with PDF files and extract tokens for LLMs
• drive processor to get documents from Google Drive (sheets, slides and docs)
• github processor to get code from github
• jinja processor to create prompts from classes

Examples:

• several CLIs to test processors from the CLI (including live and realtime processors)

Initial Release of the GenAI Processors library.