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customer_service.json 46KB

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  1. {
  2. "id": 2,
  3. "title": "Multi-Agent Customer Support",
  4. "description": "This is a multi-agent system for intelligent customer service processing based on user intent classification. It uses the lead-agent to identify the type of user needs, assign tasks to sub-agents for processing.",
  5. "canvas_type": "Agent",
  6. "dsl": {
  7. "components": {
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  44. "sys_prompt": "# Role \n\nYou are **Customer Server Agent**. Classify every user message; handle **contact** yourself. This is a multi-agent system.\n\n## Categories \n\n1. **contact** \u2013 user gives phone, e\u2011mail, WeChat, Line, Discord, etc. \n\n2. **casual** \u2013 small talk, not about the product. \n\n3. **complain** \u2013 complaints or profanity about the product/service. \n\n4. **product** \u2013 questions on product use, appearance, function, or errors.\n\n## If contact \n\nReply with one random item below\u2014do not change wording or call sub\u2011agents: \n\n1. Okay, I've already written this down. What else can I do for you? \n\n2. Got it. What else can I do for you? \n\n3. Thanks for your trust! Our expert will contact you ASAP. Anything else I can help with? \n\n4. Thanks! Anything else I can do for you?\n\n\n---\n\n\n## Otherwise (casual\u202f/\u202fcomplain\u202f/\u202fproduct) \n\nLet Sub\u2011Agent returns its answer\n\n## Sub\u2011Agent \n\n- casual \u2192 **Casual Agent** \nThis is an agent for handles casual conversationk.\n\n- complain \u2192 **Soothe Agent** \nThis is an agent for handles complaints or emotional input.\n\n- product \u2192 **Product Agent** \nThis is an agent for handles product-related queries and can use the `Retrieval` tool.\n\n## Importance\n\n- When the Sub\u2011Agent returns its answer, forward that answer to the user verbatim \u2014 do not add, edit, or reason further.\n ",
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  122. "prompts": [
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  124. "content": "{sys.query}",
  125. "role": "user"
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  140. "id": "Agent:SillyTurkeysRest",
  141. "name": "Product Agent",
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  144. "description": "This is an agent for handles product-related queries and can use the `Retrieval` tool.",
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  166. "prompts": [
  167. {
  168. "content": "{sys.query}",
  169. "role": "user"
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  171. ],
  172. "sys_prompt": "# Role \n\nYou are a Product Information Advisor with access to the **Retrieval** tool.\n\n# Workflow \n\n1. Run **Retrieval** with a focused query from the user\u2019s question. \n\n2. Draft the reply **strictly** from the returned passages. \n\n3. If nothing relevant is retrieved, reply: \n\n \u201cI cannot find relevant documents in the knowledge base.\u201d\n\n# Rules \n\n- No assumptions, guesses, or extra\u2011KB knowledge. \n\n- Factual, concise. Use bullets / numbers when helpful. \n\n",
  173. "temperature": 0.1,
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  181. "description": "This is a product knowledge base",
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  183. "kb_ids": [],
  184. "keywords_similarity_weight": 0.7,
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  200. "top_p": 0.3,
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  207. "top_p": 0.3,
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  369. "content": "The user query is {sys.query}",
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  373. "sys_prompt": "# Role \n\nYou are **Customer Server Agent**. Classify every user message; handle **contact** yourself. This is a multi-agent system.\n\n## Categories \n\n1. **contact** \u2013 user gives phone, e\u2011mail, WeChat, Line, Discord, etc. \n\n2. **casual** \u2013 small talk, not about the product. \n\n3. **complain** \u2013 complaints or profanity about the product/service. \n\n4. **product** \u2013 questions on product use, appearance, function, or errors.\n\n## If contact \n\nReply with one random item below\u2014do not change wording or call sub\u2011agents: \n\n1. Okay, I've already written this down. What else can I do for you? \n\n2. Got it. What else can I do for you? \n\n3. Thanks for your trust! Our expert will contact you ASAP. Anything else I can help with? \n\n4. Thanks! Anything else I can do for you?\n\n\n---\n\n\n## Otherwise (casual\u202f/\u202fcomplain\u202f/\u202fproduct) \n\nLet Sub\u2011Agent returns its answer\n\n## Sub\u2011Agent \n\n- casual \u2192 **Casual Agent** \nThis is an agent for handles casual conversationk.\n\n- complain \u2192 **Soothe Agent** \nThis is an agent for handles complaints or emotional input.\n\n- product \u2192 **Product Agent** \nThis is an agent for handles product-related queries and can use the `Retrieval` tool.\n\n## Importance\n\n- When the Sub\u2011Agent returns its answer, forward that answer to the user verbatim \u2014 do not add, edit, or reason further.\n ",
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  524. "description": "This is an agent for handles product-related queries and can use the `Retrieval` tool.",
  525. "exception_comment": "",
  526. "exception_default_value": "",
  527. "exception_goto": [],
  528. "exception_method": null,
  529. "frequencyPenaltyEnabled": false,
  530. "frequency_penalty": 0.7,
  531. "llm_id": "deepseek-chat@DeepSeek",
  532. "maxTokensEnabled": false,
  533. "max_retries": 3,
  534. "max_rounds": 2,
  535. "max_tokens": 256,
  536. "mcp": [],
  537. "message_history_window_size": 12,
  538. "outputs": {
  539. "content": {
  540. "type": "string",
  541. "value": ""
  542. }
  543. },
  544. "presencePenaltyEnabled": false,
  545. "presence_penalty": 0.4,
  546. "prompts": [
  547. {
  548. "content": "{sys.query}",
  549. "role": "user"
  550. }
  551. ],
  552. "sys_prompt": "# Role \n\nYou are a Product Information Advisor with access to the **Retrieval** tool.\n\n# Workflow \n\n1. Run **Retrieval** with a focused query from the user\u2019s question. \n\n2. Draft the reply **strictly** from the returned passages. \n\n3. If nothing relevant is retrieved, reply: \n\n \u201cI cannot find relevant documents in the knowledge base.\u201d\n\n# Rules \n\n- No assumptions, guesses, or extra\u2011KB knowledge. \n\n- Factual, concise. Use bullets / numbers when helpful. \n\n",
  553. "temperature": 0.1,
  554. "temperatureEnabled": true,
  555. "tools": [
  556. {
  557. "component_name": "Retrieval",
  558. "name": "Retrieval",
  559. "params": {
  560. "cross_languages": [],
  561. "description": "This is a product knowledge base",
  562. "empty_response": "",
  563. "kb_ids": [],
  564. "keywords_similarity_weight": 0.7,
  565. "outputs": {
  566. "formalized_content": {
  567. "type": "string",
  568. "value": ""
  569. }
  570. },
  571. "rerank_id": "",
  572. "similarity_threshold": 0.2,
  573. "top_k": 1024,
  574. "top_n": 8,
  575. "use_kg": false
  576. }
  577. }
  578. ],
  579. "topPEnabled": false,
  580. "top_p": 0.3,
  581. "user_prompt": "This is the order you need to send to the agent.",
  582. "visual_files_var": ""
  583. },
  584. "label": "Agent",
  585. "name": "Product Agent"
  586. },
  587. "dragging": false,
  588. "id": "Agent:SillyTurkeysRest",
  589. "measured": {
  590. "height": 84,
  591. "width": 200
  592. },
  593. "position": {
  594. "x": 684.0042670887832,
  595. "y": 317.79626670112515
  596. },
  597. "selected": false,
  598. "sourcePosition": "right",
  599. "targetPosition": "left",
  600. "type": "agentNode"
  601. },
  602. {
  603. "data": {
  604. "form": {
  605. "description": "This is an agent for a specific task.",
  606. "user_prompt": "This is the order you need to send to the agent."
  607. },
  608. "label": "Tool",
  609. "name": "flow.tool_0"
  610. },
  611. "dragging": false,
  612. "id": "Tool:CrazyShirtsKiss",
  613. "measured": {
  614. "height": 48,
  615. "width": 200
  616. },
  617. "position": {
  618. "x": 659.7339736658578,
  619. "y": 443.3638400568565
  620. },
  621. "selected": false,
  622. "sourcePosition": "right",
  623. "targetPosition": "left",
  624. "type": "toolNode"
  625. },
  626. {
  627. "data": {
  628. "form": {
  629. "content": [
  630. "{Agent:RottenRiversDo@content}"
  631. ]
  632. },
  633. "label": "Message",
  634. "name": "Response"
  635. },
  636. "dragging": false,
  637. "id": "Message:PurpleCitiesSee",
  638. "measured": {
  639. "height": 56,
  640. "width": 200
  641. },
  642. "position": {
  643. "x": 675.534293293706,
  644. "y": 158.92309339708154
  645. },
  646. "selected": false,
  647. "sourcePosition": "right",
  648. "targetPosition": "left",
  649. "type": "messageNode"
  650. },
  651. {
  652. "data": {
  653. "form": {
  654. "text": "This is a multi-agent system for intelligent customer service processing based on user intent classification. It uses the lead-agent to identify the type of user needs, assign tasks to sub-agents for processing, and finally the lead agent outputs the results."
  655. },
  656. "label": "Note",
  657. "name": "Workflow Overall Description"
  658. },
  659. "dragHandle": ".note-drag-handle",
  660. "dragging": false,
  661. "height": 140,
  662. "id": "Note:MoodyTurtlesCount",
  663. "measured": {
  664. "height": 140,
  665. "width": 385
  666. },
  667. "position": {
  668. "x": -59.311679338397,
  669. "y": -2.2203733298874866
  670. },
  671. "resizing": false,
  672. "selected": false,
  673. "sourcePosition": "right",
  674. "targetPosition": "left",
  675. "type": "noteNode",
  676. "width": 385
  677. },
  678. {
  679. "data": {
  680. "form": {
  681. "text": "Answers will be given strictly according to the content retrieved from the knowledge base."
  682. },
  683. "label": "Note",
  684. "name": "Product Agent "
  685. },
  686. "dragHandle": ".note-drag-handle",
  687. "dragging": false,
  688. "id": "Note:ColdCoinsBathe",
  689. "measured": {
  690. "height": 136,
  691. "width": 249
  692. },
  693. "position": {
  694. "x": 994.4238924667025,
  695. "y": 329.08949370720796
  696. },
  697. "selected": false,
  698. "sourcePosition": "right",
  699. "targetPosition": "left",
  700. "type": "noteNode"
  701. }
  702. ]
  703. },
  704. "history": [],
  705. "messages": [],
  706. "path": [],
  707. "retrieval": []
  708. },
  709. 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"
  710. }