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2 commits

Author SHA1 Message Date
doubleBlack2
f3e4d289e6
Feature/cloud service (#383)
* Enhance GGUF model handling with timestamps, metadata and memory training status

* Check if is_trained exists

* fix

* cloud service

* Change the data type of the is_trained field to boolean and update the related logic to reflect this change

* Change the data type of the is_trained field to boolean and update the related logic to reflect this change

* Add gguf path to json file

* Added model selection function, updated model list acquisition logic, and enhanced model information display

* Update the model service startup logic, add integrity check for the model path, and support obtaining the model path from different fields

* Service Change

* full cloud service

* feat: implement async cloud training process with job tracking and API key management

* Progress bar modification

* feat: Add Local and Cloud Training Configuration Components

- Introduced LocalTrainingConfig component for configuring local training parameters.
- Updated TrainingConfiguration component to include tabs for Local and Cloud training configurations.
- Added API functions for setting and getting cloud service API keys.
- Created useCloudProviderStore for managing cloud provider configurations.
- Enhanced event utility to include a new event for showing cloud provider modal.

* Refactor cloud provider and training configuration components

- Updated CloudProviderModal to handle cloud service API key management.
- Replaced API key handling with model configuration updates in CloudProviderModal.
- Enhanced CloudTrainingConfig to manage cloud models based on API key availability.
- Introduced new cloud service functions for listing available models and managing training jobs.
- Modified LocalTrainingConfig to ensure default model selection and synchronization.
- Updated TrainingConfiguration to manage model switching between local and cloud environments.
- Refactored useCloudProviderStore to integrate cloud service API key handling.
- Adjusted useTrainingStore to prioritize model name selection based on the active environment.

* Stream Output

* feat: Enhance training configuration and progress components

- Updated LocalTrainingConfig to improve default model handling and avoid unnecessary updates.
- Introduced LocalTrainingProgress component to manage local training progress display.
- Refactored TrainingConfiguration to support both local and cloud training types, including updated button text and actions.
- Modified TrainingProgress to conditionally render local or cloud training progress based on the selected training type.
- Added cloud service functions for starting training and managing job information.
- Adjusted training parameter interfaces to ensure consistency across local and cloud models.

* Stream response change

* feat: Enhance cloud training and inference capabilities

- Updated TrainingProgress component to handle cloud training progress data and job ID.
- Modified trainExposureModel to allow nullable path and added optional stageName.
- Enhanced useSSE hook to support cloud model inference with new parameters.
- Introduced CloudProgressData type to align cloud training progress with local training structure.
- Implemented cloud inference request handling with local knowledge retrieval in cloudService.
- Added utility functions for managing active cloud model state in cloudModelUtils.
- Updated cloud inference endpoint to support local knowledge retrieval before cloud inference.
- Refactored advanced chat service to utilize new message structure for cloud inference.
- Enhanced prompt strategies to incorporate knowledge retrieval based on user messages.

* feat: Delete the training parameter debugging information component

* Resume training at breakpoint

* Repair data redundancy

* Stop system modification

* fix error: reset training

* fix stop and reset

* Change chat reply format

* Enhance cloud and local service management with status tracking and improved progress reporting

- Implemented service status file management in cloud and local services to track active status and model information.
- Added endpoints to start and stop cloud services, including validation for existing services.
- Enhanced local service management with status checks and progress updates during document processing and chunk embedding.
- Introduced real-time progress tracking for document embedding and chunk processing, allowing for incremental updates.
- Improved error handling and logging throughout the service management processes.
- Refactored chat request handling to intelligently route between local and cloud services based on current status.

* feat:Cleaned up code comment

* translate Chinese comments to English in cloud service modules

* translate into chinese

* feat: Enhance cloud provider configuration and training management with API key handling and tab switching logic

* bug fix

* Add is_trained field modification in the cloud

* feat: Refactor training parameters management to separate local and cloud configurations

* feat: Update training parameter types to improve type safety and consistency

* feat: Add data synthesis mode to cloud training parameters and update related components

* feat: The document embedding part is restored to its original state

* refactor: optimize cloud training process with improved stop handling and file path updates

* feat: Update the default values and merging logic of cloud training parameters to ensure parameter consistency

* feat: Add API key preloading function to optimize the loading experience when the modal box is opened

* feat: Optimize CloudProviderModal component, add API key preloading and state management

* fix: Simplify cloud provider display by removing conditional rendering for Alibaba Cloud

* feat: Update .gitignore to include job_id.json and add .gitkeep for gguf directory

---------

Co-authored-by: wyx-hhhh <1360479992@qq.com>
2025-06-04 19:52:14 +08:00
ryangyuan
9fe511f0f2
Feature/0416/add thinking mode (#264)
* 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>
2025-04-24 14:19:23 +08:00