* release/v0.2.6:
fix(web): ontology class default tag bugfix
fix(version): Version 0.2.6 Release Notes
fix(web): chat file delete bugfix
feat: support model load balancing and add message_id to API responses
feat: support model load balancing and add message_id to API responses
[changes] Work space isolation
[add] Recently, memory activities have adopted Redis caching.
[changes] Work space isolation
[add] Recently, memory activities have adopted Redis caching.
fix(web): upload add loading
[changes] The enumeration check has been changed to a string.
[changes] The enumeration check has been changed to a string.
feat(web): http-request add headers variable
fix(workflow): ensure file messages are written to messages in non-stream mode
fix(workflow): fix Dify compatibility issues
[changes] Memory write completion active failure interest cache
feat(workflow): support multimodal context
[changes] AI review and correction of code
[add] Semantic pruning is unified with the ontology engineering scenario.
feat(chat): add message_id field to chat API response
1. From the model square to the model list, the added models are initially set to be inactive. When manually activating them, a mandatory API key configuration is required.
2. Copying of applications (agent, workflow, multi_agent)
1. Increase support for visual models and multimodal models;
2. The application and workflow can input various multimodal files such as images, documents, audio, and videos.
* [fix]The log retains genuine alerts and errors, while filtering out unnecessary noise.
* [fix]Scenario English and Chinese, emotion specifications
* [fix]Change the "no data" scenario from 0.0 to None
1. when adding a model API key to the model list, a tenant_id uniqueness check needs to be added;
2.the Model Square has cancelled custom models;
3. optimization of the interface logic for customizing model configurations in the model list
* [add]Integration of the core engineering and memory extraction
* [add]The import and export function of the main body engineering files
* [add]Improve the import interface
* [add]Introducing generic types helps with entity extraction
* [add]Modify the references of the main repository to the sub-repositories
* [add]The extraction trial run introduces the ontology type.
* [add]Integration of the core engineering and memory extraction
* [add]The import and export function of the main body engineering files
* [add]Improve the import interface
* [add]Introducing generic types helps with entity extraction
* [add]Modify the references of the main repository to the sub-repositories
* [add]The extraction trial run introduces the ontology type.
* [add]Complete the second phase of the main project content
* [add]The dependencies and configurations of the main body project
* [add]Modify the code based on the AI review
1. Three party web website data access - Web site synchronization
Building a knowledge base by crawling web page data in batches through web crawlers
Web site synchronization utilizes crawler technology, which can automatically capture all websites under the same domain name through a single entry website. Currently, it supports up to 200 subpages. For compliance and security reasons, only static site crawling is supported, mainly used for quickly building knowledge bases on various document sites.
2. Feishu Knowledge Base
By configuring Feishu document permissions, a knowledge base can be built using Feishu documents, and the documents will not undergo secondary storage
3. Language Bird Knowledge Base
You can configure the permissions of the language bird document to build a knowledge base using the language bird document, and the document will not undergo secondary storage
1. Add the "Skills" module;
2. The loading of the model square has been modified to be controlled through environment variables;
3. Dynamic scheduling of the skill binding tool;
4. Agent Integration Skills
