diff --git a/agent/templates/user_interaction.json b/agent/templates/user_interaction.json
new file mode 100644
index 000000000..4a1451bed
--- /dev/null
+++ b/agent/templates/user_interaction.json
@@ -0,0 +1,519 @@
+{
+ "id": 27,
+ "title": {
+ "en": "Interacting with the Agent",
+ "zh": "用户与 Agent 交互"
+ },
+ "description": {
+ "en": "During the Agent’s execution, users can actively intervene and interact with the Agent to adjust or guide its output, ensuring the final result aligns with their intentions.",
+ "zh": "在 Agent 的运行过程中,用户可以随时介入,与 Agent 进行交互,以调整或引导生成结果,使最终输出更符合预期。"
+ },
+ "canvas_type": "Agent",
+ "dsl": {
+ "components": {
+ "Agent:LargeFliesMelt": {
+ "downstream": [
+ "UserFillUp:GoldBroomsRelate"
+ ],
+ "obj": {
+ "component_name": "Agent",
+ "params": {
+ "cite": true,
+ "delay_after_error": 1,
+ "description": "",
+ "exception_default_value": "",
+ "exception_goto": [],
+ "exception_method": "",
+ "frequencyPenaltyEnabled": false,
+ "frequency_penalty": 0.7,
+ "llm_id": "qwen-turbo@Tongyi-Qianwen",
+ "maxTokensEnabled": false,
+ "max_retries": 3,
+ "max_rounds": 1,
+ "max_tokens": 256,
+ "mcp": [],
+ "message_history_window_size": 12,
+ "outputs": {
+ "content": {
+ "type": "string",
+ "value": ""
+ },
+ "structured": {}
+ },
+ "presencePenaltyEnabled": false,
+ "presence_penalty": 0.4,
+ "prompts": [
+ {
+ "content": "User query:{sys.query}",
+ "role": "user"
+ }
+ ],
+ "sys_prompt": "\nYou are the Planning Agent in a multi-agent RAG workflow.\nYour sole job is to design a crisp, executable Search Plan for the next agent. Do not search or answer the user’s question.\n\n\nUnderstand the user’s task and decompose it into evidence-seeking steps.\nProduce high-quality queries and retrieval settings tailored to the task type (fact lookup, multi-hop reasoning, comparison, statistics, how-to, etc.).\nIdentify missing information that would materially change the plan (≤3 concise questions).\nOptimize for source trustworthiness, diversity, and recency; define stopping criteria to avoid over-searching.\nAnswer in 150 words.\n",
+ "temperature": 0.1,
+ "temperatureEnabled": false,
+ "tools": [],
+ "topPEnabled": false,
+ "top_p": 0.3,
+ "user_prompt": "",
+ "visual_files_var": ""
+ }
+ },
+ "upstream": [
+ "begin"
+ ]
+ },
+ "Agent:TangyWordsType": {
+ "downstream": [
+ "Message:FreshWallsStudy"
+ ],
+ "obj": {
+ "component_name": "Agent",
+ "params": {
+ "cite": true,
+ "delay_after_error": 1,
+ "description": "",
+ "exception_default_value": "",
+ "exception_goto": [],
+ "exception_method": "",
+ "frequencyPenaltyEnabled": false,
+ "frequency_penalty": 0.7,
+ "llm_id": "qwen-turbo@Tongyi-Qianwen",
+ "maxTokensEnabled": false,
+ "max_retries": 3,
+ "max_rounds": 1,
+ "max_tokens": 256,
+ "mcp": [],
+ "message_history_window_size": 12,
+ "outputs": {
+ "content": {
+ "type": "string",
+ "value": ""
+ },
+ "structured": {}
+ },
+ "presencePenaltyEnabled": false,
+ "presence_penalty": 0.4,
+ "prompts": [
+ {
+ "content": "Search Plan: {Agent:LargeFliesMelt@content}\n\n\n\nAwait Response feedback:{UserFillUp:GoldBroomsRelate@instructions}\n",
+ "role": "user"
+ }
+ ],
+ "sys_prompt": "\nYou are the Search Agent.\nYour job is to execute the approved Search Plan, integrate the Await Response feedback, retrieve evidence, and produce a well-grounded answer.\n\n\nTranslate the plan + feedback into concrete searches.\nCollect diverse, trustworthy, and recent evidence meeting the plan’s evidence bar.\nSynthesize a concise answer; include citations next to claims they support.\nIf evidence is insufficient or conflicting, clearly state limitations and propose next steps.\n\n \nRetrieval: You must use Retrieval to do the search.\n \n",
+ "temperature": 0.1,
+ "temperatureEnabled": false,
+ "tools": [
+ {
+ "component_name": "Retrieval",
+ "name": "Retrieval",
+ "params": {
+ "cross_languages": [],
+ "description": "",
+ "empty_response": "",
+ "kb_ids": [],
+ "keywords_similarity_weight": 0.7,
+ "outputs": {
+ "formalized_content": {
+ "type": "string",
+ "value": ""
+ },
+ "json": {
+ "type": "Array