ht-docker-ai/changelog.md

Changelog

2026-01-20 - 1.15.2 - fix(dev-deps)

bump devDependencies @push.rocks/smartagent to ^1.6.2 and @push.rocks/smartai to ^0.13.3

• Bumped @push.rocks/smartagent from ^1.5.4 to ^1.6.2 in devDependencies
• Bumped @push.rocks/smartai from ^0.13.2 to ^0.13.3 in devDependencies
• Updated test/test.invoices.nanonets.ts JSON extraction prompt: instruct not to omit special characters in invoice_number and to use the json validate tool
• No breaking changes; only dev dependency updates and test prompt adjustments

2026-01-20 - 1.15.1 - fix(tests)

enable progress events in invoice tests and bump @push.rocks/smartagent devDependency to ^1.5.4

• Added an onProgress handler in test/test.invoices.nanonets.ts to log progress events (console.log(event.logMessage)) so tool calls and progress are visible during tests.
• Bumped devDependency @push.rocks/smartagent from ^1.5.2 to ^1.5.4 in package.json.

2026-01-20 - 1.15.0 - feat(tests)

integrate SmartAi/DualAgentOrchestrator into extraction tests and add JSON self-validation

• Integrate SmartAi and DualAgentOrchestrator into bankstatement and invoice tests to perform structured extraction with streaming
• Register and use JsonValidatorTool to validate outputs (json.validate) and enforce validation before task completion
• Add tryExtractJson parsing fallback, improved extraction prompts, retries and clearer parsing/logging
• Initialize and teardown SmartAi and orchestrator in test setup/summary, and enable onToken streaming handlers for real-time output
• Bump devDependencies: @push.rocks/smartagent to ^1.3.0 and @push.rocks/smartai to ^0.12.0

2026-01-20 - 1.14.3 - fix(repo)

no changes detected in the diff; no files modified and no release required

• Diff contained no changes
• No files were added, removed, or modified
• No code, dependency, or documentation updates to release

2026-01-19 - 1.14.2 - fix(readme)

update README to document Nanonets-OCR2-3B (replaces Nanonets-OCR-s), adjust VRAM and context defaults, expand feature docs, and update examples/test command

• Renamed Nanonets-OCR-s -> Nanonets-OCR2-3B throughout README and examples
• Updated Nanonets VRAM guidance from ~10GB to ~12-16GB and documented 30K context
• Changed documented MAX_MODEL_LEN default from 8192 to 30000
• Updated example model identifiers (model strings and curl/example snippets) to nanonets/Nanonets-OCR2-3B
• Added MiniCPM and Qwen feature bullets (multilingual, multi-image, flowchart support, expanded context notes)
• Replaced README test command from ./test-images.sh to pnpm test

2026-01-19 - 1.14.1 - fix(extraction)

improve JSON extraction prompts and model options for invoice and bank statement tests

• Refactor JSON extraction prompts to be sent after the document text and add explicit 'WHERE TO FIND DATA' and 'RULES' sections for clearer extraction guidance
• Change chat message flow to: send document, assistant acknowledgement, then the JSON extraction prompt (avoids concatenating large prompts into one message)
• Add model options (num_ctx: 32768, temperature: 0) to give larger context windows and deterministic JSON output
• Simplify logging to avoid printing full prompt contents; log document and prompt lengths instead
• Increase timeouts for large documents to 600000ms (10 minutes) where applicable

2026-01-19 - 1.14.0 - feat(docker-images)

add vLLM-based Nanonets-OCR2-3B image, Qwen3-VL Ollama image and refactor build/docs/tests to use new runtime/layout

• Add new Dockerfiles for Nanonets (Dockerfile_nanonets_vllm_gpu_VRAM10GB), Qwen3 (Dockerfile_qwen3vl_ollama_gpu_VRAM20GB) and a clarified MiniCPM Ollama variant (Dockerfile_minicpm45v_ollama_gpu_VRAM9GB); remove older, redundant Dockerfiles.
• Update build-images.sh to build the new image tags (minicpm45v, qwen3vl, nanonets-ocr) and adjust messaging/targets accordingly.
• Documentation overhaul: readme.md and readme.hints.md updated to reflect vLLM vs Ollama runtimes, corrected ports/VRAM estimates, volume recommendations, and API endpoint details.
• Tests updated to target the new model ID (nanonets/Nanonets-OCR2-3B), to process one page per batch, and to include a 10-minute AbortSignal timeout for OCR requests.
• Added focused extraction test suites (test/test.invoices.extraction.ts and test/test.invoices.failed.ts) for faster iteration and debugging of invoice extraction.
• Bump devDependencies: @git.zone/tsrun -> ^2.0.1 and @git.zone/tstest -> ^3.1.5.
• Misc: test helper references and docker compose/test port mapping fixed (nanonets uses 8000), and various README sections cleaned and reorganized.

2026-01-18 - 1.13.2 - fix(tests)

stabilize OCR extraction tests and manage GPU containers

• Add stopAllGpuContainers() and call it before starting GPU images to free GPU memory.
• Remove PaddleOCR-VL image configs and associated ensure helpers from docker test helper to simplify images list.
• Split invoice/bankstatement tests into two sequential stages: Stage 1 runs Nanonets OCR to produce markdown files, Stage 2 stops Nanonets and runs model extraction from saved markdown (avoids GPU contention).
• Introduce temporary markdown directory handling and cleanup; add stopNanonets() and container running checks in tests.
• Switch bank statement extraction model from qwen3:8b to gpt-oss:20b; add request timeout and improved logging/console output across tests.
• Refactor extractWithConsensus and extraction functions to accept document identifiers, improve error messages and JSON extraction robustness.

2026-01-18 - 1.13.1 - fix(image_support_files)

remove PaddleOCR-VL server scripts from image_support_files

• Deleted files: image_support_files/paddleocr_vl_full_server.py (approx. 636 lines) and image_support_files/paddleocr_vl_server.py (approx. 465 lines)
• Cleanup/removal of legacy PaddleOCR-VL FastAPI server implementations — may affect users who relied on these local scripts

2026-01-18 - 1.13.0 - feat(tests)

revamp tests and remove legacy Dockerfiles: adopt JSON/consensus workflows, switch MiniCPM model, and delete deprecated Docker/test variants

• Removed multiple Dockerfiles and related entrypoints for MiniCPM and PaddleOCR-VL (cpu/gpu/full), cleaning up legacy image recipes.
• Pruned many older test files (combined, ministral3, paddleocr-vl, and several invoice/test variants) to consolidate the test suite.
• Updated bank statement MiniCPM test: now uses MODEL='openbmb/minicpm-v4.5:q8_0', JSON per-page extraction prompt, consensus retry logic, expanded logging, and stricter result matching.
• Updated invoice MiniCPM test: switched to a consensus flow (fast JSON pass + thinking pass), increased PDF conversion quality, endpoints migrated to chat-style API calls with image-in-message payloads, and improved finalization logic.
• API usage changed from /api/generate to /api/chat with message-based payloads and embedded images — CI and local test runners will need model availability and possible pipeline adjustments.

2026-01-18 - 1.12.0 - feat(tests)

switch vision tests to multi-query extraction (count then per-row/field queries) and add logging/summaries

• Replace streaming + consensus pipeline with multi-query approach: count rows per page, then query each transaction/field individually (batched parallel queries).
• Introduce unified helpers (queryVision / queryField / getTransaction / countTransactions) and simplify Ollama requests (stream:false, reduced num_predict, /no_think prompts).
• Improve parsing and normalization for amounts (European formats), invoice numbers, dates and currency extraction.
• Adjust model checks to look for generic 'minicpm' and update test names/messages; add pass/fail counters and a summary test output.
• Remove previous consensus voting and streaming JSON accumulation logic, and add immediate per-transaction logging and batching.

2026-01-18 - 1.11.0 - feat(vision)

process pages separately and make Qwen3-VL vision extraction more robust; add per-page parsing, safer JSON handling, reduced token usage, and multi-query invoice extraction

• Bank statements: split extraction into extractTransactionsFromPage and sequentially process pages to avoid thinking-token exhaustion
• Bank statements: reduced num_predict from 8000 to 4000, send single image per request, added per-page logging and non-throwing handling for empty or non-JSON responses
• Bank statements: catch JSON.parse errors and return empty array instead of throwing
• Invoices: introduced queryField to request single values and perform multiple simple queries (reduces model thinking usage)
• Invoices: reduced num_predict for invoice queries from 4000 to 500 and parse amounts robustly (handles European formats like 1.234,56)
• Invoices: normalize currency to uppercase 3-letter code, return safe defaults (empty strings / 0) instead of nulls, and parse net/vat/total with fallbacks
• General: simplified Ollama API error messages to avoid including response body content in thrown errors

2026-01-18 - 1.10.1 - fix(tests)

improve Qwen3-VL invoice extraction test by switching to non-stream API, adding model availability/pull checks, simplifying response parsing, and tightening model options

• Replaced streaming reader logic with direct JSON parsing of the /api/chat response
• Added ensureQwen3Vl() to check and pull the Qwen3-VL:8b model from Ollama
• Switched to ensureMiniCpm() to verify Ollama service is running before model checks
• Use /no_think prompt for direct JSON output and set temperature to 0.0 and num_predict to 512
• Removed retry loop and streaming parsing; improved error messages to include response body
• Updated logging and test setup messages for clarity

2026-01-18 - 1.10.0 - feat(vision)

add Qwen3-VL vision model support with Dockerfile and tests; improve invoice OCR conversion and prompts; simplify extraction flow by removing consensus voting

• Add Dockerfile_qwen3vl to provide an Ollama-based image for Qwen3-VL and expose the Ollama API on port 11434
• Introduce test/test.invoices.qwen3vl.ts and ensureQwen3Vl() helper to pull and test qwen3-vl:8b
• Improve PDF->PNG conversion and prompt in ministral3 tests (higher DPI, max quality, sharpen) and increase num_predict from 512 to 1024
• Simplify extraction pipeline: remove consensus voting, log single-pass results, and simplify OCR HTML sanitization/truncation logic

2026-01-18 - 1.9.0 - feat(tests)

add Ministral 3 vision tests and improve invoice extraction pipeline to use Ollama chat schema, sanitization, and multi-page support

• Add new vision-based test suites for Ministral 3: test/test.invoices.ministral3.ts and test/test.bankstatements.ministral3.ts (model ministral-3:8b).
• Introduce ensureMinistral3() helper to start/check Ollama/MiniCPM model in test/helpers/docker.ts.
• Switch invoice extraction to use Ollama /api/chat with a JSON schema (format) and streaming support (reads message.content).
• Improve HTML handling: sanitizeHtml() to remove OCR artifacts, concatenate multi-page HTML with page markers, and increase truncation limits.
• Enhance response parsing: strip Markdown code fences, robustly locate JSON object boundaries, and provide clearer JSON parse errors.
• Add PDF->PNG conversion (ImageMagick) and direct image-based extraction flow for vision model tests.

2026-01-18 - 1.8.0 - feat(paddleocr-vl)

add structured HTML output and table parsing for PaddleOCR-VL, update API, tests, and README

• Add result_to_html(), parse_markdown_table(), and parse_paddleocr_table() to emit semantic HTML and convert OCR/markdown tables to proper elements
• Enhance result_to_markdown() with positional/type hints (header/footer/title/table/figure) to improve downstream LLM processing
• Expose 'html' in supported formats and handle output_format='html' in parse endpoints and CLI flow
• Update tests to request HTML output and extract invoice fields from structured HTML (test/test.invoices.paddleocr-vl.ts)
• Refresh README with usage, new images/tags, architecture notes, and troubleshooting for the updated pipeline

2026-01-17 - 1.7.1 - fix(docker)

standardize Dockerfile and entrypoint filenames; add GPU-specific Dockerfiles and update build and test references

• Added Dockerfile_minicpm45v_gpu and image_support_files/minicpm45v_entrypoint.sh; removed the old Dockerfile_minicpm45v and docker-entrypoint.sh
• Renamed and simplified PaddleOCR entrypoint to image_support_files/paddleocr_vl_entrypoint.sh and updated CPU/GPU Dockerfile references
• Updated build-images.sh to use *_gpu Dockerfiles and clarified PaddleOCR GPU build log
• Updated test/helpers/docker.ts to point to Dockerfile_minicpm45v_gpu so tests build the GPU variant

2026-01-17 - 1.7.0 - feat(tests)

use Qwen2.5 (Ollama) for invoice extraction tests and add helpers for model management; normalize dates and coerce numeric fields

• Added ensureOllamaModel and ensureQwen25 test helpers to pull/check Ollama models via localhost:11434
• Updated invoices test to use qwen2.5:7b instead of MiniCPM and removed image payload from the text-only extraction step
• Increased Markdown truncate limit from 8000 to 12000 and reduced model num_predict from 2048 to 512
• Rewrote extraction prompt to require strict JSON output and added post-processing to parse/convert numeric fields
• Added normalizeDate and improved compareInvoice to normalize dates and handle numeric formatting/tolerance
• Updated test setup to ensure Qwen2.5 is available and adjusted logging/messages to reflect the Qwen2.5-based workflow

2026-01-17 - 1.6.0 - feat(paddleocr-vl)

add PaddleOCR-VL full pipeline Docker image and API server, plus integration tests and docker helpers

• Add Dockerfile_paddleocr_vl_full and entrypoint script to build a GPU-enabled image with PP-DocLayoutV2 + PaddleOCR-VL and a FastAPI server
• Introduce image_support_files/paddleocr_vl_full_server.py implementing the full pipeline API (/parse, OpenAI-compatible /v1/chat/completions) and a /formats endpoint
• Improve image handling: decode_image supports data URLs, HTTP(S), raw base64 and file paths; add optimize_image_resolution to auto-scale images into the recommended 1080-2048px range
• Add test helpers (test/helpers/docker.ts) to build/start/health-check Docker images and new ensurePaddleOcrVlFull workflow
• Add comprehensive integration tests for bank statements and invoices (MiniCPM and PaddleOCR-VL variants) and update tests to ensure required containers are running before tests
• Switch MiniCPM model references to 'minicpm-v:latest' and increase health/timeout expectations for the full pipeline

2026-01-17 - 1.5.0 - feat(paddleocr-vl)

add PaddleOCR-VL GPU Dockerfile, pin vllm, update CPU image deps, and improve entrypoint and tests

• Add a new GPU Dockerfile for PaddleOCR-VL (transformers-based) with CUDA support, healthcheck, and entrypoint.
• Pin vllm to 0.11.1 in Dockerfile_paddleocr_vl to use the first stable release with PaddleOCR-VL support.
• Update CPU image: add torchvision==0.20.1 and extra Python deps (protobuf, sentencepiece, einops) required by the transformers-based server.
• Rewrite paddleocr-vl-entrypoint.sh to build vllm args array, add MAX_MODEL_LEN and ENFORCE_EAGER env vars, include --limit-mm-per-prompt and optional --enforce-eager, and switch to exec vllm with constructed args.
• Update tests to use the OpenAI-compatible PaddleOCR-VL chat completions API (/v1/chat/completions) with image+text message payload and model 'paddleocr-vl'.
• Add @types/node to package.json dependencies and tidy devDependencies ordering.

2026-01-16 - 1.4.0 - feat(invoices)

add hybrid OCR + vision invoice/document parsing with PaddleOCR, consensus voting, and prompt/test refactors

• Add hybrid pipeline documentation and examples (PaddleOCR + MiniCPM-V) and architecture diagram in recipes/document.md
• Integrate PaddleOCR: new OCR extraction functions and OCR-only prompt flow in test/test.node.ts
• Add consensus voting and parallel-pass optimization to improve reliability (multiple passes, hashing, and majority voting)
• Refactor prompts and tests: introduce /nothink token, OCR truncation limits, separate visual and OCR-only prompts, and improved prompt building in test/test.invoices.ts
• Update image conversion defaults (200 DPI, filename change) and add TypeScript helper functions for extraction and consensus handling

2026-01-16 - 1.3.0 - feat(paddleocr)

add PaddleOCR OCR service (Docker images, server, tests, docs) and CI workflows

• Add GPU and CPU PaddleOCR Dockerfiles; pin paddlepaddle/paddle and paddleocr to stable 2.x and install libgomp1 for CPU builds
• Avoid pre-downloading OCR models at build-time to prevent build-time segfaults; models are downloaded on first run
• Refactor PaddleOCR FastAPI server: respect CUDA_VISIBLE_DEVICES, support per-request language, cache default language instance and create temporary instances for other languages
• Add comprehensive tests (test.paddleocr.ts) and improve invoice extraction tests (parallelize passes, JSON OCR API usage, prioritize certain test cases)
• Add Gitea CI workflows for tag and non-tag Docker runs and release pipeline (docker build/push, metadata trigger)
• Update documentation (readme.hints.md) with PaddleOCR usage and add docker registry entry to npmextra.json

2026-01-16 - 1.2.0 - feat(paddleocr)

add PaddleOCR support: Docker images, FastAPI server, entrypoint and tests

• Add PaddleOCR FastAPI server implementation at image_support_files/paddleocr_server.py
• Remove old image_support_files/paddleocr-server.py and update entrypoint to import paddleocr_server:app
• Extend build-images.sh to build paddleocr (GPU) and paddleocr-cpu images and list them
• Extend test-images.sh to add paddleocr health/OCR tests, new test_paddleocr_image function, port config, and cleanup; rename test_image -> test_minicpm_image

2026-01-16 - 1.1.0 - feat(ocr)

add PaddleOCR GPU Docker image and FastAPI OCR server with entrypoint; implement OCR endpoints and consensus extraction testing

• Add Dockerfile_paddleocr for GPU-accelerated PaddleOCR image (pre-downloads PP-OCRv4 models, exposes port 5000, healthcheck, entrypoint)
• Add image_support_files/paddleocr-server.py: FastAPI app providing /ocr (base64), /ocr/upload (file), and /health endpoints; model warm-up on startup; structured JSON responses and error handling
• Add image_support_files/paddleocr-entrypoint.sh to configure environment, detect GPU/CPU mode, and launch uvicorn
• Update test/test.node.ts to replace streaming extraction with a consensus-based extraction flow (multiple passes, hashing of results, majority voting) and improve logging/prompt text
• Add test/test.invoices.ts: integration tests for invoice extraction that call PaddleOCR, build prompts with optional OCR text, run consensus extraction, and produce a summary report

2026-01-16 - 1.0.0 - initial release

Initial project files added with two small follow-up updates.

• initial: base project commit.
• update: two minor follow-up updates refining the initial commit.