Release/v0.2.3 (#355)
* feat(web): add PageEmpty component
* feat(web): add PageTabs component
* feat(web): add PageEmpty component
* feat(web): add PageTabs component
* feat(prompt): add history tracking for prompt releases
* feat(web): add prompt menu
* refactor: The PageScrollList component supports two generic parameters
* feat(web): BodyWrapper compoent update PageLoading
* feat(web): add Ontology menu
* feat(web): memory management add scene
* feat(tasks): add celery task configuration for periodic jobs
- Add ignore_result=True to prevent storing results for periodic tasks
- Set max_retries=0 to skip failed periodic tasks without retry attempts
- Configure acks_late=False for immediate acknowledgment in beat tasks
- Add time_limit and soft_time_limit to regenerate_memory_cache task (3600s/3300s)
- Add time_limit and soft_time_limit to workspace_reflection_task (300s/240s)
- Add time_limit and soft_time_limit to run_forgetting_cycle_task (7200s/7000s)
- Improve task reliability and resource management for scheduled jobs
* feat(sandbox): add Node.js code execution support to sandbox
* Release/v0.2.2 (#260)
* [modify] migration script
* [add] migration script
* fix(web): change form message
* fix(web): the memoryContent field is compatible with numbers and strings
* feat(web): code node hidden
* fix(model):
1. create a basic model to check if the name and provider are duplicated.
2. The result shows error models because the provider created API Keys for all matching models.
---------
Co-authored-by: Mark <zhuwenhui5566@163.com>
Co-authored-by: zhaoying <yzhao96@best-inc.com>
Co-authored-by: yingzhao <zhaoyingyz@126.com>
Co-authored-by: Timebomb2018 <18868801967@163.com>
* Feature/ontology class clean (#249)
* [add] Complete ontology engineering feature implementation
* [add] Add ontology feature integration and validation utilities
* [add] Add OWL validator and validation utilities
* [fix] Add missing render_ontology_extraction_prompt function
* [fix]Add dependencies, fix functionality
* [add] migration script
* feat(celery): add dedicated periodic tasks worker and queue (#261)
* fix(web): conflict resolve
* Fix/v022 bug (#263)
* [fix]Fix the issue of inconsistent language in explicit and episodic memory.
* [fix]Fix the issue of inconsistent language in explicit and episodic memory.
* [add]Add scene_id
* [fix]Based on the AI review to fix the code
* Fix/develop memory reflex (#265)
* 遗漏的历史映射
* 遗漏的历史映射
* 反思后台报错处理
* [add] migration script
* fix: chat conversation_id add node_start
* feat(web): show code node
* fix(web): Restructure the CustomSelect component, repair the interface that is called multiple times when the form is updated
* feat(web): RadioGroupCard support block mode
* feat(web): create space add icon
* feat(app and model): token consumption statistics
* Add/develop memory (#264)
* 遗漏的历史映射
* 遗漏的历史映射
* 遗漏的历史映射
* 遗漏的历史映射
* 遗漏的历史映射
* 遗漏的历史映射
* 遗漏的历史映射
* 遗漏的历史映射
* 遗漏的历史映射
* 新增长期记忆功能
* 新增长期记忆功能
* 新增长期记忆功能
* 知识库检索多余字段
* 长期
* feat(app and model): token consumption statistics of the cluster
* memory_BUG_fix
* fix(web): prompt history remove pageLoading
* fix(prompt): remove hard-coded import of prompt file paths (#279)
* Fix/develop memory bug (#274)
* 遗漏的历史映射
* 遗漏的历史映射
* fix_timeline_memories
* fix(web): update retrieve_type key
* Fix/develop memory bug (#276)
* 遗漏的历史映射
* 遗漏的历史映射
* fix_timeline_memories
* fix_timeline_memories
* write_gragp/bug_fix
* write_gragp/bug_fix
* write_gragp/bug_fix
* chore(celery): disable periodic task scheduling
* fix(prompt): remove hard-coded import of prompt file paths
---------
Co-authored-by: lixinyue11 <94037597+lixinyue11@users.noreply.github.com>
Co-authored-by: zhaoying <yzhao96@best-inc.com>
Co-authored-by: yingzhao <zhaoyingyz@126.com>
Co-authored-by: Ke Sun <kesun5@illinois.edu>
* fix(web): remove delete confirm content
* refactor(workflow): relocate template directory into workflow
* feat(memory): add long-term storage task routing and batching
* fix(web): PageScrollList loading update
* fix(web): PageScrollList loading update
* Ontology v1 bug (#291)
* [changes]Add 'id' as the secondary sorting key, and 'scene_id' now returns a UUID object
* [fix]Fix the "end_user" return to be sorted by update time.
* [fix]Set the default values of the memory configuration model based on the spatial model.
* [fix]Remove the entity extraction check combination model, read the configuration list, and add the return of scene_id
* [fix]Fix the "end_user" return to be sorted by update time.
* [fix]
* fix(memory): add Redis session validation
- Add macOS fork() safety configuration in celery_app.py to prevent initialization issues
- Add null/False checks for Redis session queries in term_memory_save to handle missing sessions gracefully
- Add null/False checks in memory_long_term_storage to prevent processing empty Redis results
- Add null/False checks in aggregate_judgment before format_parsing to avoid errors on missing data
- Initialize redis_messages variable in window_dialogue for consistency
- Add debug logging when no existing session found in Redis for better troubleshooting
- Add TODO comments for magic numbers (scope=6, time=5) to be extracted as constants
- Improve error handling when Redis returns False or empty results instead of crashing
* fix(web): PageScrollList style update
* fix(workflow): fix argument passing in code execution nodes
* fix(web): prompt add disabled
* fix(web): space icon required
* feat(app): modify the key of the token
* fix(fix the key of the app's token):
* fix(workflow): switch code input encoding to base64+URL encoding
* [add]The main project adds multi-API Key load balancing.
* [changes]Attribute security access, secure numerical conversion, unified use of local variables
* fix(web): save add session update
* fix(web): language editor support paste
* [changes]Active status filtering logic, API Key selection strategy
* memory_BUG
* memory_BUG_long_term
* [changes]
* memory_BUG_long_term
* memory_BUG_long_term
* Fix/release memory bug (#306)
* memory_BUG_fix
* memory_BUG
* memory_BUG_long_term
* memory_BUG_long_term
* memory_BUG_long_term
* knowledge_retrieval/bug/fix
* knowledge_retrieval/bug/fix
* knowledge_retrieval/bug/fix
* [fix]1.The "read_all_config" interface returns "scene_name";2.Memory configuration for lightweight query ontology scenarios
* fix(web): replace code editor
* [changes]Modify the description of the time for the recent event
* [changes]Modify the code based on the AI review
* feat(web): update memory config ontology api
* fix(web): ui update
* knowledge_retrieval/bug/fix
* knowledge_retrieval/bug/fix
* knowledge_retrieval/bug/fix
* feat(workflow): add token usage statistics for question classifier and parameter extraction
* feat(web): move prompt menu
* Multiple independent transactions - single transaction
* Multiple independent transactions - single transaction
* Multiple independent transactions - single transaction
* Multiple independent transactions - single transaction
* Write Missing None (#321)
* Write Missing None
* Write Missing None
* Write Missing None
* Apply suggestion from @sourcery-ai[bot]
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
* Write Missing None
---------
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
* Fix/release memory bug (#324)
* Write Missing None
* Write Missing None
* Write Missing None
* Apply suggestion from @sourcery-ai[bot]
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
* Write Missing None
* redis update
* redis update
* redis update
* redis update
---------
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
* Fix/writer memory bug (#326)
* [fix]Fix the bug
* [fix]Fix the bug
* [fix]Correct the direction indication.
* fix(web): markdown table ui update
* Fix/release memory bug (#332)
* Write Missing None
* Write Missing None
* Write Missing None
* Apply suggestion from @sourcery-ai[bot]
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
* Write Missing None
* redis update
* redis update
* redis update
* redis update
* writer_dup_bug/fix
---------
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
* Fix/fact summary (#333)
* [fix]Disable the contents related to fact_summary
* [fix]Disable the contents related to fact_summary
* [fix]Modify the code based on the AI review
* Fix/release memory bug (#335)
* Write Missing None
* Write Missing None
* Write Missing None
* Apply suggestion from @sourcery-ai[bot]
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
* Write Missing None
* redis update
* redis update
* redis update
* redis update
* writer_dup_bug/fix
* writer_graph_bug/fix
* writer_graph_bug/fix
---------
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
* Revert "feat(web): move prompt menu"
This reverts commit 9e6e8f50f8.
* fix(web): ui update
* fix(web): update text
* fix(web): ui update
* fix(model): change the "vl" model type of dashscope to "chat"
* fix(model): change the "vl" model type of dashscope to "chat"
---------
Co-authored-by: zhaoying <yzhao96@best-inc.com>
Co-authored-by: Eternity <1533512157@qq.com>
Co-authored-by: Mark <zhuwenhui5566@163.com>
Co-authored-by: yingzhao <zhaoyingyz@126.com>
Co-authored-by: Timebomb2018 <18868801967@163.com>
Co-authored-by: 乐力齐 <162269739+lanceyq@users.noreply.github.com>
Co-authored-by: lixinyue11 <94037597+lixinyue11@users.noreply.github.com>
Co-authored-by: lixinyue <2569494688@qq.com>
Co-authored-by: Eternity <61316157+myhMARS@users.noreply.github.com>
Co-authored-by: lanceyq <1982376970@qq.com>
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
This commit is contained in:
Ke Sun
@@ -1,219 +0,0 @@
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# 智能客服工作流模板
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id: customer_service_v1
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name: 智能客服工作流
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description: 智能客服场景，包含意图识别、知识库查询和回复生成
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category: customer_service
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version: "1.0.0"
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author: RedBear Memory Team
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tags:
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- 客服
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- 意图识别
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- 知识库
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- 多步骤
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# 工作流配置
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nodes:
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- id: start
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type: start
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name: 开始
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position:
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x: 100
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y: 200
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- id: intent_recognition
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type: llm
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name: 意图识别
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config:
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prompt: |
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分析用户的问题，识别意图类型。
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用户问题：{{ var.user_message }}
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请从以下类型中选择一个：
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- product_inquiry: 产品咨询
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- technical_support: 技术支持
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- complaint: 投诉建议
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- other: 其他
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只返回类型名称，不要其他内容。
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model: gpt-3.5-turbo
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temperature: 0.3
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max_tokens: 50
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position:
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x: 300
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y: 200
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- id: intent_router
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type: condition
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name: 意图路由
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position:
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x: 500
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y: 200
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- id: product_handler
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type: llm
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name: 产品咨询处理
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config:
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prompt: |
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用户咨询产品相关问题。
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问题：{{ var.user_message }}
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意图：{{ node.intent_recognition.output }}
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请提供专业、友好的产品咨询回复。
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model: gpt-3.5-turbo
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temperature: 0.7
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max_tokens: 500
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position:
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x: 700
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y: 100
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- id: support_handler
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type: llm
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name: 技术支持处理
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config:
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prompt: |
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用户需要技术支持。
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问题：{{ var.user_message }}
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意图：{{ node.intent_recognition.output }}
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请提供详细的技术支持方案。
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model: gpt-3.5-turbo
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temperature: 0.5
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max_tokens: 800
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position:
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x: 700
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y: 200
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- id: complaint_handler
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type: llm
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name: 投诉处理
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config:
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prompt: |
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用户提出投诉或建议。
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问题：{{ var.user_message }}
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意图：{{ node.intent_recognition.output }}
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请以同理心回应，并提供解决方案。
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model: gpt-3.5-turbo
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temperature: 0.8
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max_tokens: 600
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position:
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x: 700
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y: 300
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- id: general_handler
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type: llm
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name: 通用处理
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config:
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prompt: |
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用户的问题类型：其他
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问题：{{ var.user_message }}
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请提供友好的回复。
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model: gpt-3.5-turbo
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temperature: 0.7
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max_tokens: 400
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position:
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x: 700
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y: 400
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- id: end
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type: end
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name: 结束
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position:
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x: 900
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y: 200
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edges:
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- source: start
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target: intent_recognition
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label: 开始分析
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- source: intent_recognition
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target: intent_router
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label: 识别完成
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- source: intent_router
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target: product_handler
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condition: "'product_inquiry' in node['intent_recognition']['output']"
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label: 产品咨询
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- source: intent_router
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target: support_handler
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condition: "'technical_support' in node['intent_recognition']['output']"
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label: 技术支持
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- source: intent_router
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target: complaint_handler
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condition: "'complaint' in node['intent_recognition']['output']"
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label: 投诉建议
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- source: intent_router
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target: general_handler
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condition: "True" # 默认路径
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label: 其他
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- source: product_handler
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target: end
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label: 完成
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- source: support_handler
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target: end
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label: 完成
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- source: complaint_handler
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target: end
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label: 完成
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- source: general_handler
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target: end
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label: 完成
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# 变量定义
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variables:
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- name: user_message
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type: string
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required: true
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description: 用户的消息
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default: ""
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- name: user_name
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type: string
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required: false
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description: 用户姓名（可选）
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default: "客户"
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# 执行配置
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execution_config:
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max_execution_time: 120
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max_iterations: 10
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# 触发器
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triggers: []
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# 使用示例
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examples:
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- name: 产品咨询
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description: 用户咨询产品功能
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input:
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user_message: "你们的产品支持多语言吗？"
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user_name: "张三"
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expected_output: "产品功能介绍"
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- name: 技术支持
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description: 用户遇到技术问题
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input:
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user_message: "我无法登录系统，一直显示密码错误"
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user_name: "李四"
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expected_output: "技术支持方案"
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- name: 投诉处理
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description: 用户提出投诉
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input:
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user_message: "你们的服务态度太差了，我要投诉"
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user_name: "王五"
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expected_output: "同理心回应和解决方案"
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@@ -1,131 +0,0 @@
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# 数据处理工作流模板
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id: data_processing_v1
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name: 数据处理工作流
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description: 数据提取、转换和分析的完整流程
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category: data_processing
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version: "1.0.0"
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author: RedBear Memory Team
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tags:
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- 数据处理
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- ETL
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- 分析
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- Transform
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# 工作流配置
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nodes:
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- id: start
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type: start
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name: 开始
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position:
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x: 100
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y: 200
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- id: extract_data
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type: transform
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name: 数据提取
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config:
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expression: |
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{
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"raw_text": var['input_text'],
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"length": len(var['input_text']),
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"timestamp": sys['execution_id']
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}
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position:
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x: 300
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y: 200
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- id: analyze_data
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type: llm
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name: 数据分析
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config:
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prompt: |
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请分析以下数据：
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原始文本：{{ node.extract_data.raw_text }}
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文本长度：{{ node.extract_data.length }}
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请提供：
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1. 主题分类
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2. 情感分析
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3. 关键信息提取
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以 JSON 格式返回结果。
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model: gpt-3.5-turbo
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temperature: 0.3
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max_tokens: 500
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position:
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x: 500
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y: 200
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- id: transform_result
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type: transform
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name: 结果转换
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config:
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expression: |
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{
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"original_length": node['extract_data']['length'],
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"analysis": node['analyze_data']['output'],
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"processed_at": sys['execution_id'],
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"status": "completed"
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}
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position:
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x: 700
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y: 200
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- id: end
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type: end
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name: 结束
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position:
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x: 900
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y: 200
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edges:
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- source: start
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target: extract_data
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label: 开始提取
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- source: extract_data
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target: analyze_data
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label: 开始分析
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- source: analyze_data
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target: transform_result
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label: 转换结果
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- source: transform_result
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target: end
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label: 完成
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# 变量定义
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variables:
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- name: input_text
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type: string
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required: true
|
||||
description: 待处理的文本数据
|
||||
default: ""
|
||||
|
||||
# 执行配置
|
||||
execution_config:
|
||||
max_execution_time: 180
|
||||
max_iterations: 5
|
||||
|
||||
# 触发器
|
||||
triggers: []
|
||||
|
||||
# 使用示例
|
||||
examples:
|
||||
- name: 文本分析
|
||||
description: 分析一段文本
|
||||
input:
|
||||
input_text: "今天天气真好，心情也很愉快。我们公司推出了新产品，市场反响热烈。"
|
||||
expected_output:
|
||||
original_length: 35
|
||||
analysis: "主题：天气和产品，情感：积极"
|
||||
status: "completed"
|
||||
|
||||
- name: 长文本处理
|
||||
description: 处理较长的文本
|
||||
input:
|
||||
input_text: "这是一段很长的文本..."
|
||||
expected_output:
|
||||
status: "completed"
|
||||
@@ -1,99 +0,0 @@
|
||||
# 多步骤问答工作流
|
||||
# 演示节点输出参数的使用
|
||||
|
||||
id: multi_step_qa_v1
|
||||
name: 多步骤问答工作流
|
||||
description: 先分析问题，再生成答案，展示节点间的数据传递
|
||||
category: advanced
|
||||
version: "1.0.0"
|
||||
author: RedBear Memory Team
|
||||
tags:
|
||||
- 问答
|
||||
- 多步骤
|
||||
- LLM
|
||||
|
||||
# 工作流配置
|
||||
nodes:
|
||||
- id: start
|
||||
type: start
|
||||
name: 开始
|
||||
position:
|
||||
x: 100
|
||||
y: 100
|
||||
|
||||
- id: analyze_question
|
||||
type: llm
|
||||
name: 分析问题
|
||||
description: 分析用户问题的类型和意图
|
||||
config:
|
||||
model_id: gpt-3.5-turbo
|
||||
temperature: 0.3
|
||||
max_tokens: 500
|
||||
messages:
|
||||
- role: system
|
||||
content: |
|
||||
你是一个问题分析专家。请分析用户的问题，提取以下信息：
|
||||
1. 问题类型（事实性、观点性、操作性等）
|
||||
2. 问题领域（科技、历史、文化等）
|
||||
3. 关键词
|
||||
- role: user
|
||||
content: "{{ sys.message }}"
|
||||
position:
|
||||
x: 300
|
||||
y: 100
|
||||
|
||||
- id: generate_answer
|
||||
type: llm
|
||||
name: 生成答案
|
||||
description: 根据问题分析结果生成详细答案
|
||||
config:
|
||||
model_id: gpt-3.5-turbo
|
||||
temperature: 0.7
|
||||
max_tokens: 1000
|
||||
messages:
|
||||
- role: system
|
||||
content: |
|
||||
你是一个专业的AI助手。根据问题分析结果，生成准确、详细的答案。
|
||||
|
||||
问题分析结果：
|
||||
{{ analyze_question.output }}
|
||||
- role: user
|
||||
content: "{{ sys.message }}"
|
||||
position:
|
||||
x: 500
|
||||
y: 100
|
||||
|
||||
- id: end
|
||||
type: end
|
||||
name: 结束
|
||||
config:
|
||||
output: "{{ generate_answer.output }}"
|
||||
position:
|
||||
x: 700
|
||||
y: 100
|
||||
|
||||
edges:
|
||||
- source: start
|
||||
target: analyze_question
|
||||
label: 开始分析
|
||||
|
||||
- source: analyze_question
|
||||
target: generate_answer
|
||||
label: 生成答案
|
||||
|
||||
- source: generate_answer
|
||||
target: end
|
||||
label: 完成
|
||||
|
||||
# 变量定义
|
||||
variables:
|
||||
- name: user_question
|
||||
type: string
|
||||
required: true
|
||||
description: 用户的问题
|
||||
default: ""
|
||||
|
||||
# 执行配置
|
||||
execution_config:
|
||||
max_execution_time: 120
|
||||
max_iterations: 1
|
||||
@@ -1,93 +0,0 @@
|
||||
# 简单问答工作流模板
|
||||
id: simple_qa_v1
|
||||
name: 简单问答工作流
|
||||
description: 最基础的问答工作流，适合快速开始
|
||||
category: basic
|
||||
version: "1.0.0"
|
||||
author: RedBear Memory Team
|
||||
tags:
|
||||
- 问答
|
||||
- 基础
|
||||
- LLM
|
||||
|
||||
# 工作流配置
|
||||
nodes:
|
||||
- id: start
|
||||
type: start
|
||||
name: 开始
|
||||
position:
|
||||
x: 100
|
||||
y: 100
|
||||
|
||||
- id: llm_qa
|
||||
type: llm
|
||||
name: LLM 问答
|
||||
config:
|
||||
# 使用 LangChain 标准的消息格式
|
||||
messages:
|
||||
- role: system
|
||||
content: |
|
||||
你是一个专业、友好且乐于助人的 AI 助手。
|
||||
|
||||
你的职责：
|
||||
- 准确理解用户的问题并提供有价值的回答
|
||||
- 保持回答的专业性和准确性
|
||||
- 如果不确定答案，诚实地告知用户
|
||||
- 使用清晰、易懂的语言进行交流
|
||||
|
||||
回答风格：
|
||||
- 简洁明了，直击要点
|
||||
- 必要时提供详细解释和示例
|
||||
- 使用友好、礼貌的语气
|
||||
- 适当使用格式化（如列表、段落）提高可读性
|
||||
|
||||
|
||||
model_id: null
|
||||
temperature: 0.7
|
||||
max_tokens: 1000
|
||||
position:
|
||||
x: 500
|
||||
y: 100
|
||||
|
||||
- id: end
|
||||
type: end
|
||||
name: 结束
|
||||
config:
|
||||
output: "{{llm_qa.output}}"
|
||||
position:
|
||||
x: 900
|
||||
y: 100
|
||||
|
||||
edges:
|
||||
- source: start
|
||||
target: llm_qa
|
||||
label: 开始处理
|
||||
|
||||
- source: llm_qa
|
||||
target: end
|
||||
label: 完成
|
||||
|
||||
# 变量定义
|
||||
variables: []
|
||||
|
||||
# 执行配置
|
||||
execution_config:
|
||||
max_execution_time: 60
|
||||
max_iterations: 1
|
||||
|
||||
# 触发器（可选）
|
||||
triggers: []
|
||||
|
||||
# 使用示例
|
||||
examples:
|
||||
- name: 基础问答
|
||||
description: 询问一个简单的问题
|
||||
input:
|
||||
user_question: "什么是人工智能？"
|
||||
expected_output: "关于人工智能的解释"
|
||||
|
||||
- name: 技术咨询
|
||||
description: 询问技术问题
|
||||
input:
|
||||
user_question: "如何学习 Python 编程？"
|
||||
expected_output: "Python 学习建议"
|
||||
Reference in New Issue
Block a user