# v1.0.0 - First Release 🎉#306
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kevin-mindverse merged 21 commits intomasterfrom Apr 29, 2025
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* fix:fix l1 save problem * fix:simplify the code * fix:delete no use import * fix:delete useless data
* fix password update logic, if there's more than one load * update fix
* fix: modify thinking_model loading configuration * feat: realize thinkModel ui * feat:store * feat: add combined_llm_config_dto * add thinking_model_config & database migration * directly add thinking model to user_llm_config * delete thinking model repo dto service * delete thinkingmodel table migration * add is_cot config * feat: allow define is_cot * feat: simplify logs info * feat: add training model * feat: fix is_cot problem * fix: fix chat message * fix: fix progress error * fix: disable no settings thinking * feat: add thinking warning * fix: fix start service error * feat:fix init trainparams problem * feat: change playGround prompt * feat: Add Dimension Mismatch Handling for ChromaDB (#157) (#207) * Fix Issue #157 Add chroma_utils.py to manage chromaDB and added docs for explanation * Add logging and debugging process - Enhanced the`reinitialize_chroma_collections` function in`chroma_utils.py` to properly check if collections exist before attempting to delete them, preventing potential errors when collections don't exist. - Improved error handling in the`_handle_dimension_mismatch` method in`embedding_service.py` by adding more robust exception handling and verification steps after reinitialization. - Enhanced the collection initialization process in`embedding_service.py` to provide more detailed error messages and better handle cases where collections still have incorrect dimensions after reinitialization. - Added additional verification steps to ensure that collection dimensions match the expected dimension after creation or retrieval. - Improved logging throughout the code to provide more context in error messages, making debugging easier. * Change topics_generator timeout to 30 (#263) * quick fix * fix: shade -> shade_merge_info (#265) * fix: shade -> shade_merge_info * add convert array * quick fix import error * add log * add heartbeat * new strategy * sse version * add heartbeat * zh to en * optimize code * quick fix convert function * Feat/new branch management (#267) * feat: new branch management * feat: fix multi-upload * optimize contribute management --------- Co-authored-by: Crabboss Mr <1123357821@qq.com> Co-authored-by: Ye Xiangle <yexiangle@mail.mindverse.ai> Co-authored-by: Xinghan Pan <sampan090611@gmail.com> Co-authored-by: doubleBlack2 <108928143+doubleBlack2@users.noreply.github.com> Co-authored-by: kevin-mindverse <kevin@mindverse.ai> Co-authored-by: KKKKKKKevin <115385420+kevin-mindverse@users.noreply.github.com>
* feat: replace tutorial link * replace video link --------- Co-authored-by: kevin-mindverse <kevin@mindverse.ai>
* Add CUDA support - CUDA detection - Memory handling - Ollama model release after training * Fix logging issue added cuda support flag so log accurately reflected cuda toggle * Update llama.cpp rebuild Changed llama.cpp to only check if cuda support is enabled and if so rebuild during the first build rather than each run * Improved vram management Enabled memory pinning and optimizer state offload * Fix CUDA check rewrote llama.cpp rebuild logic, added manual y/n toggle if user wants to enable cuda support * Added fast restart and fixed CUDA check command Added make docker-restart-backend-fast to restart the backend and reflect code changes without causing a full llama.cpp rebuild Fixed make docker-check-cuda command to correctly reflect cuda support * Added docker-compose.gpu.yml Added docker-compose.gpu.yml to fix error on machines without nvidia gpu and made sure "\n" is added before .env modification * Fixed cuda toggle Last push accidentally broke cuda toggle * Code review fixes Fixed errors resulting from removed code: - Added return save_path to end of save_hf_model function - Rolled back download_file_with_progress function * Update Makefile Use cuda by default when using docker-restart-backend-fast * Minor cleanup Removed unnecessary makefile command and fixed gpu logging * Delete .gpu_selected * Simplified cuda training code - Removed dtype setting to let torch automatically handle it - Removed vram logging - Removed Unnecessary/old comments * Fixed gpu/cpu selection Made "make docker-use-gpu/cpu" command work with .gpu_selected flag and changed "make docker-restart-backend-fast" command to respect flag instead of always using gpu * Fix Ollama embedding error Added custom exception class for Ollama embeddings, which seemed to be returning keyword arguments while the Python exception class only accepts positional ones * Fixed model selection & memory error Fixed training defaulting to 0.5B model regardless of selection and fixed "free(): double free detected in tcache 2" error caused by cuda flag being passed incorrectly
* feature: use uv to setup python environment * TrainProcessService add singleten method: get_instance
* feature: use uv to setup python environment * TrainProcessService add singleten method: get_instance * feat: fix code * Added CUDA support (#228) * Add CUDA support - CUDA detection - Memory handling - Ollama model release after training * Fix logging issue added cuda support flag so log accurately reflected cuda toggle * Update llama.cpp rebuild Changed llama.cpp to only check if cuda support is enabled and if so rebuild during the first build rather than each run * Improved vram management Enabled memory pinning and optimizer state offload * Fix CUDA check rewrote llama.cpp rebuild logic, added manual y/n toggle if user wants to enable cuda support * Added fast restart and fixed CUDA check command Added make docker-restart-backend-fast to restart the backend and reflect code changes without causing a full llama.cpp rebuild Fixed make docker-check-cuda command to correctly reflect cuda support * Added docker-compose.gpu.yml Added docker-compose.gpu.yml to fix error on machines without nvidia gpu and made sure "\n" is added before .env modification * Fixed cuda toggle Last push accidentally broke cuda toggle * Code review fixes Fixed errors resulting from removed code: - Added return save_path to end of save_hf_model function - Rolled back download_file_with_progress function * Update Makefile Use cuda by default when using docker-restart-backend-fast * Minor cleanup Removed unnecessary makefile command and fixed gpu logging * Delete .gpu_selected * Simplified cuda training code - Removed dtype setting to let torch automatically handle it - Removed vram logging - Removed Unnecessary/old comments * Fixed gpu/cpu selection Made "make docker-use-gpu/cpu" command work with .gpu_selected flag and changed "make docker-restart-backend-fast" command to respect flag instead of always using gpu * Fix Ollama embedding error Added custom exception class for Ollama embeddings, which seemed to be returning keyword arguments while the Python exception class only accepts positional ones * Fixed model selection & memory error Fixed training defaulting to 0.5B model regardless of selection and fixed "free(): double free detected in tcache 2" error caused by cuda flag being passed incorrectly * fix: train service singlten --------- Co-authored-by: Zachary Pitroda <30330004+zpitroda@users.noreply.github.com>
* fix: adjustment status order * fix: adjustment train status * fix: split the status of service and train
* Update README.md Changed the updated tutorial link * Update README.md with FAQ New section for FAQ doc
* fix: adjustment status order * fix: adjustment train status * fix: split the status of service and train * feat: adjustment train rule
* feat: what? no llama.cpp * add cache
* fix: add relative
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# v1.0.0 - First Release 🎉
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# v1.0.0 - First Release 🎉
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Overview
We're excited to announce our first release! This version introduces multi-platform support, thinking mode capabilities, and CUDA integration.
Deployment Options 🚀
uvor other virtual environments to avoid package conflictsNew Features ✨
Thinking Mode (Beta)
CUDA Support 🎮
Special thanks to our community contributors!
Notes
This is our first stable release, and we welcome feedback from the community to help improve future versions.
Tags:
releasethinking-modecudamulti-platformdocker