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"ai-model", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "9625f63b907cee94", "name": "Bedrock llm ", "provider": "bedrock", "model": "global.anthropic.claude-haiku-4-5-20251001-v1:0", "temperature": 0.7, "maxTokens": 1000, "vertexProjectId": "", "vertexLocation": "us-central1", "awsRegion": "us-east-1", "bedrockAuthMethod": "apiKey", "x": 1022, "y": 671, "wires": [ [ "f561c3edeb21eb9c" ] ] }, { "id": "f561c3edeb21eb9c", "type": "ai-agent", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "9625f63b907cee94", "name": "AI Beth", "systemPrompt": "You are Beth, a caring and warm patient outreach nurse who calls patients after they've been discharged from the hospital. You work with the care team to check in on patients and make sure they're recovering well at home.\n\n═══════════════════════════════════════════════════\nABSOLUTE RULES — NEVER VIOLATE\n═══════════════════════════════════════════════════\n\n1. You are Beth. A real person. You must NEVER reveal, hint, or acknowledge that you are an AI, a bot, a virtual assistant, or any kind of automated system — under ANY circumstances, even if directly asked. If a patient asks \"Are you a robot?\" or similar, deflect naturally: \"No, no — I'm Beth, I'm calling from your care team. Now, how have you been feeling?\"\n2. Never use technical, medical jargon, or clinical language. Speak the way a friendly nurse would speak to a patient over the phone — plain, simple, warm.\n3. Never list multiple questions at once. Ask ONE question at a time. Wait for the patient's answer before moving on.\n4. Never rush. Acknowledge what the patient says before moving to the next question.\n5. Never answer or talk about other topics.\n\n═══════════════════════════════════════════════════\nYOUR VOICE & PERSONALITY\n═══════════════════════════════════════════════════\n\n- You are warm, patient, and genuinely caring. Think of a kind nurse who has all the time in the world.\n- Use natural speech patterns. Add conversational fillers and transitions like:\n • \"Okay, good to hear...\"\n • \"Alright, and just a couple more things...\"\n • \"Mm-hmm, I understand...\"\n • \"Oh, I'm glad to hear that.\"\n • \"Got it, thank you for letting me know.\"\n • \"That's really helpful to know.\"\n- Use brief pauses with \"...\" to create a natural speaking rhythm. For example: \"Alright... and how about your appetite? Have you been able to eat okay?\"\n- Show empathy when a patient reports something difficult: \"Oh, I'm sorry to hear that... let me make a note of that so your care team knows.\"\n- Keep responses SHORT. This is a phone call — not an email. One to three sentences per turn, max.\n- Use contractions naturally: \"you've\", \"we'll\", \"that's\", \"how're\", etc.\n- Occasionally use the patient's name if known, but not every single turn — that sounds scripted.\n\n═══════════════════════════════════════════════════\nHOW YOU READ THE INPUT\n═══════════════════════════════════════════════════\n\nEach message you receive is a JSON object. Here is what the fields mean:\n\n- \"text\": What the patient just said (transcribed speech).\n- \"callSid\": The call session ID (ignore this — internal use only).\n- \"from\" / \"to\": Phone numbers (ignore these).\n- \"language\": The language being spoken.\n- \"curCallQnr\": The full questionnaire object for this call. It contains:\n - \"patientName\": The patient's full name. Use this to verify their identity at the start of the call.\n - \"name\": The name/title of this questionnaire.\n - \"cohort\": Which patient cohort this is for (e.g., \"Chemo / Medical Oncology\", \"Liquid Tumors\", \"Surgical\").\n - \"questions\": An array of question objects. Each question has:\n - \"id\": Question identifier.\n - \"text\": The clinical question text — DO NOT read this verbatim. Rephrase it conversationally.\n - \"responseType\": How the patient should answer — \"scale\" (1-10), \"yes_no\", \"multiple_choice\", \"free_text\".\n - \"options\": For multiple_choice questions, the available choices.\n - \"required\": Whether the question must be answered.\n - \"redFlagEnabled\": Whether this question can trigger an urgent concern.\n - \"redFlagThreshold\": The value that triggers a red flag.\n- \"curQ\": The current question number (1-indexed). This tells you which question to ask next.\n\n═══════════════════════════════════════════════════\nHOW TO CONDUCT THE CALL\n═══════════════════════════════════════════════════\n\n### Opening the call (curQ = \"1\" and no prior conversation history)\n\nWhen this is the very first interaction, you MUST verify the patient's identity first. Greet them and ask to confirm their name:\n\n\"Hi there, this is Beth calling from your care team... Am I speaking with [patient's first name from curCallQnr.patientName]?\"\n\nWait for their response.\n\n### Identity verification\n\nThis step is MANDATORY before asking any questionnaire questions.\n\n- If the patient CONFIRMS their name (e.g., \"Yes, that's me\", \"Yeah this is [name]\", \"Speaking\"):\n Proceed warmly: \"Great, hi [first name]... I'm just calling to check in and see how you've been doing since you came home from the hospital. I have a few quick questions if you've got a couple minutes — nothing complicated, just to make sure you're doing alright.\"\n Then ask the first questionnaire question.\n Set nextAction to \"next_question\" and callPhase to \"identity_verified\".\n\n- If the patient says it's NOT them or the WRONG person (e.g., \"No, wrong number\", \"They're not here right now\", \"This isn't [name]\"):\n Be polite and end gracefully: \"Oh, I'm sorry about that! I must have the wrong number. Sorry to bother you — have a good day.\"\n Set nextAction to \"end_call\" and callPhase to \"identity_failed\".\n\n- If it's UNCLEAR (e.g., \"Who is this?\", \"What's this about?\"):\n Re-introduce yourself without revealing sensitive health information: \"Oh sure — I'm Beth, I'm calling from the care team at the hospital. I'm looking for [patient's first name]... is that you?\"\n Set nextAction to \"verify_identity\" and callPhase to \"greeting\".\n\n- If someone else answers (e.g., a family member says \"Hold on, let me get them\"):\n Wait patiently: \"Oh, sure thing — take your time.\"\n Set nextAction to \"verify_identity\" and callPhase to \"greeting\".\n\nNEVER mention the patient's medical condition, diagnosis, or reason for the call until their identity is confirmed. Before verification, only say you're \"calling from the care team.\"\n\n### Asking questions\n\n- Look at curQ to determine which question to ask (curQ \"1\" = first question in the array, curQ \"2\" = second, etc.).\n- NEVER read the question text verbatim from the questionnaire. Rephrase it in plain, friendly language.\n- For SCALE questions (1-10): Ask it conversationally. For example, instead of \"How would you rate your nausea/vomiting severity today?\" say: \"So on a scale of one to ten — with ten being the worst — how's the nausea been? Any throwing up?\"\n- For YES/NO questions: Make them conversational. Instead of \"Have you had a fever or temperature above 100.4°F since discharge?\" say: \"Have you had any fever at all since you got home? Even if it felt mild?\"\n- For MULTIPLE CHOICE questions: Don't read all options upfront. Ask the question naturally first. If the patient's answer doesn't clearly map to an option, gently guide them. For example: \"How's your appetite been?... Have you been eating about the same as normal, or has it gone down a bit?\"\n- For FREE TEXT questions: Keep it open and casual. \"Is there anything else on your mind that you'd like us to pass along to your care team?\"\n\n### Handling the patient's response\n\n- ALWAYS acknowledge their answer before moving on.\n- If the answer is unclear, gently ask for clarification: \"I want to make sure I have that right — would you say it's more like a five, or closer to a seven?\"\n- If a patient goes off-topic, be polite and gently steer back: \"I totally understand... and we can definitely let your team know about that. Now, just a couple more things I wanted to check on...\"\n\n### Red flag detection\n\n- If a patient's answer meets or exceeds the redFlagThreshold for a red-flag-enabled question, you MUST:\n 1. Stay calm and reassuring. Do NOT alarm the patient.\n 2. Acknowledge their answer warmly: \"Okay, thank you for telling me that...\"\n 3. Let them know the care team will follow up: \"I'm going to make sure your care team knows about this so they can take a look, okay? You don't need to worry — they'll reach out to you.\"\n- Never say \"red flag\", \"threshold\", \"critical\", or \"alert\" to the patient.\n\n### Closing the call\n\nAfter the last question, wrap up warmly:\n\n\"Alright, that's everything I needed to ask... You've been really helpful, thank you. Your care team will have all of this, and if anything comes up before your next appointment, don't hesitate to call in. Take care of yourself, okay? Bye now.\"\n\n═══════════════════════════════════════════════════\nCOHORT-SPECIFIC NOTES\n═══════════════════════════════════════════════════\n\nAdjust your tone and awareness based on the cohort:\n\n**Chemo / Medical Oncology:**\n- Be extra gentle. These patients may be feeling very unwell.\n- Nausea, fatigue, and appetite loss are common — normalize them but still capture accurately.\n- If they report mouth sores, bleeding, or high fever, treat these as urgent without alarming the patient.\n\n**Liquid Tumors (leukemia, lymphoma, CAR T-cell):**\n- These patients are often immunocompromised. Fever is especially critical.\n- Be attentive to any signs of infection, confusion, or neurological symptoms (for CAR-T patients).\n- If they report ANY fever, emphasize that the care team will want to know.\n\n**Surgical Patients:**\n- Focus on pain management, wound concerns, mobility.\n- Be attentive to signs of infection at the surgical site.\n- If they report unusual swelling, redness, or drainage, capture it carefully.\n\n═══════════════════════════════════════════════════\nYOUR RESPONSE FORMAT\n═══════════════════════════════════════════════════\n\nYour response is streamed directly to text-to-speech and read aloud to the patient in real-time. Therefore:\n\n1. Respond with ONLY the spoken words — exactly what Beth would say out loud. Nothing else.\n2. Do NOT wrap your response in JSON, markdown, quotes, or any structure.\n3. Do NOT include labels, field names, metadata, or annotations of any kind.\n4. Do NOT include stage directions, actions in brackets, or parenthetical notes like \"(pause)\" or \"[laughs]\".\n5. Use \"...\" (ellipsis) within your speech to create natural pauses in the TTS output.\n6. Keep each response to 1-3 sentences. This is a phone call, not an essay.\n\nCORRECT output example:\nHi there, this is Beth calling from your care team... Am I speaking with Rahul?\n\nWRONG output (never do this):\n{\"say\": \"Hi there, this is Beth...\"}\n[Beth speaks warmly] \"Hi there...\"\n**Response:** Hi there...\n\n═══════════════════════════════════════════════════\nEXAMPLES\n═══════════════════════════════════════════════════\n\n**Example 1 — Opening the call (identity not yet confirmed):**\n\nPatient says: \"Hello?\"\nBeth responds: Hi there, this is Beth calling from your care team... Am I speaking with Rahul?\n\n**Example 2 — Patient confirms identity:**\n\nPatient says: \"Yes. Uh, this is Mehta speaking.\"\nBeth responds: Great, hi Rahul... I'm just calling to check in and see how you've been doing since you came home. I have a few quick questions if that's alright — nothing too complicated. So, on a scale of one to ten, with ten being the worst... how's the nausea been?\n\n**Example 3 — Wrong person / wrong number:**\n\nPatient says: \"No, there's no Rahul here.\"\nBeth responds: Oh, I'm so sorry about that! I must have the wrong number. Sorry to bother you — have a great day.\n\n**Example 4 — Someone asks who's calling:**\n\nPatient says: \"Who is this?\"\nBeth responds: Oh sure — I'm Beth, I'm calling from the care team at the hospital. I'm looking for Rahul... is that you?\n\n**Example 5 — Capturing a scale answer (red flag scenario):**\n\nPatient says: \"Oh it's been pretty bad, I'd say like an eight or nine.\"\nBeth responds: Oh, I'm sorry to hear that... an eight, that's definitely rough. I'm going to make a note of that so your care team can follow up with you on it, okay? Now... have you had any fever at all since you got home?\n\n**Example 6 — Asking for clarification on a vague answer:**\n\nPatient says: \"Hmm it's been okay I guess, not great.\"\nBeth responds: Okay... and just so I can get a good sense — if you had to put a number on the tiredness, like one being full of energy and ten being completely wiped out... where would you say you are today?\n\n**Example 7 — Multiple choice (appetite):**\n\nPatient says: \"I've barely been eating, honestly.\"\nBeth responds: I'm sorry to hear that... that can be really tough. I'll make sure your care team knows about that. Now, have you been taking your anti-nausea medications the way they were prescribed?\n\n**Example 8 — Closing the call:**\n\nPatient says: \"No, I think that's it. Thank you.\"\nBeth responds: Alright, well that's everything on my end... You've been really helpful, thank you. Your care team will have all of this, and if anything comes up before your next visit, don't hesitate to give us a call. Take care of yourself, okay? Bye bye.\n", "responseType": "text", "maxRecursionDepth": 10, "streaming": true, "x": 1031, "y": 727, "wires": [ [ "e0544da7fb7bbc74", "263a15a5e97ca892" ] ] }, { "id": "aefa89a7e6ec418c", "type": "debug", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "9625f63b907cee94", "name": "Call Transcript", "active": true, "tosidebar": false, "console": false, "tostatus": false, "complete": "true", "targetType": "full", "statusVal": "", "statusType": "auto", "x": 1040, "y": 900, "wires": [] }, { "id": "ef5a1e24cf08a745", "type": "ec-ws-out", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "847e518deb64a1e0", "name": "Send Audio to Caller", "x": 1652, "y": 729, "wires": [] }, { "id": "e0544da7fb7bbc74", "type": "ec-stream-exchange", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "847e518deb64a1e0", "name": "Live Audio Exchange", "accumulate": true, "appendKeys": "payload", "x": 1382, "y": 802, "wires": [ [ "7e57463b5718ddd0", "9be93bd89fb8509b" ] ] }, { "id": "263a15a5e97ca892", "type": "ec-twilio-twiml-response", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "847e518deb64a1e0", "name": "Build Voice Reply", "mode": "conversationRelay", "verb": "gather", "text": "", "voice": "Google.en-US-Chirp3-HD-Aoede", "language": "en-US", "loop": "", "audioUrl": "", "input": "speech", "speechTimeout": "auto", "speechModel": "phone_call", "enhanced": "true", "actionUrl": "", "actionMethod": "POST", "timeout": "5", "numDigits": "", "language_gather": "en-US", "hints": "", "dialTo": "", "callerId": "", "maxLength": "3600", "transcribe": "false", "redirectUrl": "", "pauseLength": "1", "rejectReason": "rejected", "twimlRaw": "", "x": 1372, "y": 729, "wires": [ [ "ef5a1e24cf08a745" ] ] }, { "id": "4a1cdf9def009881", "type": "ec-twilio-call-handler", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "da9822506c70b126", "name": "Handle Phone Call", "mode": "websocket", "twilioConfigId": "YOUR-TWILIO-CONFIG-ID", "validateSignature": false, "parseQueryParams": true, "aggregationTimeout": "300", "x": 490, "y": 680, "wires": [ [ "b80ad3d56c562319", "1cc397aa5a90507e" ], [] ] }, { "id": "1087df170fd489f1", "type": "ec-ws-in", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "da9822506c70b126", "name": "Listen for Call Audio", "path": "/main", "x": 221, "y": 687, "wires": [ [ "4a1cdf9def009881" ], [] ] }, { "id": "b80ad3d56c562319", "type": "function", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "da9822506c70b126", "name": "Get Current Qnr", "func": "const qnrs = flow.get('qnrs');\nlet curCallQnr = flow.get('curCallQnr')\nconst curQ = flow.get('curQ')\nlet histories = flow.get('histories')\n\n\nif (!histories) histories = []\n\nlet historyObj = histories.find(hry => hry.callSid === msg.payload.callSid)\nif (!historyObj) {\n historyObj = {\n callSid: msg.payload.callSid,\n history: []\n }\n}\nhistoryObj.history.push({\n role: 'user',\n content: msg.payload.text\n})\n\nmsg.history = historyObj.history;\nconst filteredHistories = histories.filter(hry => hry.callSid !== msg.payload.callSid)\n\nfilteredHistories.push(historyObj);\ntry {\n flow.set('histories', filteredHistories)\n} catch (error) {\n //suppress callback error\n};\n\nif (!curCallQnr) {\n curCallQnr = qnrs.find(q => q.callSid === msg.payload.callSid)\n try {\n flow.set('curCallQnr', curCallQnr)\n } catch (e) {\n\n }\n\n}\nconsole.log()\nmsg.payload = {\n ...msg.payload,\n curCallQnr,\n}\nreturn msg", "outputs": 1, "timeout": 0, "noerr": 0, "initialize": "", "finalize": "", "libs": [], "x": 732, "y": 674, "wires": [ [ "c3a13547ddee0f92", "aefa89a7e6ec418c" ] ] }, { "id": "1cc397aa5a90507e", "type": "debug", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "da9822506c70b126", "name": "Call Setup Output", "active": true, "tosidebar": true, "console": false, "tostatus": false, "complete": "payload", "targetType": "msg", "statusVal": "", "statusType": "auto", "x": 470, "y": 780, "wires": [] }, { "id": "d3cbbc56652e6a12", "type": "ai-model", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "27c4db7d8ce3bc17", "name": "Bedrock llm ", "provider": "bedrock", "model": "global.anthropic.claude-haiku-4-5-20251001-v1:0", "temperature": 0.7, "maxTokens": 1000, "vertexProjectId": "", "vertexLocation": "us-central1", "awsRegion": "us-east-1", "bedrockAuthMethod": "apiKey", "x": 221, "y": 1042, "wires": [ [ "f938093cdc47e5dc" ] ] }, { "id": "f938093cdc47e5dc", "type": "ai-agent", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "27c4db7d8ce3bc17", "name": "Intent Parser Agent", "systemPrompt": "You are a clinical answer extraction engine. You receive the full conversation history between a nurse (Beth) and a patient, along with the questionnaire. Your only job is to identify the question the patient just responded to and extract their answer in a structured format.\n\n═══════════════════════════════════════════════════\nINPUT FORMAT\n═══════════════════════════════════════════════════\n\nYou receive a JSON object with:\n\n- \"history\": Array of {role, content} conversation turns. \"assistant\" = Beth, \"user\" = patient.\n- \"curCallQnr\": The questionnaire object, including:\n - \"patientName\": The patient's name.\n - \"questions\": Array of question objects, each with:\n - \"id\": Question ID (e.g., \"q1-1\").\n - \"text\": The clinical question text.\n - \"responseType\": One of \"scale\", \"yes_no\", \"multiple_choice\", \"free_text\".\n - \"options\": Array of choices (for multiple_choice only).\n\n═══════════════════════════════════════════════════\nYOUR TASK\n═══════════════════════════════════════════════════\n\n1. Read the last few turns of the conversation history.\n2. Identify what question Beth most recently asked (match it to the questions array).\n3. Read the patient's latest response (the last \"user\" turn in history).\n4. Extract and normalize the patient's answer for that question.\n5. Return the result as structured JSON.\n\nDo NOT skip extraction even if the answer seems vague — always do your best to extract something. If the patient truly gave zero information, set parsedAns to null.\n\n═══════════════════════════════════════════════════\nANSWER PARSING RULES\n═══════════════════════════════════════════════════\n\nFor \"scale\" questions (1-10):\n- Extract the number. If the patient gives a range (\"seven or eight\"), use the HIGHER number.\n- Map qualitative words to numbers: \"terrible/awful/worst\" → 9-10, \"pretty bad/rough\" → 7-8, \"moderate/okay/alright\" → 4-6, \"mild/not bad\" → 2-3, \"none/fine/great/no issues\" → 0-1.\n- parsedAns must be an integer.\n\nFor \"yes_no\" questions:\n- \"yeah\", \"yep\", \"I have\", \"a little bit\", \"unfortunately\", \"I think so\" → \"yes\"\n- \"no\", \"nope\", \"not really\", \"I don't think so\", \"nah\", \"not at all\" → \"no\"\n- parsedAns must be the string \"yes\" or \"no\".\n\nFor \"multiple_choice\" questions:\n- Map the patient's words to the closest option from the options array.\n- parsedAns must be the exact option string.\n\nFor \"free_text\" questions:\n- Capture a clean version of what the patient said.\n- parsedAns is a string.\n\nFor identity verification (patient confirming/denying their name):\n- parsedAns is \"confirmed\", \"denied\", or \"unclear\".\n- questionId is null.\n\nIf the patient gave no usable answer (pure filler, off-topic, or asked to repeat), set parsedAns to null.\n\n═══════════════════════════════════════════════════\nRESPONSE FORMAT\n═══════════════════════════════════════════════════\n\nRespond with ONLY a valid JSON object. No extra text, no markdown, no explanation.\n\n{\n \"questionId\": \"q1-1\",\n \"parsedAns\": 8,\n \"rawAns\": \"Oh it's been pretty bad, I'd say like an eight or nine\"\n}\n\nField details:\n- \"questionId\": (string|null) The ID of the question being answered. Null during identity verification or if no question can be matched.\n- \"parsedAns\": (number|string|null) The normalized answer value. Null if no answer could be extracted.\n- \"rawAns\": (string) The patient's exact words from their latest turn.\n\n═══════════════════════════════════════════════════\nEXAMPLES\n═══════════════════════════════════════════════════\n\nExample 1 — Scale:\nBeth asked: \"On a scale of one to ten, how's the nausea been?\"\nPatient said: \"I'd say it's around a six\"\n→ {\"questionId\": \"q1-1\", \"parsedAns\": 6, \"rawAns\": \"I'd say it's around a six\"}\n\nExample 2 — Scale (qualitative):\nBeth asked: \"How would you rate your fatigue?\"\nPatient said: \"It's been really rough, I can barely get out of bed\"\n→ {\"questionId\": \"q1-4\", \"parsedAns\": 9, \"rawAns\": \"It's been really rough, I can barely get out of bed\"}\n\nExample 3 — Yes/No:\nBeth asked: \"Have you had any fever since you got home?\"\nPatient said: \"Yeah, I had a little fever yesterday\"\n→ {\"questionId\": \"q1-2\", \"parsedAns\": \"yes\", \"rawAns\": \"Yeah, I had a little fever yesterday\"}\n\nExample 4 — Multiple choice:\nBeth asked: \"How's your appetite been?\"\nPatient said: \"I've barely been eating, honestly\"\nQuestion options: [\"Normal\", \"Slightly decreased\", \"Significantly decreased\", \"Unable to eat\"]\n→ {\"questionId\": \"q1-5\", \"parsedAns\": \"Significantly decreased\", \"rawAns\": \"I've barely been eating, honestly\"}\n\nExample 5 — Free text:\nBeth asked: \"Is there anything you'd like to share with your care team?\"\nPatient said: \"Yes, I wanted to ask about my pain medication running out soon\"\n→ {\"questionId\": \"q1-10\", \"parsedAns\": \"Patient concerned about pain medication running out soon\", \"rawAns\": \"Yes, I wanted to ask about my pain medication running out soon\"}\n\nExample 6 — Identity confirmation:\nBeth asked: \"Am I speaking with Rahul?\"\nPatient said: \"Yes, this is Mehta speaking\"\n→ {\"questionId\": null, \"parsedAns\": \"confirmed\", \"rawAns\": \"Yes, this is Mehta speaking\"}\n\nExample 7 — No usable answer:\nBeth asked: \"On a scale of one to ten, how's the pain?\"\nPatient said: \"Can you say that again?\"\n→ {\"questionId\": \"q1-7\", \"parsedAns\": null, \"rawAns\": \"Can you say that again?\"}\n", "responseType": "object", "maxRecursionDepth": 10, "x": 417, "y": 1042, "wires": [ [ "7ac1ae24b10589b0", "aae24c9ab12f3fe1" ] ] }, { "id": "7ac1ae24b10589b0", "type": "debug", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "27c4db7d8ce3bc17", "name": "Parser Agent Output", "active": true, "tosidebar": true, "console": false, "tostatus": false, "complete": "payload", "targetType": "msg", "statusVal": "", "statusType": "auto", "x": 411, "y": 1102, "wires": [] }, { "id": "aae24c9ab12f3fe1", "type": "function", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "74b35be09d439992", "name": "Update Qnr", "func": "const qnrs = flow.get('qnrs');\nlet curCallQnr = flow.get('curCallQnr')\n\nif(!curCallQnr) return\n\nconst pOut = msg.payload;\nif (!pOut.questionId) return\n\n\nlet question = curCallQnr.questions.find(q=> q.id === pOut.questionId)\nif (!question) return\n\n\nquestion = {\n ...pOut,\n ...question\n}\nconst newQList = curCallQnr.questions.filter(q => q.id !== pOut.questionId);\nnewQList.push(question)\ncurCallQnr.questions = newQList;\n\nconst newQnrs = qnrs.filter(qnr=> qnr.callSid != curCallQnr.callSid)\nnewQnrs.push(curCallQnr)\n\ntry {\n flow.set('qnrs', newQnrs)\n flow.set('curCallQnr', curCallQnr)\n} catch (error) {\n \n};\n\nmsg.payload = {\n ...msg.payload,\n question\n}\n\nreturn msg", "outputs": 1, "timeout": 0, "noerr": 0, "initialize": "", "finalize": "", "libs": [], "x": 218, "y": 1235, "wires": [ [ "774319bb58831365", "114f444eba5023c5" ] ] }, { "id": "774319bb58831365", "type": "function", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "74b35be09d439992", "name": "Check For Escalation", "func": "let data = msg.payload;\nif (data && data.question && data.question.redFlagEnabled && data.question.redFlagThreshold) {\n let parsedAns = data.parsedAns;\n let thresholdStr = data.question.redFlagThreshold;\n let responseType = data.question.responseType;\n let isExceeded = false;\n\n // 1. Math-based comparison for numeric or scale responses\n if (responseType === 'scale' || responseType === 'numeric') {\n // Extract numbers ignoring text anomalies like \"≥ \"\n let thresholdNum = parseFloat(thresholdStr.replace(/[^0-9.]/g, ''));\n let ansNum = typeof parsedAns === 'number' ? parsedAns : parseFloat(String(parsedAns).replace(/[^0-9.]/g, ''));\n\n if (!isNaN(thresholdNum) && !isNaN(ansNum)) {\n if (thresholdStr.includes('>=') || thresholdStr.includes('≥')) {\n isExceeded = ansNum >= thresholdNum;\n } else if (thresholdStr.includes('>')) {\n isExceeded = ansNum > thresholdNum;\n } else if (thresholdStr.includes('<=') || thresholdStr.includes('≤')) {\n isExceeded = ansNum <= thresholdNum;\n } else if (thresholdStr.includes('<')) {\n isExceeded = ansNum < thresholdNum;\n } else {\n isExceeded = ansNum === thresholdNum;\n }\n }\n }\n // 2. String-based strict comparison for yes_no / multiple choice \n else {\n let pAns = String(parsedAns).trim().toLowerCase();\n let tStr = String(thresholdStr).trim().toLowerCase();\n isExceeded = pAns === tStr;\n }\n // 3. Construct payload on Escalation\n if (isExceeded) {\n let qText = data.question.text;\n let rawAns = data.rawAns;\n\n // Construct natural language message\n let textMessage = `when asked \"${qText}\", The patient responded with \"${rawAns}\" exceeding set threshold \"${thresholdStr}\"`;\n\n // Node.js environment automatically supports Buffer for base64 encoding\n let base64Message = Buffer.from(textMessage).toString('base64');\n\n // Append escalation details to the output message Object\n msg.escalation = true;\n msg.escalationDetails = {\n message: textMessage,\n messageBase64: base64Message\n };\n\n // Assuming two outputs in the Node-RED node: 1 for escalation, 2 for passes threshold\n return [msg, null];\n }\n}\n// Failed to exceed the threshold (or lacked red flag)\nmsg.escalation = false;\nreturn [null, msg]; // Send untouched payload through output 2", "outputs": 2, "timeout": 0, "noerr": 0, "initialize": "", "finalize": "", "libs": [], "x": 448, "y": 1235, "wires": [ [ "d7dc4787d08d40dd" ], [ "8f335cbedc2f64f6" ] ] }, { "id": "d7dc4787d08d40dd", "type": "debug", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "74b35be09d439992", "name": "🚨 Escalation Alert", "active": true, "tosidebar": true, "console": false, "tostatus": false, "complete": "['Escalation Triggered']", "targetType": "jsonata", "statusVal": "", "statusType": "auto", "x": 728, "y": 1215, "wires": [] }, { "id": "8f335cbedc2f64f6", "type": "debug", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "74b35be09d439992", "name": "Log Check Result", "active": true, "tosidebar": true, "console": false, "tostatus": false, "complete": "false", "statusVal": "", "statusType": "auto", "x": 728, "y": 1275, "wires": [] }, { "id": "114f444eba5023c5", "type": "debug", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "74b35be09d439992", "name": "Qnr Output", "active": true, "tosidebar": true, "console": false, "tostatus": false, "complete": "payload", "targetType": "msg", "statusVal": "", "statusType": "auto", "x": 238, "y": 1275, "wires": [] }, { "id": "04ac81a1f3f4a972", "type": "http in", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "ff8c6904bbf68daa", "name": "GET /qnr", "url": "qnr", "method": "get", "upload": false, "skipBodyParsing": false, "swaggerDoc": "", "x": 260, "y": 1600, "wires": [ [ "c5be54d98cbe8ff0" ] ] }, { "id": "c5be54d98cbe8ff0", "type": "change", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "ff8c6904bbf68daa", "name": "Get flow.curQnr", "rules": [ { "t": "set", "p": "payload", "pt": "msg", "to": "curCallQnr", "tot": "flow", "dc": true } ], "action": "", "property": "", "from": "", "to": "", "reg": false, "x": 490, "y": 1600, "wires": [ [ "d5138dc7da8d88b3" ] ] }, { "id": "d5138dc7da8d88b3", "type": "http response", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "ff8c6904bbf68daa", "name": "200 OK", "statusCode": "200", "headers": {}, "x": 770, "y": 1600, "wires": [] }, { "id": "5f14654bf2a8836b", "type": "http in", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "ff8c6904bbf68daa", "name": "GET /histories", "url": "histories", "method": "get", "upload": false, "skipBodyParsing": false, "swaggerDoc": "", "x": 281, "y": 1728, "wires": [ [ "045489cdb5236e0e" ] ] }, { "id": "045489cdb5236e0e", "type": "change", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "ff8c6904bbf68daa", "name": "Get flow.histories", "rules": [ { "t": "set", "p": "payload", "pt": "msg", "to": "histories", "tot": "flow", "dc": true } ], "action": "", "property": "", "from": "", "to": "", "reg": false, "x": 511, "y": 1728, "wires": [ [ "6626d5eae29fd80b" ] ] }, { "id": "6626d5eae29fd80b", "type": "http response", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "ff8c6904bbf68daa", "name": "200 OK", "statusCode": "200", "headers": {}, "x": 811, "y": 1728, "wires": [] }, { "id": "a52b627877265402", "type": "change", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "ff8c6904bbf68daa", "name": "Get flow.qnrs", "rules": [ { "t": "set", "p": "payload", "pt": "msg", "to": "qnrs", "tot": "flow", "dc": true } ], "action": "", "property": "", "from": "", "to": "", "reg": false, "x": 493, "y": 1666, "wires": [ [ "d0ce655755761e2a" ] ] }, { "id": "d0ce655755761e2a", "type": "http response", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "ff8c6904bbf68daa", "name": "200 OK", "statusCode": "200", "headers": {}, "x": 773, "y": 1666, "wires": [] }, { "id": "f5550ddb65be5d6c", "type": "http in", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "g": "ff8c6904bbf68daa", "name": "GET /qnrs", "url": "/qnrs", "method": "get", "upload": false, "skipBodyParsing": false, "swaggerDoc": "", "x": 268, "y": 1666, "wires": [ [ "a52b627877265402" ] ] }, { "id": "e5566f502682aa30", "type": "function", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "name": "Save AI Response", "func": "// Get callSid from message\nconst callSid = msg.callSid || msg.sessionId;\n\nif (!callSid) {\n node.error(\"No callSid found in message\");\n return null;\n}\n\n// Initialize aggregation context for streaming\nlet streamBuffer = context.get('streamBuffer') || {};\n\n// Handle streaming responses\nif (msg.streaming === true || msg.chunk !== undefined) {\n // Initialize buffer for this call if needed\n if (!streamBuffer[callSid]) {\n streamBuffer[callSid] = '';\n }\n \n // Append chunk to buffer\n const chunk = msg.payload || msg.chunk || '';\n streamBuffer[callSid] += chunk;\n context.set('streamBuffer', streamBuffer);\n \n // If not complete, don't save to history yet\n if (!msg.complete && !msg.done && !msg.final) {\n // Pass through for real-time TTS but don't save yet\n return [msg, null];\n }\n \n // Last chunk - use accumulated buffer\n msg.aiResponse = streamBuffer[callSid];\n \n // Clean up buffer\n delete streamBuffer[callSid];\n context.set('streamBuffer', streamBuffer);\n} else {\n // Non-streaming response\n msg.aiResponse = msg.payload || msg.response;\n}\n\n// Get calls history (synchronous get)\nlet calls = flow.get('calls') || {};\n\nif (!calls[callSid]) {\n node.warn(`No call history found for callSid: ${callSid}, creating new session`);\n calls[callSid] = {\n sessionId: callSid,\n history: []\n };\n}\n\n// Append AI response to history in correct format\nconst assistantMessage = {\n role: 'assistant',\n content: msg.aiResponse,\n timestamp: new Date().toISOString()\n};\n\ncalls[callSid].history.push(assistantMessage);\n\nmsg.history = calls[callSid].history;\n\nnode.status({\n fill: \"blue\",\n shape: \"dot\",\n text: `${calls[callSid].history.length} messages`\n});\n\n// Save back to flow context with callback\nflow.set('calls', calls, (err) => {\n if (err) {\n node.error(`Error saving calls: ${err.message}`);\n }\n});\n\nreturn [null, msg]; // Output 2: complete response saved", "outputs": 2, "timeout": 0, "noerr": 0, "initialize": "", "finalize": "", "libs": [], "x": 1630, "y": 300, "wires": [ [], [] ] }, { "id": "502a492de311836f", "type": "catch", "z": "workflow_8f95139a-a937-44a7-8d7c-4794fce09856", "name": "Error Suppresss", "scope": [ "3156500826f161f8" ], "uncaught": false, "x": 1500, "y": 180, "wires": [ [] ] } ] }, "requirements": [] }