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[v0.15.3] - 2025-11-07

Fixed

  • Fixed weird import issues with posthog and StrEnum

[v0.15.2] - 2025-11-07

Fixed

  • Fixed resetting routing profile when calling with --reset flag in pipelex init

[v0.15.1] - 2025-11-07

Fixed

  • Bumped OpenAI dependency to >=1.108.1 to support their breaking change: "change optional parameter type from NotGiven to Omit"
  • get_selected_backend_keys() now correctly considers backends enabled by default (like before v0.15.0)

[v0.15.0] - 2025-11-07

Highlights: This release dramatically simplifies onboarding with interactive CLI setup, comprehensive documentation relaunch, and intelligent model fallbacks, making Pipelex more accessible and resilient than ever.

Added

  • Model Waterfalls: Define prioritized model lists in base_deck.toml (e.g., smart_llm = ["gpt-4o", "claude-4.5-sonnet", "grok-3"]). Pipelex automatically falls back to the next model if the preferred one is unavailable.
  • Advanced Routing Profiles: New capabilities in routing_profiles.toml: fallback_order (Global fallback sequence specifying which backends to try if a model isn't found) and optional_routes (Routes that activate only when their target backend is enabled)
  • New Models: Anthropic claude-4.5-haiku (Pipelex Inference, Anthropic, and Bedrock backends) and Azure OpenAI o3
  • Comprehensive Documentation Relaunch: Complete restructure under /home/ with new "Get Started" guides for pipelex build and manual workflows, plus in-depth sections on Domains, Bundles, Concepts, and Pipe lifecycle.
  • Enhanced CLI: pipelex init now interactively guides backend selection and automatically configures routing profiles, including primary backend and fallback order. Added pipelex init routing focus.
  • Enhanced CLI: Improved error reporting across all commands (build, validate, run, show) with clear, actionable feedback for configuration errors, missing models, and invalid presets.
  • Enhanced CLI: pipelex doctor now validates model deck configuration.
  • New Routing Profiles: Full suite of all_* profiles (e.g., all_openai, all_anthropic, all_google) to route all requests to a single provider.

Changed

  • BREAKING: for inline concept structures, the fields are now optional by default: the required property defaults to false. Explicitly set required = true to make fields mandatory, which we discourage as it increases risks of hallucinations.
  • LLM Presets Overhaul: Rationalized and renamed default presets in base_deck.toml. Single-model aliases replaced with waterfall aliases. Key renames: llm_for_complex_reasoning → llm_to_engineer, llm_to_answer_hard_questions → llm_to_answer_questions, llm_to_write_questions → llm_for_writing_cheap. Removed redundant older presets.
  • Stricter Configuration Validation: Pipelex validates model deck on startup and raises errors if presets reference unavailable models.

Fixed

  • Local OpenAI-Compatible Endpoints: OpenAI plugin now handles empty API keys, enabling seamless integration with local servers like Ollama.

Removed

  • Old Documentation Structure: Previous /pages/ directory documentation removed in favor of new structure.

[v0.14.3] - 2025-10-29

Added

  • Image generation models via BlackBoxAI backend: flux-pro, flux-pro/v1.1, flux-pro/v1.1-ultra (Black Forest Labs), fast-lightning-sdxl (ByteDance), and nano-banana (Google). Implemented using new openai_alt_img_gen SDK worker with chat completion-style API.
  • Language model: claude-4.5-sonnet (Anthropic) via BlackBoxAI backend.
  • Routing profile: all_blackboxai profile routes all supported model requests to BlackBoxAI backend.

Changed

  • Model aliases in base_deck.toml: base-img-gen → flux-pro/v1.1-ultra, best-img-gen → nano-banana, llm_for_large_codebase now includes claude-4.5-sonnet.
  • Configuration file: BLACKBOX_RULES.md renamed to .blackboxrules.

Fixed

  • Image generation schema: ImgGenJobParams.seed field now explicitly defined with default=None.
  • CLI bundle validation: pipelex validate command now accepts bundle path (.plx file) which are in the package and already loaded and performs dry run on all pipes in the bundle.

[v0.14.2] - 2025-10-29

Chaged

  • Improved pipe builder.

Added

  • CLI to generate inputs JSON.

[v0.14.1] - 2025-10-27

Added

  • Tutorial GIF on the README.md file.

[v0.14.0] - 2025-10-27

Added

  • pipelex doctor command: Diagnoses and fixes common configuration issues including missing files, invalid telemetry settings, and unset environment variables for enabled backends.
  • Interactive backend selection in pipelex init: Multi-select menu for enabling/disabling inference backends (OpenAI, Anthropic, Amazon Bedrock, etc.).
  • JSON input support: pipelex run --inputs flag accepts a JSON file path for passing structured data to pipelines.
  • pretty_print methods: Added to PipeSpec, ConceptSpec, and Stuff objects for readable debugging output.
  • VS Code debug configuration: "Debug run pipe" launch configuration for debugging pipeline executions.
  • display_name attribute: Added to all inference backends in backends.toml for better UI presentation.
  • Documentation headers: All default .toml configuration files now include headers with links to documentation and support channels.

Changed

  • pipelex init redesign: Transformed into a unified, interactive setup wizard with rich terminal UI for configuration files, backend selection, and telemetry preferences. Telemetry is now configured here instead of via first-run prompt.
  • README.md rewrite: Complete overhaul featuring a simplified 5-step quick-start guide highlighting the pipelex build command.
  • Documentation updates: "Quick Start" guide renamed to "Writing Workflows" with simplified content. Python examples updated to use JSON input method, removing manual Stuff and WorkingMemory object creation boilerplate. Developer guides and AI assistant rules now recommend pipelex validate over make validate. Added instructions emphasizing .venv activation before running commands.
  • Error handling improvements: Pipelines now validate required inputs upfront and fail early with PipeRunInputsError. pipelex run prints full rich-formatted exception tracebacks on error.
  • Default enabled backends: Amazon Bedrock, Google AI, and Google Vertex AI are now enabled by default.
  • Naming consistency: "AWS Bedrock" renamed to "Amazon Bedrock" throughout codebase, configuration, and documentation.

Fixed

  • Some documentation links were broken.

[v0.13.2] - 2025-10-25

Added

  • Added the n8n documentation page for the n8n-nodes-pipelex package.
  • Added optional telemetry system with first-run interactive prompt offering three modes: off (no data collected), anonymous (usage data without identification), and identified (usage data with user identification). Automatically respects DO_NOT_TRACK environment variable and redacts sensitive data (prompts, responses, file paths, URLs). Configuration stored in .pipelex/telemetry.toml.
  • Added telemetry documentation: user-friendly setup guide and comprehensive configuration reference.

Changed

  • Updated the PipelexClient and changed the route of the API calls to v1/pipeline/execute and v1/pipeline/start.
  • Changed the parameter input_memory to inputs in the documentaton.

[v0.13.1] - 2025-10-22

Changed

  • Changed the pydanticdependency from ==2.10.6 to >=2.10.6,<3.0.0 to avoid compatibility issues.

[v0.13.0] - 2025-10-21

Highlights - Simplifying pipeline execution and improving developer experience

This release focuses on making Pipelex more accessible and easier to use, with major improvements to the CLI, simplified syntax for multiplicity, and a complete documentation overhaul:

  • New CLI commands: Run pipelines directly with pipelex run, generate Python runners with pipelex build runner, and inspect your AI backend configuration with pipelex show backends
  • Simplified pipeline inputs: The new inputs parameter replaces input_memory and accepts strings, lists, or content objects directly - no more complex dictionary structures
  • Getting started faster: Completely rewritten quick-start guide and new documentation sections help you go from installation to your first pipeline in minutes

Added

  • CLI command pipelex run: Top-level command to execute pipelines directly from the CLI. Can run pipes from the package or from any .plx bundle file, with options to provide inputs from a JSON file and save the output
  • CLI command pipelex build runner: Generates Python script with imports and example input structures for any pipe
  • CLI command pipelex show backends: Displays configured AI providers, their status, and active routing rules
  • Model presets: Added task-oriented presets including llm_to_write_questions, llm_to_code, llm_for_basic_vision, llm_for_visual_analysis
  • Documentation: Complete quick-start guide rewrite, new guides for "Understanding Multiplicity", "API Guide", "Executing Pipelines with Inputs", and updated README with video demo
  • Migration guide: Updated guide at pipelex/kit/migrations/migrate_0.11.0_0.12.x.md

Changed

  • Unified bracket notation for multiplicity: Single items use "Concept", variable lists use "Concept[]", fixed-count lists use "Concept[3]". Applies to both inputs and output fields in .plx files
  • Pipeline input format: input_memory parameter renamed to inputs; now accepts strings, lists of strings, StuffContent objects, or explicit concept dictionaries instead of CompactMemory
  • Bundle main_pipe attribute: Pipelex bundles (.plx files) now support a main_pipe attribute to designate the primary entry point of the bundle. Used by pipelex run and pipelex build runner commands to simplify execution
  • Model preset names: llm_to_reason → llm_for_complex_reasoning, base_ocr_mistral → extract_text_from_visuals, base_extract_pypdfium2 → extract_text_from_pdf, base_img_gen → gen_image_basic, fast_img_gen → gen_image_fast, high_quality_img_gen → gen_image_high_quality
  • Unified model parameter: PipeExtract and PipeImgGen now use model parameter for consistency across all operator pipes
  • PipeExtract operator: Output is now consistently validated to be the Page concept, simplifying its usage for document processing
  • CLI improvements: pipelex run and pipelex validate now auto-detect pipe code vs .plx bundle files; pipelex validate promoted to top-level command with improved error reporting and syntax-highlighted code snippets
  • CLI reorganization: Main command-line interface restructured for better usability with improved help texts and more logical command order
  • Python API: Pipelex.make() now accepts dependency injection arguments directly
  • Python coding standards: Updated internal coding standards to recommend declaring variables with a type but no default value to better leverage linters for bug detection
  • Default configuration: Azure and AWS inference backends now disabled by default in template configuration

Fixed

  • Structure generation: Special characters (double quotes, backslashes) in concept field descriptions or default values no longer produce invalid Python code

Removed

  • Legacy multiplicity syntax: nb_output, multiple_output parameters, and complex input dictionary syntax with multiplicity field
  • Pipe-specific model parameters: ocr parameter from PipeExtract and img_gen parameter from PipeImgGen
  • prompt_template_to_structure and system_prompt_to_structure configurations at the pipe and domain level
  • Project Name discovery from Configuration
  • Temporary design document for the new inference backend system (feature now fully implemented and documented)

[v0.12.0] - 2025-10-15

Highlights - Moving fast and breaking things

  • Added the new builder pipeline system for auto-generating Pipelex bundles from user briefs
  • it's a pipeline to generate pipelines, and it works!
  • the pipeline definitions are in pipelex_libraries/pipelines/base_library/builder/
  • removed the previous draft which was named meta_pipeline.plx

Breaking changes... for good!

We tried to group all the renamings we wanted to do which impact our language, so that you get one migration to apply and then we will be way more stable in the future releases.

This is all in the spirit of making Pipelex a declarative language, where you express what you want to do, and the system will figure out how to do it. So our focus inwas to make the Pipelex language easier to understand and use for non-technical users, and at the same time use more consistent and obvious words that developers are used to.

💡 Pro tip: To make migration easier, pass the migration guide to your favorite SWE agent (Cursor, Claude Code, github copilot, etc.) and let it handle the bulk of the changes!

  • Removed centralized pipelex_libraries folder system
  • Pipelines are now auto-discovered from anywhere in your project—no special directory required
  • No config path parameters needed in Pipelex.make() or CLI commands (just call Pipelex.make())
  • Custom functions require @pipe_func() decorator for auto-discovery
  • Structure classes auto-discovered (must inherit from StructuredContent)
  • Configuration stays at repository root in .pipelex/ directory

  • See migration guide for details on reorganizing your project structure

  • General changes

  • renamed definition fields to description across all cases

  • Renamed PipeJinja2 to PipeCompose

  • the fact that our templating engine is Jinja2 is a technnical detail, not fundamental to the language, especially since we included a pre-processor enabling insertion of variables in prompts using @variable or $variable, in addition to the jinja2 syntax {{ variable }}
  • renamed jinja2 field to template for the same reason

  • for more control, instead of providing a string for the template field, you can also use a nested template section with template, category and templating_style fields

  • Renamed PipeOCR to PipeExtract

  • this is to account for various text extraction techniques from images and docs, including but not only OCR; e.g. we now have integrated the pypdfium2 package which can extract text and images from PDF, when it's actually real text (not an image), and soon we'll add support for other document extraction models solutions
  • removed obligation to name your document input ocr_input, it can now be named whatever you want as long as it's a single input and it's either an Image or a PDF or some concept refining PDF or Image
  • renamed ocr_page_contents_from_pdf to extract_page_contents_from_pdf
  • renamed ocr_page_contents_and_views_from_pdf to extract_page_contents_and_views_from_pdf
  • introduced model settings and presets for extract models like we had for LLMs

  • renamed ocr_model to model for choice of model, preset, or explicit setting and introduced base_ocr_mistral as an alias to mistral-ocr

  • PipeLLM field renames

  • image inputs must now be tagged in the prompt like all other inputs; you can just drop their names at the beginning or end of the prompt, or you can reference them in meaningful sentences to guide the Visual LLM, e.g. "Analyze the colors in $some_photo and the shapes in $some_painting."
  • renamed prompt_template field to prompt
  • renamed llm field to model

  • renamed llm_to_structure field to model_to_structure

  • PipeImgGen field renames

  • renamed img_gen field to model for choice of model, preset, or explicit setting
  • removed some technical settings such as nb_steps from the pipe attributes, instead you can set these as model settings or model presets

  • introduced model settings and presets for image generation models like we had for LLMs

  • PipeCondition field renames

  • renamed pipe_map to outcomes

  • renamed default_pipe_code to default_outcome and it's now a required field, because we need to know what to do if the expression doesn't match any key in the outcomes map; if you don't know what to do in that case, then it's a failure and you can use the fail value

  • Configuration file changes (.pipelex/ directory)

  • Renamed parameter llm_handle to model across all LLM presets in deck files
  • Renamed parameter img_gen_handle to model across all image generation presets in deck files
  • Renamed parameter ocr_handle to model in extraction presets
  • Renamed ocr section to extract throughout configuration files
  • Renamed ocr_config to extract_config in pipelex.toml
  • Renamed base_ocr_pypdfium2 to base_extract_pypdfium2
  • Renamed is_auto_setup_preset_ocr to is_auto_setup_preset_extract
  • Renamed nb_ocr_pages to nb_extract_pages
  • Updated pytest marker from 'ocr' to 'extract'

Added

  • Added cheap-gpt model alias for gpt-4o-mini
  • Added cheap_llm_for_vision preset using gemini-2.5-flash-lite
  • Added llm_for_testing_vision and llm_for_testing_vision_structured presets for vision testing
  • Added is_dump_text_prompts_enabled and is_dump_response_text_enabled configuration flags to have the console display everything that goes in and out of the LLMs
  • Added generic_templates section in llm_config with structure extraction prompts
  • Added useful error messages with migration configuration maps pin-pointing the fields to rename for config and plx files
  • Added improved error message for PipeFunc when function not found in registry, mentioning @pipe_func() decorator requirement since v0.12.0
  • Added pytest filterwarnings to ignore deprecated class-based config warnings
  • Added Flow class that represents the flow of pipe signatures
  • Added pipe-builder command flow to generate flow view from pipeline brief
  • Added FlowFactory class to create Flow from PipelexBundleSpec or PLX files
  • Added sort_pipes_by_dependencies() function for topological sorting of pipes
  • Added pipe_sorter.py module for pipe dependency sorting utilities
  • Added search_for_nested_image_fields_in_structure_class() method to Concept class
  • Added image_field_search.py module with utilities to search for image fields in structure classes
  • Added pipe_dependencies property to PipeBlueprint and controller blueprints
  • Added ordered_pipe_dependencies property to PipeBlueprint for ordered dependencies
  • Added get_native_concept() function to hub
  • Added get_pipes() function to hub
  • Added remove_concepts_by_codes() method to ConceptLibraryAbstract
  • Added remove_pipes_by_codes() method to PipeLibraryAbstract
  • Added template preprocessing with preprocess_template() function
  • Added better dependency checking for optional SDK packages (anthropic, mistralai, boto3, aioboto3)
  • Added MissingDependencyError exception for missing optional dependencies
  • Added library_utils.py module with utility functions for PLX file discovery using importlib.resources
  • Added class_utils.py module with are_classes_equivalent() and has_compatible_field() functions
  • Added comprehensive unit tests for CostRegistry, WorkingMemory, and ModuleInspector
  • Added ScanConfig class with configurable excluded directories for library scanning
  • Added CSV export capabilities to CostRegistry with save_to_csv() and to_records() methods
  • Added default configuration template in pipelex/kit/configs/pipelex.toml

Changed

  • Replaced package toml by tomli which is more modern and faster
  • Updated Gemini 2.0 model from gemini-2.0-flash-exp to gemini-2.0-flash with new pricing (input: $0.10, output: $0.40 per million tokens)
  • Updated Gemini 2.5 Series comment from '(when available)' to stable release
  • Updated base-claude from claude-4-sonnet to claude-4.5-sonnet across all presets
  • Updated kajson dependency from version 0.3.0 to 0.3.1
  • Updated httpx dependency to >=0.23.0,<1.0.0 for broader compatibility
  • Cleanup env example and better explain how to set up keys in README and docs
  • Changed Gemini routing from google backend to pipelex_inference backend
  • BREAKING: Major module reorganization - moved tools/config/, tools/exceptions.py, tools/environment.py, tools/runtime_manager.py to system/ package structure (system/configuration/, system/exceptions.py, system/environment.py, system/runtime.py)
  • BREAKING: Reorganized registry modules from tools/ to system/registries/ (affects class_registry_utils, func_registry, func_registry_utils, registry_models)
  • BREAKING: Split pipelex.core.stuffs.stuff_content module into individual files per content type (affects imports: StructuredContent, TextContent, ImageContent, ListContent, PDFContent, PageContent, NumberContent, HtmlContent, MermaidContent, TextAndImagesContent)
  • BREAKING: Renamed package pipelex.pipe_works to pipelex.pipe_run and moved PipeRunParams classes into it
  • BREAKING: Cost reporting changed from Excel (xlsx) to CSV format using native Python csv module instead of pandas
  • Renamed ConfigManager to ConfigLoader
  • Renamed PipelexRegistryModels to CoreRegistryModels
  • Renamed PipelexTestModels to TestRegistryModels
  • Renamed generate_jinja2_context() to generate_context() in WorkingMemory and ContextProviderAbstract
  • Renamed ConceptProviderAbstract to ConceptLibraryAbstract
  • Renamed DomainProviderAbstract to DomainLibraryAbstract
  • Renamed PipeProviderAbstract to PipeLibraryAbstract
  • Renamed PipeInputSpec to InputRequirements
  • Renamed PipeInputSpecFactory to InputRequirementsFactory
  • Renamed pipe_input.py to input_requirements.py
  • Renamed pipe_input_factory.py to input_requirements_factory.py
  • Renamed pipe_input_blueprint.py to input_requirement_blueprint.py
  • Changed hub methods from get_*_provider() to get_*_library() pattern
  • Changed hub methods from set_*_provider() to set_*_library() pattern
  • Changed PipeLLM validation to check all inputs are in required variables
  • Updated LLMPromptSpec to handle image collections (lists/tuples) in addition to single images
  • Changed Mermaid diagram URL generation from /img/ to /svg/ endpoint
  • Changed PipeLLMPromptTemplate.make_llm_prompt() to private method _make_llm_prompt()
  • Updated pipe-builder prompts to include concept specs for better context
  • Updated PipelexBundleSpec.to_blueprint() to sort pipes by dependencies before creating bundle
  • Changed exception base class from PipelexError to PipelexException throughout codebase
  • Updated Makefile pyright target to use --pythonpath flag correctly
  • Enhanced LibraryManager to use importlib.resources for reliable PLX file discovery across all installation modes (wheel, source, relative path)
  • Simplified FuncRegistryUtils to exclusively register functions with @pipe_func decorator (removed decorator_names and require_decorator parameters)
  • Updated ReportingManager to get config directly instead of via constructor parameter
  • Updated PipeFunc documentation to reflect @pipe_func() decorator requirement and auto-discovery from anywhere in project
  • Added warnings about module-level code execution during auto-discovery to PipeFunc and StructuredContent documentation

Fixed

  • Fixed Makefile target pyright to use correct pythonpath flag
  • Fixed bug with inputs of the PipeLLM where image inputs couldn't be used and tagged in prompts
  • Fixed image input handling in LLMPromptSpec to support both single images and image collections
  • Fixed template preprocessing to handle jinja2 templates correctly
  • Fixed hard dependencies by moving imports to function scope in model_lists.py
  • Updated README badge URL to point to main branch instead of feature/pipe-builder branch

Removed

  • Removed centralized pipelex_libraries folder system and pipelex init libraries command
  • Removed config path parameters from Pipelex.make() (relative_config_folder_path, config_folder_path, from_file)
  • Removed Gemini 1.5 series models: gemini-1.5-pro, gemini-1.5-flash, and gemini-1.5-flash-8b
  • Removed base_templates.toml file (generic prompts moved to pipelex.toml)
  • Removed gpt-5-mini from possible models in pipe-builder
  • Removed useless functions in LLMJobFactory: make_llm_job_from_prompt_factory(), make_llm_job_from_prompt_template(), make_llm_job_from_prompt_contents()
  • Removed add_or_update_pipe() method from PipeLibrary
  • Removed get_optional_library_manager() method from PipelexHub
  • Removed get_optional_domain_provider() and get_optional_concept_provider() methods from hub
  • Removed unused test fixtures (apple, cherry, blueberry, concept_provider, pretty) from conftest.py
  • Removed some Vision/Image description pipes from the base library, because we doubt they were useful as they were
  • Removed pandas and openpyxl dependencies (including stubs: pandas-stubs, types-openpyxl)
  • Removed Excel file generation for cost reports and to_dataframe() method from CostRegistry
  • Removed should_warn_if_already_registered parameter from func_registry.register_function()
  • Removed decorator_names and require_decorator parameters from FuncRegistryUtils methods
  • Removed _find_plx_files_in_dir() and _get_pipelex_plx_files_from_dirs() methods from LibraryManager (refactored to library_utils module)
  • Removed hardcoded excluded directories from ClassRegistryUtils and FuncRegistryUtils (now use ScanConfig)
  • Removed are_classes_equivalent() and has_compatible_field() methods from ClassRegistryUtils (moved to class_utils module)

[v0.11.0] - 2025-10-01

Highlights

  • New pipe builder pipeline to generate Pipes based on a brief in natural language: use the cli pipelex build pipe "Your task" to build the pipe.
  • New observer system: inject your own class to observe and trace all details before and after each pipe run. We also provide a local observer that dumps the payloads to local JSONL files = new-line delilmited json, i.e. one json object per line.
  • Full refactoring of OCR and Image Generation to use the same patterns as LLM workers and pipes.

Added

  • Added claude-4.5-sonnet to the model deck.
  • Added a badge on the README.md to display the number of tests.
  • Added new test cases for environment variable functions
  • Added new documentation for PipeFunc on how to register functions.
  • Added pipelex show models [BACKEND_NAME] command to list available models from a specific backend.

Changed

  • Renamed llm_deck terminology to model_deck throughout codebase and documentation, now that it's also used for OCR and Image Generation models
  • Renamed is_gha_testing property to is_ci_testing in RuntimeManager
  • Refactored all_env_vars_are_set() function to only accept a list of keys, single string support now uses is_env_var_set()
  • Modified any_env_var_is_placeholder() to use new placeholder detection logic
  • Updated test environment setup to use dynamic placeholder generation instead of hardcoded values

Fixed

  • Fixed logic error in any_env_var_is_placeholder() function - now correctly returns False when no placeholders are found

Removed

  • Removed get_rooted_path() and get_env_rooted_path() utility functions which were not used
  • Removed hardcoded placeholder dictionary and ENV_DUMMY_PLACEHOLDER_VALUE constant in test setup
  • Removed function run_pipe_code in pipe router because it was not relevant (used mostly in tests)
  • Remove the use of PipeCompose in PipeCondition, to only use jinja2 directly, through the ContentGenerator
  • Remove the template libraries from the pipelex libraries.
  • Removed claude-3.5-sonnet and claude-3.5-sonnet-v2 from the model deck.

[v0.10.2] - 2025-09-18

Added

  • Unified OCR system using model handles instead of separate OcrHandle enum
  • ModelType enum supporting LLM and TEXT_EXTRACTOR types
  • Enhanced error handling in library loading with better validation messages
  • Config template management with config-template and cft Makefile targets to update templates from the .pipelex/ directory

Changed

  • ⚠️ Breaking changes:
  • Renamed ocr_handle to ocr_model in PipeExtract blueprint, so you'll need to update your PLX code accordingly
  • Updated .env.example file with slightly modified key names (more standard).
  • OCR system now uses InferenceModelSpec with unified model handles
  • Renamed get_llm_deck() to get_model_deck() and updated parameter names from llm_handle to model_handle
  • Simplified OCR worker factory using plugin SDK matching
  • Enhanced plugin system compatibility with InferenceModelSpec
  • Improved error messages throughout system
  • Improved management of placeholder environment variables for unit tests

Removed

  • Legacy OCR classes: OcrHandle, OcrPlatform, OcrEngine, OcrEngineFactory
  • Obsolete configuration fields and setup methods
  • PipelexFileError exception class

[v0.10.1] - 2025-09-17

Changed

  • Enabled all backends, still required to pass all unit tests.
  • A few tweaks to the base model deck.

[v0.10.0] - 2025-09-17

Highlight: New Inference Backend Configuration System

We've completely redesigned how LLMs are configured and accessed in Pipelex, making it more flexible and easier to get started:

  • Get started in seconds with Pipelex Inference: Use a single API key to access all major LLM providers (OpenAI, Anthropic, Google, Mistral, and more)
  • Flexible backend configuration: Configure multiple inference backends (Azure OpenAI, Amazon Bedrock, Vertex AI, etc.) through simple TOML files in .pipelex/inference/
  • Smart model routing: Automatically route models to the right backend using routing profiles with pattern matching
  • User-friendly aliases: Define shortcuts like best-claude → claude-4.1-opus with optional fallback chains
  • Cost-aware model specs: Each model includes detailed pricing, capabilities, and constraints for better cost management

For complete details, see the Inference Backend Configuration documentation.

Added

  • New inference backend configuration system in .pipelex/inference/ directory
  • Support for 10+ inference backends: OpenAI, Anthropic, Azure OpenAI, Amazon Bedrock, Mistral, Vertex AI, XAI, BlackboxAI, Perplexity, Ollama, and Pipelex Inference
  • Model routing profiles with pattern matching (*model*, model*, *model)
  • Model aliases with waterfall fallback chains
  • Environment variable and secret substitution in TOML configs (${VAR} and ${secret:KEY})
  • Comprehensive model specifications with detailed cost categories
  • Unified plugin SDK registry for all backends
  • CI environment detection with automatic placeholder API keys for testing
  • Improved pipelex init config command to copy entire configuration template directory structure to .pipelex/ with smart file handling (skips existing files, shows clear progress messages)
  • Added FuncRegistryUtils to register functions in a pipelex folder that have a specific signature.
  • Added mistral-medium and mistral-medium-2508 to the Mistral backend configuration.
  • Added gemini-2.5-flash to the VertexAI backend configuration.

Changed

  • LLM configuration moved from pipelex_libraries/llm_deck/ to .pipelex/inference/deck/
  • LLM handles simplified to direct model names or user-defined aliases
  • Model deck completely redesigned with inference models, aliases, and presets
  • Plugin system refactored to use backend-specific TOML configuration
  • Token categories renamed to cost categories with expanded types

Fixed

  • Improved error messages for missing environment variables
  • Enhanced TOML configuration validation
  • More robust model routing and backend selection

Removed

  • Legacy LLM model library system (llm_integrations/ directory)
  • Platform-specific configuration classes (AnthropicConfig, OpenAIConfig, etc.)
  • Deprecated LLM engine blueprint and factory classes
  • Old LLM platform and family enumerations

Security

  • Enhanced secret management with secure fallback patterns
  • Improved API key handling through centralized backend configuration

[v0.9.5] - 2025-09-12

Highlight

  • Pinned instructor to version <1.10.0 to avoid errors with mypy

Added

  • Added PIPELEX_INFERENCE LLM family enum value
  • Added support for PIPELEX_INFERENCE in OpenAI LLM worker
  • Added Azure OpenAI platform support for Grok models (grok-3 and grok-3-mini)
  • Added debug logging for PipeParallel output contents
  • Added TOML file filtering in LLM model library loading
  • Added error handling for Unicode decode errors in LLM model library
  • Added new test model configurations for pipelex and vertex_ai platforms

Changed

  • Improved error messages in StuffFactory to include concept code and stuff name
  • Disabled is_gen_object_supported for all Grok models (grok-3, grok-3-mini, grok-3-fast)
  • Updated test configurations to use different LLM models and platforms
  • Modified Jinja2 filter to use default TagStyle.TICKS instead of raising error
  • Added proper error handling for Unicode decode errors when loading model libraries
  • Improved error handling in Anthropic plugin tests with specific AuthenticationError handling
  • Image handling in AnthropicFactory now converts image URLs to base64 data URLs with proper MIME type prefix
  • Put back Discord link in README.md

Fixed

  • Pinned instructor to version <1.10.0 to avoid errors with mypy

[v0.9.4] - 2025-09-06

Added

  • Added support for BlackboxAI models

[v0.9.3] - 2025-09-06

Added

  • Better support for BlackboxAI IDE
  • VS Code extensions recommendations file with Pipelex, Ruff, and MyPy extensions
  • File association for .plx files in VS Code settings

[v0.9.2] - 2025-09-05

Fixed

  • Fix the rules of all agents.

Added

  • Added agent rule for copilot
  • Added a rule to forbidden structuring basic text concepts

[v0.9.1] - 2025-09-05

Fixed

  • Fixed many inconsistencies in the documentation.

[v0.9.0] - 2025-09-02

Refacto

  • Changed the pipeline file extension from .toml to .plx: Updated the LibraryManager in consequence.

Fixed

  • Fixed the structuring_method behavior in the PipeLLM pipe: Putting it to preliminary_text, the PipeLLM will always generate text before generating the structure -> Reliability increased by a lot.

Fixed

  • Fixed a bug in the needed_inputs method of the PipeSequence pipe.

Changed

  • dry_run_pipe now returns a DryRunOutput object instead of a str with additional information.
  • Updated cocode dependency from version v0.0.10 to v0.0.15.

Added

  • Added the FuncRegistryUtils class to register functions in the library.

[v0.8.1] - 2025-08-27

Bugfix

  • Bugfix: Fixed the PipeFunc output concept code and structure class name in the dry run.

[v0.8.0] - 2025-08-27

Refactor

  • Refactored the concepts: Blueprints are now more explicit, and hold only concept strings or code. Pipes hold concept instances.
  • Organized code: Created subfolders for controller and operator pipes.
  • Say goodbye to PipeLLMPrompt.
  • Removed the PipeCompose and PipeLLMPrompt from the PipeLLM.

Added

  • Added a lot of unit tests.
  • Loading the library can now be done from toml file or from PipelexBundleBlueprint.

Fixed

  • Backported backports.strenum to >=1.3.0 to support Python 3.10 now in dependencies and not in optional dependencies.

[v0.7.0] - 2025-08-20

Refactor

  • Refactored the Blueprints. Introduces the PipelexInterpreter that interprets the Pipelex language and creates the Pipelex Blueprints (and vice versa)
  • Modified the way we declare pipes. Use the field type = "PipeLLM" instead of field PipeLLM. (Same for all pipes)
  • Refactored the LibraryManager.
  • Refactored CLI commands and added new ones. Modified CLI command structure:
  • pipelex init - Initialization commands
    • pipelex init libraries [DIRECTORY] - Initialize pipelex libraries (creates pipelex_libraries folder)
    • pipelex init config - Initialize pipelex configuration (creates pipelex.toml)
  • pipelex validate - Validation and dry-run commands
    • pipelex validate all -c pipelex/libraries - Validate all libraries and dry-run all pipes
    • pipelex validate pipe PIPE_CODE - Dry run a single pipe by its code
  • pipelex show - Show and list commands
    • pipelex show config - Show the pipelex configuration
    • pipelex show pipes - List all available pipes with descriptions
    • pipelex show pipe PIPE_CODE - Show a single pipe definition
  • pipelex migrate - Migration commands
    • pipelex migrate run - Migrate TOML files to new syntax (with --dry-run and --backups options)
  • pipelex build - Build artifacts like pipeline blueprints
    • pipelex build draft PIPELINE_NAME - Generate a draft pipeline
    • pipelex build blueprint PIPELINE_NAME - Generate a pipeline blueprint
  • Organized concept, pipe, working_memory, stuff files into folders.

Changed

  • Allow aiofiles version >=23.2.1
  • GHA Cla assistant fixed with Github App

Added

  • New LLM families LLMFamily.GPT_5, LLMFamily.GPT_5_CHAT and LLMFamily.CLAUDE_4_1
  • Added support for Claude 4.1 and GPT 5 models (inc. mini, nano, chat)
  • New Pipe that generates pipe. Pipe code: build_blueprint
  • New tests. Especially for the PipelexInterpreter.
  • Migration files and cli commands to migrate Pipelex language to new syntax.
  • Introduces PipelexBundle, which correspond to the python paradigm of the Pipelex TOML syntax.

[v0.6.10] - 2025-08-02

Added

  • New test file for source code manipulation functions (tests/cases/source_code.py)
  • New integration test for PipeFunc functionality (tests/integration/pipelex/pipes/pipe_operator/pipe_func/test_pipe_func.py)
  • New package structure file for pipe_func tests (init.py)
  • Simplified input memory creation for native concepts (Text, Image, PDF) in pipeline execution
  • Added Pipeline requests link to GitHub issue template config

Changed

  • Updated pipeline execution documentation and examples to use input_memory instead of working_memory
  • Renamed pipeline from 'extract_page_contents_from_pdf' to 'ocr_page_contents_from_pdf'
  • Renamed pipeline from 'extract_page_contents_and_views_from_pdf' to 'ocr_page_contents_and_views_from_pdf'
  • Updated cocode dependency from version 0.0.6 to 0.0.9

Fixed

  • Fixed typo in pipeline description ('aspage views' to 'as full page views')

Removed

  • Removed WorkingMemoryFactory and StuffFactory imports from pipeline execution examples
  • Removed working memory creation code from pipeline examples

[v0.6.9] - 2025-07-26

Changed

Simplified input memory:

  • The concept code can now be provided with arg named concept in addition to concept_code
  • You can pass a simple string to create a Text stuff

[v0.6.8] - 2025-07-25

Added

  • New method make_stuff_using_concept_name_and_search_domains in StuffFactory for creating stuff using concept names and search domains.
  • New method make_stuff_from_stuff_content_using_search_domains in StuffFactory for creating stuff from stuff content using search domains.
  • New method make_from_implicit_memory in WorkingMemoryFactory for creating working memory from implicit memory.
  • New method create_mock_content in WorkingMemoryFactory for creating mock content for requirements.

Changed

  • Refactored PipeInput to use InputRequirement and TypedNamedInputRequirement classes instead of plain strings for input specifications.
  • Updated WorkingMemoryFactory to handle PipelineInputs instead of CompactMemory.
  • Replaced ExecutePipelineException with PipelineInputError in execute_pipeline function.
  • Updated PipeBatch, PipeCondition, PipeParallel, PipeSequence, PipeFunc, PipeImgGen, PipeCompose, PipeLLM, and PipeExtract classes to use InputRequirement for input handling.
  • Updated PipeInput creation in various test files to use make_from_dict method.
  • Updated pyproject.toml to exclude pypdfium2 version 4.30.1.
  • Updated Jinja2TemplateCategory to handle HTML and Markdown templates differently.

Fixed

  • Corrected error messages in StuffFactory and StuffContentFactory to provide more detailed information about exceptions.

[v0.6.7] - 2025-07-24

Removed

  • Removed the structure_classes parameter from the Pipelex class.

[v0.6.6] - 2025-07-24

Added

  • Added a new method verify_content_type in the Stuff class to verify and convert content to the expected type.
  • Added cocode==0.0.6 to the development dependencies in pyproject.toml.

Changed

  • Updated Stuff class methods to use the new verify_content_type method for content verification.
  • Updated vertexai.toml to change LLM IDs from preview models to released models: gemini-2.5-pro and gemini-2.5-flash.

Removed

  • Removed reinitlibraries, rl, v, and init targets from the Makefile.

[v0.6.5] - 2025-07-21

Fixed

  • In the documentation, fixed the use of execute_pipeline.

[v0.6.4] - 2025-07-19

  • Fixed the README.md link to the documentation

[v0.6.3] - 2025-07-18

Changed

  • Enhanced Stuff.content_as() method with improved type validation logic - now attempts model validation when isinstance check fails

[v0.6.2] - 2025-07-18

Added

  • New dry-run-pipe cli command to dry run a single pipe by its code
  • New show-pipe cli command to display pipe definitions from the pipe library
  • New dry_run_single_pipe() function for running individual pipe dry runs

Changed

  • Updated init-libraries command to accept a directory argument and create pipelex_libraries folder in specified location
  • Updated validate command to use -c flag for the config folder path

[v0.6.1] - 2025-07-16

  • Can execute pipelines with input_memory: It is a CompactMemory: Dict[str, Dict[str, Any]]

[v0.6.0] - 2025-07-15

Changed

  • Enhanced Pipelex.make() method: Complete overhaul of the initialization method with new path configuration options and robust validation:
  • Added relative_config_folder_path and absolute_config_folder_path parameters for flexible config folder specification
  • The from_file parameter controls path resolution: if True (default), relative paths are resolved relative to the caller's file location; if False, relative to the current working directory (useful for CLI scenarios)
  • Renamed Makefile targets like make doc to make docs for consistency

Added

  • Added github action for inference tests
  • load_json_list_from_path function in pipelex.tools.misc.file_utils: Loads a JSON file and ensures it contains a list.
  • Added issue templates
  • Updated Azure/OpenAI integrations, using dated deployment names systematically

[v0.5.2] - 2025-07-11

  • log a warning when dry running a PipeFunc
  • Update Readme.md

[v0.5.1] - 2025-07-09

Fixed

  • Fixed the ConceptFactory.make_from_blueprint method: Concepts defined in single-line format no longer automatically refine TextContent when a structure class with the same name exists
  • ConceptFactory.make_concept_from_definition is now ConceptFactory.make_concept_from_definition_str

Added

  • Bumped kajson to v0.3.0: Introducing MetaSingleton for better singleton management
  • Unit tests for ConceptLibrary.is_compatible_by_concept_code

[v0.5.0] - 2025-07-01

Highlight: Vibe Coding an AI workflow becomes a reality

Create AI workflows from natural language without writing code - The combination of Pipelex's declarative language, comprehensive Cursor rules, and robust validation tools enables AI assistants to autonomously iterate on pipelines until all errors are resolved and workflows are ready to run.

Added

  • Complete Dry Run & Static Validation System - A comprehensive validation framework that catches configuration and pipeline errors before any expensive inference operations.
  • WorkingMemoryFactory Enhancement: New make_for_dry_run() method creates working memory with realistic mock objects for zero-cost pipeline testing
  • Enhanced Dry Run System: Complete dry run support for all pipe controllers (PipeCondition, PipeParallel, PipeBatch) with mock data generation using polyfactory
  • Comprehensive Static Validation: Enhanced static validation with configurable error handling for missing/extraneous input variables and domain validation
  • TOML File Validation: Automatic detection and prevention of trailing whitespaces, formatting issues, and compilation blockers in pipeline files
  • Pipeline Testing Framework: New dry_run_all_pipes() method enables comprehensive testing of entire pipeline libraries
  • Enhanced Library Loading: Improved error handling and validation during TOML file loading with proper exception propagation

Configuration

  • Dry Run Configuration: New allowed_to_fail_pipes setting allows specific pipes (like infinite loop examples that fail on purpose) to be excluded from dry run validation
  • Static Validation Control: Configurable error reactions (raise, log, ignore) for different validation error types

Documentation & Development Experience

  • Cursor Rules Enhancement: Comprehensive pipe controller documentation covering PipeSequence, PipeCondition, PipeBatch, and PipeParallel, improved PipeOperator documentation for PipeLLM, PipeOCR
  • Pipeline Validation CLI: Enhanced pipelex validate all -c pipelex/libraries command with better error reporting and validation coverage
  • Improved Error Messages: Better formatting and context for pipeline configuration errors

Changed

  • Error Message Improvements: Updated PipeCondition error messages to reference expression_template instead of deprecated expression_jinja2

[v0.4.11] - 2025-06-30

  • LLM Settings Simplification: Streamlined LLM choice system by removing complex for_object_direct, for_object_list, and for_object_list_direct options. LLM selection now uses a simpler fallback pattern: specific choice → text choice → overrides → defaults.
  • Image Model Updates: Renamed image_bytes field to base_64 in PromptImageTypedBytes for better consistency. Updated to use CustomBaseModel base class to benefit from bytes truncation when printing.

[v0.4.10] - 2025-06-30

  • Fixed a bad import statement

[v0.4.9] - 2025-06-30

Highlights

Plugin System Refactoring - Complete overhaul of the plugin architecture to support external LLM providers.

Added

  • External Plugin Support: New LLMWorkerAbstract base class for integrating custom LLM providers, and we don't mean only an OpenAI-SDK-based LLM with a custom endpoint, now the implementation can be anything, as long as it implements the LLMWorkerAbstract interface.
  • Plugin SDK Registry: Better management of SDK instances with proper teardown handling
  • Enhanced Error Formatting: Improved Pydantic validation error messages for enums

Changed

  • Plugin Architecture: Moved plugin system to dedicated pipelex.plugins package
  • LLM Workers: Split into LLMWorkerInternalAbstract (for built-in providers) and LLMWorkerAbstract (for external plugins)
  • Configuration: Plugin configs moved from main pipelex.toml to separate pipelex_libraries/plugins/plugin_config.toml (⚠️ breaking change)
  • Error Handling: Standardized credential errors with new CredentialsError base class

[v0.4.8] - 2025-06-26

  • Added StorageProviderAbstract
  • Updated the changelog of v0.4.7: Moved Added StorageProviderAbstract to v0.4.8

[v0.4.7] - 2025-06-26

  • Added an API serializer: introducing the compact_memory, a new way to encode/decode the working memory as json, for the API.
  • When creating a Concept with no structure specified and no explicit refines, set it to refine native.Text
  • JobMetadata: added job_name. Removed top_job_id and wfid
  • PipeOutput: added pipeline_run_id

[v0.4.6] - 2025-06-24

  • Changed the link to the doc in the README.md: https://docs.pipelex.com

[v0.4.5] - 2025-06-23

Changed

  • Test structure overhaul: Reorganized test directory structure for better organization:
  • Tests now separated into unit/, integration/, and e2e/ directories
  • Created tests/cases/ package for pure test data and constants
  • Created tests/helpers/ package for test utilities
  • Cleaned up test imports and removed empty __init__.py files
  • Class registry refactoring: Updated kajson from 0.1.6 to 0.2.0, adapted to changes in Kajson's class registry with new ClassRegistryUtils (better separation of concerns)
  • Dependency updates:
  • Added pytest-mock to dev dependencies for improved unit testing

Added

  • Coverage commands: New Makefile targets for test coverage analysis:
  • make cov: Run tests with coverage report
  • make cov-missing (or make cm): Show coverage with missing lines
  • Test configuration: Set xfail_strict = true in pytest config for stricter test failure handling
  • Pydantic validation errors: Enhanced error formatting to properly handle model_type errors

Fixed

  • External links: Removed broken Markdown target="_blank" syntax from MANIFESTO.md links
  • Variable naming consistency: Fixed redundant naming in OpenAI config (openai_openai_config → openai_config)
  • Makefile optimization: Removed parallel test execution (-n auto) from codex-tests, works better now

Tests

  • Unit tests added: New comprehensive unit tests for:
  • ClassRegistryUtils
  • FuncRegistry
  • ModuleInspector
  • File finding utilities

[v0.4.4] - 2025-06-20

Fixed

  • Changed the allowed base branch names in the GHA guard-branches.yml: doc -> docs
  • Fixed kajson dependency (see kajson v0.1.6 changelog)

Cursor rules

  • Added Cursor rules for coding best practices and standards (including linting methods). Added TDD (Test Driven Development) rule on demand.
  • Various changes

Documentation

  • Added documentation for referencing images in PipeLLM.
  • Fixed typos

Refactor

  • Removed the images field from PipeLLM - images can now be referenced directly in the inputs
  • Moved the list-pipes CLI function to the PipeLibrary class.

[v0.4.3] - 2025-06-19

Fixed

  • Removed deprecated Gemini 1.5 models: Removed gemini-1.5-flash and gemini-1.5-pro from the VertexAI integration as they are no longer supported
  • Fixed multiple import statements across the codebase

Documentation

  • Enhanced MkDocs search: Added search functionality to the documentation site
  • Proofreading improvements: Fixed various typos and improved clarity across documentation

Refactor

  • Mini refactor: changed kajson dependency to kajson==0.1.5 (instead of >=) to tolerate temporary breaking changes from kajson

[v0.4.2] - 2025-06-17

  • Fixed the inheritance config manager method (Undocumented feature, soon to be removed)
  • Fixed the deploy-doc.yml GitHub Action
  • Grouped the mkdocs dependencies in a single group docs in the pyproject.toml file

[v0.4.1] - 2025-06-16

  • Changed discord link to the new one: https://go.pipelex.com/discord
  • Added hello-world example in the cookbook-examples of the documentation.

[v0.4.0] - 2025-06-16

Highlight: Complete documentation overhaul

  • MkDocs setup for static web docs generation
    • Material for MkDocs theme, custom styling and navigation
    • Other plugins: meta-manager, glightbox
    • GitHub Pages deployment, mapped to docs.pipelex.com
    • Added GHA workflows for documentation deployment and validation
  • Added to docs:
    • Manifesto explaining the Pipelex viewpoint
    • The Pipelex Paradigm explaining the fundamentals of Pipelex's solution
    • **Cookbook examples** presented and explained, commented code, some event with mermaid flow charts
    • And plenty of details about using Pipelex and developing for Pipelex, from structured generation to PipeOperators (LLM, Image generation, OCR…) to PipeControllers (Sequence, Parallel, Batch, Condition…), workflow optimization, workflow static validation and dry run… there's still work to do, but we move fast!
  • Also a major update of Cursor rules

Tooling Improvements

  • Pipeline tracking: restored visual flowchart generation using Mermaid
  • Enhanced dry run configuration: added more granular control with nb_list_items, nb_extract_pages, and image_urls
  • New feature flags: better control over pipeline tracking, activity tracking, and reporting
  • Improved OCR configuration: handle image file type for Mistral-OCR, added default_page_views_dpi setting
  • Enhanced LLM configuration: better prompting for structured generation with automatic schema insertion for two-step structuring: generate plain text and then structure via Json
  • Better logging: Enhanced log truncation and display for large objects like image bytes (there are still cases to deal with)

Refactor

Concept system refactoring

  • Improved concept code factory with better domain handling, so you no longer need the native domain prefix for native domains, you can just call them by their names: Text, Image, PDF, Page, Number…
  • Concept refines attribute can now be a string for single refined concepts (the most common case)

Breaking Changes

  • File structure changes: documentation moved from doc/ to docs/
  • Configuration changes: some configuration keys have been renamed or restructured
  • StuffFactory.make_stuff() argument concept_code renamed to concept_str to explicitly support concepts without fully qualified domains (e.g., Text or PDF implicitly native )
  • Some method signatures have been updated

Tests

  • Added Concept refinement validation: TestConceptRefinesValidationFunction and TestConceptPydanticFieldValidation ensure proper concept inheritance and field validation

[v0.3.2] - 2025-06-13

  • Improved automatic insertion of class structure from BaseModel into prompts, based on the PipeLLM's output_concept. New unit test included.
  • The ReportingManager now reports costs for all pipeline IDs when no pipeline_run_id is specified.
  • The make_from_str method from the StuffFactory class now uses Text context by default.

[v0.3.1] - 2025-06-10

Added

  • New pytest marker dry_runnable for tests that can run without inference.
  • Enhanced make targets with dry-run capabilities for improved test coverage:
  • make test-xdist (or make t): Runs all non-inference tests plus inference tests that support dry-runs - fast and resource-efficient
  • make test-inference (or make ti): Runs tests requiring actual inference, with actual inference (slow and costly)
  • Parallel test execution using pytest-xdist (-n auto) enabled for:
  • GitHub Actions workflows
  • Codex test targets

Changed

  • Domain validation is now less restrictive in pipeline TOML: the description attribute is now Optional

[v0.3.0] - 2025-06-09

Highlights

  • Structured Input Specifications: Pipe inputs are now defined as a dictionary mapping a required variable name to a concept code (required_variable -> concept_code). This replaces the previous single input field and allows for multiple, named inputs, making pipes more powerful and explicit. This is a breaking change.
  • Static Validation for Inference Pipes: You can now catch configuration and input mistakes in your pipelines before running any operations. This static validation checks PipeLLM, PipeExtract, and PipeImgGen. Static validation for controller pipes (PipeSequence, PipeParallel…) will come in a future release.
    • Configure the behavior for different error types using the static_validation_config section in your settings. For each error type, choose to raise, log, or ignore.
  • Dry Run Mode for Zero-Cost Pipeline Validation: A powerful dry-run mode allows you to test entire pipelines without making any actual inference calls. It's fast, costs nothing, works offline, and is perfect for linting and validating pipeline logic.
    • The new dry_run_config lets you control settings, like disabling Jinja2 rendering during a dry run.
    • This feature leverages polyfactory to generate mock Pydantic models for simulated outputs.
    • Error handling for bad inputs during run_pipe has been improved and is fully effective in dry-run mode.
    • One limitation: currently, dry running doesn't work when the pipeline uses a PipeCondition. This will be fixed in a future release.

Added

  • native.Anything Concept: A new flexible native concept that is compatible with any other concept, simplifying pipe definitions where input types can vary.
  • Added dependency on polyfactory for mock Pydantic model generation in dry-run mode.

Changed

  • Refactored Cognitive Workers: The abstraction for LLM, ImgGen, and Ocr workers has been elegantly simplified. The old decorator-based approach (..._job_func) has been replaced with a more robust pattern: a public base method now handles pre- and post-execution logic while calling a private abstract method that each worker implements.
  • The b64_image_bytes field in PromptImageBytes was renamed to base_64 for better consistency.

Fixed

  • Resolved a logged error related to the pipe stack when using PipeParallel.
  • The pipe tracker functionality has been restored. It no longer crashes when using nested object attributes (e.g., my_object.attribute) as pipe inputs.

Tests

  • A new pytest command-line option --pipe-run-mode has been added to switch between live and dry runs (default is dry). All pipe tests now respect this mode.
  • Introduced the pipelex_api pytest marker for tests related to the Pipelex API client, separating them from general inference or llm tests.
  • Added a make test-pipelex-api target (shorthand: make ta) to exclusively run these new API client tests.

Removed

  • The llm_job_func.py file and the associated decorators have been removed as part of the cognitive worker refactoring.

[v0.2.14] - 2025-06-06

  • Added a feature flag for the ReportingManager in the config: 
    [pipelex]
[pipelex.feature_config]
is_reporting_enabled = true
  • Moved the reporting config form the cogtconfig to the Pipelex config.

[v0.2.13] - 2025-06-06

  • Added Discord badge on the Readme. Join the community! -> https://go.pipelex.com/discord
  • Added a client for the Pipelex API. Join the waitlist -> https://www.pipelex.com/signup
  • Removed the run_pipe_code function. Replaced by execute_pipeline in pipelex.pipeline.execute.
  • Added llm deck llm_for_img_to_text.
  • Renamed InferenceReportManager to ReportingManager: It can report more than Inference cost. Renamed InferenceReportDelegate to ReportingProtocol.
  • Added an injection of dependency for ReportingManager
  • pipelex cli: fixed some bugs

[v0.2.12] - 2025-06-03

  • pipelex cli: Split pipelex init into 2 separate functions: pipelex init-libraries and pipelex init-config
  • Fixed the inheritance config manager method
  • Rename Mission to Pipeline
  • Enable to start a pipeline and let in run in the background, getting it's run id, but not waiting for the output
  • Makefile: avoid defaulting pytest to verbose. Setup target make test-xdist = Run unit tests with xdist, make it the default for shorthand make t. The old make t is now make tp (test-with-prints)
  • Added mistral-small-3.1 and qwen3:8b
  • Fix template pre-processor: don't try and substitute a dollar numerical like $10 or @25
  • Refactor with less "OpenAI" naming for non-openai stuff that just uses the OpenAI SDK

[v0.2.11] - 2025-06-02

  • HotFix for v0.2.10 👇 regarding the new pipelex/pipelex_init.toml`

[v0.2.10] - 2025-06-02

Highlights

Python Support Expansion - We're no longer tied to Python 3.11! Now supporting Python 3.10, 3.11, 3.12, and 3.13 with full CI coverage across all versions.

Major Model Additions - Claude 4 (Opus & Sonnet), Grok-3, and GPT-4 image generation are now in the house.

Pipeline Base Library update

  • New pipe - ocr_page_contents_and_views_from_pdf transferred from cookbook to base library (congrats on the promotion!). This pipe extracts text, linked images, AND page_view images (rendered pages) - it's very useful if you want to use Vision in follow-up pipes

Added

  • Template preprocessor - New @? token prefix for optional variable insertion - if a variable doesn't exist, we gracefully skip it instead of throwing exceptions
  • Claude 4 support - Both Opus and Sonnet variants, available through Anthropic SDK (direct & Bedrock) plus Bedrock SDK. Includes specific max_tokens limit reduction to prevent timeout/streaming issues (temporary workaround)
  • Grok-3 family support - Full support via OpenAI SDK for X.AI's latest models
  • GPT-4 image generation - New gpt-image-1 model through OpenAI SDK, available via PipeImgGen. Currently saves local files (addressing in next release)
  • Gemini update - Added latest gemini-2.5-pro to the lineup
  • Image generation enhancements - Better quality controls, improved background handling options, auto-adapts to different models: Flux, SDXL and now gpt-image-1

Refactored

  • Moved subpackage plugin to the same level as cogt within pipelex for better visibility
  • Major cleanup in the unit tests, hierarchy significantly flattened
  • Strengthened error handling throughout inference flows and template preprocessing
  • Added make test-quiet (shorthand tq) to Makefile to run tests without capturing outputs (i.e. without pytest -s option)
  • Stopped using Fixtures for pipe_router and content_generator: we're now always getting the singleton from pipelex.hub

Fixed

  • Perplexity integration - Fixed breaking changes from recent updates

Dependencies

  • Added pytest-xdist to run unit tests in parallel on multiple CPUs. Not yet integrated into the Makefile, so run it manually with pytest -n auto (without inference) or pytest -n auto -m "inference" (inference only).
  • Swapped pytest-pretty for pytest-sugar - because readable test names > pretty tables
  • Updated instructor to v1.8.3
  • All dependencies tested against Python 3.10, 3.11, 3.12, and 3.13

Tests

  • TestTemplatePreprocessor
  • TestImgGenByOpenAIGpt
  • TestImageGeneration
  • TestPipeImgGen

[v0.2.9] - 2025-05-30

  • Include pyproject.toml inside the project build.
  • Fix ImgGenEngineFactory: image generation (imgg) handle required format is platform/model_name
  • pipelex cli: Added list-pipes method that can list all the available pipes along with their descriptions.
  • Use a minimum version for uv instead of a fixed version
  • Implement AGENTS.md for Codex
  • Add tests for some of the tools.misc
  • pipelex cli: Rename pipelex run-setup to pipelex validate all -c pipelex/libraries

[v0.2.8] - 2025-05-28

  • Replaced poetry by uv for dependency management.
  • Simplify llm provider config: All the API keys, urls, and regions now live in the .env.
  • Added logging level OFF, prevents any log from hitting the console

[v0.2.7] - 2025-05-26

  • Reboot repository

[v0.2.6] - 2025-05-26

  • Refactor: use ActivityManagerProtocol, rename BaseModelTypeVar

[v0.2.5] - 2025-05-25

  • Add custom LLM integration via OpenAI sdk with custom base_url

[v0.2.4] - 2025-05-25

  • Tidy tools
  • Tidy inference API plugins
  • Tidy WIP feature ActivityManager

[v0.2.2] - 2025-05-22

  • Simplify the use of native concepts
  • Include "page views" in the outputs of Ocr features

[v0.2.1] - 2025-05-22

  • Added OcrWorkerAbstract and MistralOcrWorker, along with PipeExtract for OCR processing of images and PDFs.
  • Introduced MissionManager for managing missions, cost reports, and activity tracking.
  • Added detection and handling for pipe stack overflow, configurable with pipe_stack_limit.
  • More possibilities for dependency injection and better class structure.
  • Misc updates including simplified PR template, LLM deck overrides, removal of unused config vars, and disabling of an LLM platform id.

[v0.2.0] - 2025-05-19

  • Added OCR, thanks to Mistral
  • Refactoring and cleanup

[v0.1.14] - 2025-05-13

  • Initial release 🎉