{ "messages": [ { "role": "system", "content": "" }, { "version": "v1", "chatId": "", "createdAt": "2025-05-08T07:06:48.280Z", "role": "assistant", "content": "How can I help you today?", "agenticSender": "Example Agent", "agenticResponseType": "external" }, { "role": "user", "content": "Tell me about article 1", "version": "v1", "chatId": "", "createdAt": "2025-05-08T07:06:53.518Z" }, { "version": "v1", "chatId": "", "createdAt": "2025-05-08T07:06:55.690Z", "role": "assistant", "tool_calls": [ { "id": "call_uzRd4Y1CeBioJ9h26XeGhCvH", "function": { "name": "rag_search", "arguments": "{\"query\":\"article 1\"}" }, "type": "function" } ], "agenticSender": "Example Agent", "agenticResponseType": "internal" }, { "version": "v1", "chatId": "", "createdAt": "2025-05-08T07:06:55.690Z", "role": "tool", "content": "{\n \"Information\": [\n {\n \"title\": \"text\",\n \"name\": \"text\",\n \"content\": \"This is article 1.\",\n \"docId\": \"681c50f17e7a18621c7215cd\",\n \"sourceId\": \"681c50f17e7a18621c7215cc\"\n },\n {\n \"title\": \"text\",\n \"name\": \"text\",\n \"content\": \"This is article 2.\",\n \"docId\": \"681c51067e7a18621c7215cf\",\n \"sourceId\": \"681c51067e7a18621c7215ce\"\n },\n {\n \"title\": \"text\",\n \"name\": \"text\",\n \"content\": \"This is article 3.\",\n \"docId\": \"681c51137e7a18621c7215d1\",\n \"sourceId\": \"681c51137e7a18621c7215d0\"\n }\n ]\n}", "tool_call_id": "call_uzRd4Y1CeBioJ9h26XeGhCvH", "tool_name": "" }, { "version": "v1", "chatId": "", "createdAt": "2025-05-08T07:06:57.096Z", "role": "assistant", "content": "Article 1 states: \"This is article 1.\"\n\nIf you need more details or information about another article, please let me know!", "agenticSender": "Example Agent", "agenticResponseType": "external" } ], "lastRequest": { "projectId": "8e59c4b6-91d2-42e9-8990-41583f4105f1", "messages": [ { "content": "", "role": "system", "sender": null, "tool_calls": null, "tool_call_id": null, "tool_name": null }, { "content": "How can I help you today?", "role": "assistant", "sender": "Example Agent", "tool_calls": null, "tool_call_id": null, "tool_name": null, "response_type": "external" }, { "content": "Tell me about article 1", "role": "user", "sender": null, "tool_calls": null, "tool_call_id": null, "tool_name": null } ], "state": { "last_agent_name": "Example Agent", "tokens": { "total": 0, "prompt": 0, "completion": 0 } }, "agents": [ { "name": "Example Agent", "type": "conversation", "description": "An example agent that uses the rag_search tool to fetch information for customer support queries.", "instructions": "## šŸ§‘ā€šŸ’¼ Role:\nYou are a helpful customer support assistant who fetches information using the rag_search tool.\n\n---\n## āš™ļø Steps to Follow:\n1. Ask the user what they would like help with.\n2. If the user's query requires information or an answer, use the [@tool:rag_search] tool with the user's question as the query.\n3. Provide the user with an answer based on the information retrieved from the tool.\n4. If the user's issue is about follow-up or requires human support, ask for their email address and let them know someone will contact them soon.\n5. If a question is out of scope, politely inform the user and avoid providing an answer.\n\n---\n## šŸŽÆ Scope:\nāœ… In Scope:\n- Answering customer support questions using information from articles.\n- Asking the user their issue and getting their email if needed.\n\nāŒ Out of Scope:\n- Questions unrelated to customer support.\n- Providing answers without using the rag_search tool when information is needed.\n\n---\n## šŸ“‹ Guidelines:\nāœ”ļø Dos:\n- Use [@tool:rag_search](#mention) to fetch accurate information for user queries.\n- Provide clear and concise answers based on the tool's results.\n- Ask for the user's email if the issue requires follow-up.\n\n🚫 Don'ts:\n- Do not provide answers without fetching information when required.\n- Do not ask for details other than the user's email.\n\n# Examples\n- **User** : What is your refund policy?\n - **Agent actions**: Call [@tool:rag_search](#mention)\n - **Agent response**: Our refund policy is as follows: \n\n- **User** : How can I change my password?\n - **Agent actions**: Call [@tool:rag_search](#mention)\n - **Agent response**: To change your password, follow these steps: \n\n- **User** : I need help with my order.\n - **Agent actions**: Call [@tool:rag_search](#mention)\n - **Agent response**: Can you please provide more details about your order issue? \n\n- **User** : I want someone to contact me about a billing issue.\n - **Agent response**: Sure, could you please provide your email address so someone from our team can contact you soon?\n\n- **User** : Can you tell me about your subscription plans?\n - **Agent actions**: Call [@tool:rag_search](#mention)\n - **Agent response**: Here are our subscription plans:
", "model": "gpt-4.1", "controlType": "retain", "ragDataSources": [ "681c50f17e7a18621c7215cc", "681c51067e7a18621c7215ce", "681c51137e7a18621c7215d0" ], "ragK": 1, "ragReturnType": "chunks", "tools": [ "rag_search" ], "prompts": [], "connectedAgents": [] } ], "tools": [ { "name": "web_search", "description": "Fetch information from the web based on chat context", "parameters": { "type": "object", "properties": {} }, "isLibrary": true }, { "name": "rag_search", "description": "Fetch articles with knowledge relevant to the query", "parameters": { "type": "object", "properties": { "query": { "type": "string", "description": "The query to retrieve articles for" } }, "required": [ "query" ] }, "isLibrary": true } ], "prompts": [], "startAgent": "Example Agent", "mcpServers": [], "toolWebhookUrl": "" }, "lastResponse": { "state": { "last_agent_name": "Example Agent", "tokens": { "total": 1581, "prompt": 1533, "completion": 48 } }, "messages": [ { "version": "v1", "chatId": "", "createdAt": "2025-05-08T07:06:55.690Z", "role": "assistant", "tool_calls": [ { "id": "call_uzRd4Y1CeBioJ9h26XeGhCvH", "function": { "name": "rag_search", "arguments": "{\"query\":\"article 1\"}" }, "type": "function" } ], "agenticSender": "Example Agent", "agenticResponseType": "internal" }, { "version": "v1", "chatId": "", "createdAt": "2025-05-08T07:06:55.690Z", "role": "tool", "content": "{\n \"Information\": [\n {\n \"title\": \"text\",\n \"name\": \"text\",\n \"content\": \"This is article 1.\",\n \"docId\": \"681c50f17e7a18621c7215cd\",\n \"sourceId\": \"681c50f17e7a18621c7215cc\"\n },\n {\n \"title\": \"text\",\n \"name\": \"text\",\n \"content\": \"This is article 2.\",\n \"docId\": \"681c51067e7a18621c7215cf\",\n \"sourceId\": \"681c51067e7a18621c7215ce\"\n },\n {\n \"title\": \"text\",\n \"name\": \"text\",\n \"content\": \"This is article 3.\",\n \"docId\": \"681c51137e7a18621c7215d1\",\n \"sourceId\": \"681c51137e7a18621c7215d0\"\n }\n ]\n}", "tool_call_id": "call_uzRd4Y1CeBioJ9h26XeGhCvH", "tool_name": "" }, { "version": "v1", "chatId": "", "createdAt": "2025-05-08T07:06:57.096Z", "role": "assistant", "content": "Article 1 states: \"This is article 1.\"\n\nIf you need more details or information about another article, please let me know!", "agenticSender": "Example Agent", "agenticResponseType": "external" } ] } }