[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_247":248,"_249":250},"routes/_app.x.$handle.$name",{"_132":131,"_36":74,"_141":120,"_31":142,"_13":14,"_143":-5,"_11":144,"_145":146,"_147":148,"_149":150,"_151":152,"_25":-5,"_153":154,"_155":156,"_157":29,"_158":159,"_160":89,"_161":-5,"_162":-5,"_163":164},"routes/_app.x.$handle.$name.branch.$branch.version.$version.diff",{"_11":12,"_13":14,"_15":16,"_17":-5,"_18":-5},"project",{"_72":73,"_36":74,"_41":75,"_76":-5,"_77":29,"_78":79,"_80":79,"_81":82,"_83":84,"_18":85,"_86":87,"_88":89,"_90":-5,"_91":-5,"_92":93,"_94":95,"_96":97,"_98":99,"_100":101,"_102":-5,"_103":104,"_105":104,"_106":107,"_108":107,"_109":107,"_110":104,"_111":104,"_112":113,"_114":115,"_116":117,"_118":29},"version",1,"changes",[19,20,21,22,23,24],"aiChatInfo","userId",{"_25":67,"_27":-7,"_28":29,"_30":29,"_31":68,"_33":68},{"_25":62,"_27":-7,"_28":29,"_30":29,"_31":63,"_33":63},{"_25":56,"_27":-7,"_28":29,"_30":29,"_31":57,"_33":57},{"_25":51,"_27":-7,"_28":29,"_30":29,"_31":52,"_33":52},{"_25":46,"_27":-7,"_28":29,"_30":29,"_31":47,"_33":47},{"_25":26,"_27":-7,"_28":29,"_30":29,"_31":32,"_33":32},"file",{"_34":35,"_36":32,"_37":38,"_39":40,"_41":42,"_43":14,"_44":45,"_28":29},"previous","deleted",false,"deletedHere","path","vapi.ts","latestPath","fileId","019ec8ff-b70b-705e-aff8-a6d646b38698","name","fileType","script","content","// Thin Vapi REST client — BYOK: every function takes the caller's own key.\n// Nothing is read from env; this is a public multi-tenant server.\n//\n// dispatch-my-human DOES use Vapi's own LLM brain (native model), unlike the\n// puppet sibling call-my-human whose custom-llm always returned \"\". The agent\n// runs the whole conversation itself for low latency, then Vapi's analysis\n// produces a structured report we hand back to the dispatcher.\n\nconst VAPI_BASE = \"https://api.vapi.ai\";\n\nexport interface DispatchOpts {\n vapiKey: string;\n phoneNumberId: string;\n number: string;\n firstMessage: string;\n systemPrompt: string;\n questions: string[];\n model: string; // e.g. \"gpt-4o\"\n maxDurationSeconds: number;\n origin: string; // this val's https origin\n tenant: string; // short hash of the vapi key — routes webhooks back to the right feed\n}\n\n// Structured report schema: objective + one answer per required question + followups.\n// The required questions are baked into the schema descriptions (not a separate\n// prompt) so the extractor always sees them — Vapi feeds it the transcript by default.\nfunction structuredSchema(questions: string[]) {\n const qList = questions.length\n ? \" The agent was told to get answers to these specific questions: \" +\n questions.map((q, i) => `(${i + 1}) ${q}`).join(\"; \") +\n \". Provide one entry per question, in that order.\"\n : \"\";\n return {\n type: \"object\",\n properties: {\n objective_met: {\n type: \"boolean\",\n description: \"True if the call accomplished its stated objective.\",\n },\n answers: {\n type: \"array\",\n description:\n \"One entry for each question the agent was asked to get answered, with the human's answer.\" + qList,\n items: {\n type: \"object\",\n properties: {\n question: { type: \"string\", description: \"The question the agent needed answered.\" },\n answer: {\n type: \"string\",\n description: \"The human's answer, paraphrased or verbatim. Use 'not answered' if never resolved.\",\n },\n },\n required: [\"question\", \"answer\"],\n },\n },\n followups: {\n type: \"string\",\n description:\n \"Anything the human raised, requested, or asked that the dispatcher should act on after the call. Empty string if none.\",\n },\n },\n required: [\"objective_met\", \"answers\"],\n };\n}\n\nexport async function createDispatchCall(opts: DispatchOpts) {\n const body = {\n phoneNumberId: opts.phoneNumberId,\n customer: { number: opts.number },\n assistant: {\n firstMessage: opts.firstMessage,\n // A REAL brain this time: Vapi runs the LLM in-stack (lowest latency, no\n // round-trip back to the dispatcher). The endCall tool lets it hang up\n // itself once the objective is met.\n model: {\n provider: \"openai\",\n model: opts.model,\n temperature: 0.6,\n messages: [{ role: \"system\", content: opts.systemPrompt }],\n tools: [\n { type: \"endCall\" },\n // The escape hatch. When the agent hits a question outside its brief it\n // calls this; our /tool endpoint blocks until the operator answers (or\n // times out), then returns the answer as the tool result for the agent\n // to relay. The messages keep the human company during the wait.\n {\n type: \"function\",\n function: {\n name: \"ask_operator\",\n description:\n \"Ask your operator (the AI assistant that dispatched you) something you cannot answer from your briefing. Use this the MOMENT the human asks something outside what you were told — never guess or make it up. The operator replies and you relay their answer to the human.\",\n parameters: {\n type: \"object\",\n properties: {\n question: {\n type: \"string\",\n description: \"The human's question, phrased clearly and completely for your operator.\",\n },\n },\n required: [\"question\"],\n },\n },\n server: { url: `${opts.origin}/tool/${opts.tenant}`, secret: opts.tenant, timeoutSeconds: 45 },\n messages: [\n { type: \"request-start\", content: \"Good question — let me check on that real quick.\" },\n {\n type: \"request-response-delayed\",\n content: \"Still checking on that, hang with me one second.\",\n timingMilliseconds: 12000,\n },\n {\n type: \"request-failed\",\n content: \"Hmm, I couldn't reach them just now — I'll make sure they follow up on that for you.\",\n },\n ],\n },\n ],\n },\n // No transcriber override — use Vapi's default (what templates/vapi-phone-call\n // uses). The explicit deepgram nova-2 override added latency and produced\n // duplicated/cumulative transcript lines. Native models get a default STT.\n // Vapi-native voice — what the dashboard \"test call\" uses, tuned for telephony\n // and bundled (no extra provider key). Much better on a phone than openai/shimmer.\n voice: { provider: \"vapi\", voiceId: \"Elliot\", version: 2 },\n server: { url: `${opts.origin}/webhook/${opts.tenant}`, secret: opts.tenant },\n serverMessages: [\"transcript\", \"status-update\", \"end-of-call-report\", \"conversation-update\"],\n // The human pauses to think; the agent answers immediately, so dead air\n // means a genuinely dropped/empty call — 30s is a safe cutoff.\n silenceTimeoutSeconds: 30,\n maxDurationSeconds: opts.maxDurationSeconds,\n // Auto-summarize + extract the structured report when the call ends.\n // Schema only — Vapi's default extractor prompt already receives the\n // transcript; a custom {{transcript}} message silently broke extraction.\n analysisPlan: {\n structuredDataPlan: {\n enabled: true,\n schema: structuredSchema(opts.questions),\n },\n },\n },\n };\n\n console.log(\"vapi: dispatching call →\", opts.number, \"tenant\", opts.tenant, \"model\", opts.model);\n const res = await fetch(`${VAPI_BASE}/call`, {\n method: \"POST\",\n headers: { Authorization: `Bearer ${opts.vapiKey}`, \"Content-Type\": \"application/json\" },\n body: JSON.stringify(body),\n });\n const data = await res.json();\n if (!res.ok) {\n console.log(\"vapi: dispatch FAILED\", res.status, JSON.stringify(data).slice(0, 500));\n throw new Error(`Vapi ${res.status}: ${JSON.stringify(data)}`);\n }\n console.log(\"vapi: call created\", data.id, \"controlUrl:\", data.monitor?.controlUrl ? \"present\" : \"MISSING\");\n return data as { id: string; status?: string; monitor?: { controlUrl?: string; listenUrl?: string } };\n}\n\nexport async function control(controlUrl: string, payload: Record) {\n const res = await fetch(controlUrl, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify(payload),\n });\n const text = await res.text();\n console.log(\"vapi control:\", payload.type, \"→\", res.status, text.slice(0, 200));\n return { status: res.status, body: text };\n}\n\n// Optional supervisor barge-in: inject a verbatim line over the live call.\n// Docs use `content`; the SDK's SayMessage type uses `message`. Try both.\nexport async function sayOnCall(controlUrl: string, text: string, endCallAfterSpoken = false) {\n const base: Record = { type: \"say\", content: text };\n if (endCallAfterSpoken) base.endCallAfterSpoken = true;\n let r = await control(controlUrl, base);\n if (r.status >= 400) {\n const alt: Record = { type: \"say\", message: text };\n if (endCallAfterSpoken) alt.endCallAfterSpoken = true;\n r = await control(controlUrl, alt);\n }\n return r;\n}\n\nexport async function endCallOnVapi(controlUrl: string) {\n return control(controlUrl, { type: \"end-call\" });\n}\n\nexport async function getCallLive(vapiKey: string, callId: string) {\n const res = await fetch(`${VAPI_BASE}/call/${callId}`, {\n headers: { Authorization: `Bearer ${vapiKey}` },\n });\n const data = await res.json();\n if (!res.ok) throw new Error(`Vapi GET /call ${res.status}: ${JSON.stringify(data).slice(0, 300)}`);\n return data;\n}\n","createdAt",["D",1781488662285],"branchVersion","branchId","d8654f79-c562-49ef-ad3d-1c9d7ac67d52",{"_34":48,"_36":47,"_37":38,"_39":49,"_41":50,"_43":14,"_44":45,"_28":29},"tools.ts","019ec8ff-b70b-705e-aff8-a244b93f7df1","// The tools, defined once and exposed twice: over MCP (/mcp) and REST (/api/call/*).\n// All config arrives per-request (BYOK) via ctx — built in main.ts from the\n// connection URL's query params. Nothing comes from env.\n//\n// Unlike the puppet sibling (call-my-human), here the Vapi agent has a REAL\n// brain and runs the whole conversation itself. Primary loop:\n// dispatch_call → hand off a brief + objective + questions\n// await_report → long-poll until it hangs up, get the structured result\n// listen / say are optional supervisor hooks (eavesdrop / barge in).\n\nimport * as db from \"./db.ts\";\nimport { createDispatchCall, endCallOnVapi, getCallLive, sayOnCall } from \"./vapi.ts\";\n\nexport interface Ctx {\n origin: string;\n vapiKey: string | null;\n phoneNumberId: string | null;\n humanNumber: string | null;\n model: string; // LLM the agent's brain runs on (default gpt-4o)\n tenant: string | null; // short hash of vapiKey\n}\n\nconst CONNECT_HELP =\n \"Missing Vapi credentials. Put them in your MCP connection URL: /mcp?vapi_key=&phone_number_id=&human_number=%2B15551234567 (the + must be URL-encoded as %2B). Get the key and phone number at dashboard.vapi.ai.\";\n\nfunction creds(ctx: Ctx): { vapiKey: string; tenant: string } {\n if (!ctx.vapiKey || !ctx.tenant) throw new Error(CONNECT_HELP);\n return { vapiKey: ctx.vapiKey, tenant: ctx.tenant };\n}\n\nconst ACTIVE = [\"starting\", \"queued\", \"ringing\", \"in-progress\", \"forwarding\"];\n\nasync function requireActiveCall(tenant: string): Promise {\n const call = await db.latestCall(tenant);\n if (!call) throw new Error(\"No call yet — use dispatch_call first.\");\n if (!ACTIVE.includes(call.status)) {\n throw new Error(\n `Latest call ${call.id} is '${call.status}'${call.ended_reason ? ` (${call.ended_reason})` : \"\"} — start a new one with dispatch_call.`,\n );\n }\n return call;\n}\n\nconst fmt = (e: db.EventRow) => ({\n t: e.created_at.slice(11, 19),\n type: e.type,\n role: e.role,\n content: e.content,\n});\n\n// Build the agent's system prompt from the dispatch brief. This IS the brain —\n// it carries the whole call, so be explicit about who it is and what \"done\" means.\nfunction buildSystemPrompt(opts: {\n objective: string;\n context: string;\n questions: string[];\n callerIdentity: string;\n maxMinutes: number;\n}): string {\n const qBlock = opts.questions.length\n ? \"Before you hang up, get a clear answer to EACH of these:\\n\" +\n opts.questions.map((q, i) => ` ${i + 1}. ${q}`).join(\"\\n\")\n : \"There are no specific required questions beyond the objective above.\";\n const ctxBlock = opts.context.trim()\n ? `Context you've been briefed with (use it; don't read it aloud verbatim):\\n${opts.context.trim()}`\n : \"You have not been given extra context beyond the objective.\";\n\n return `You are ${opts.callerIdentity}. You are placing an OUTBOUND phone call to a person on behalf of your operator (the AI assistant / system that dispatched you), who is busy and needs something from them. You called THEM — you are not their assistant waiting for requests.\n\nYOUR OBJECTIVE:\n${opts.objective.trim()}\n\n${ctxBlock}\n\n${qBlock}\n\nHOW TO TALK:\n- Sound like a real person on the phone: short, natural sentences, one idea at a time. No monologues.\n- Open by quickly saying who you are and why you're calling, then get to the point.\n- Listen and react to what they actually say. Don't plow through a script.\n- If it's a bad time, offer to have your operator follow up later, then wrap up.\n\nIF THEY ASK SOMETHING OUTSIDE YOUR BRIEF:\n- Do NOT guess, improvise, or make something up. The moment the human asks something your objective and context don't clearly cover, call the ask_operator function with their exact question.\n- A short \"let me check on that\" plays automatically while your operator is reached. When the answer comes back as the tool result, relay it to the human naturally, in your own words.\n- Use this only for genuine gaps — not for things you can already answer from your briefing.\n\nWHEN YOU'RE DONE:\n- NEVER end the call while the human is still talking or mid-thought. Wait for a clear, complete answer and a natural pause.\n- Only after you have answers to ALL the required questions (or they say they have to go) should you wrap up. First ask \"anything else before I let you go?\" — if they're still talking, keep listening; do not hang up.\n- Then briefly confirm what you heard, thank them, and use the endCall function.\n- Keep the whole call under ${opts.maxMinutes} minutes, but getting complete answers matters more than speed — don't rush them off.`;\n}\n\nexport const TOOLS = [\n {\n name: \"dispatch_call\",\n description:\n \"Dispatch a voice agent to phone your human and handle a conversation autonomously, then hang up. UNLIKE a puppet, this agent has a real brain: you hand it a brief once and it carries the whole call itself with low latency — you do NOT drive it turn by turn. Give it a clear `objective`, any `context` it needs, and the specific `questions` you want answered. After it returns, call `await_report` to block until the call ends and collect the structured result (summary + per-question answers + followups). For most check-ins this is the only tool you need besides await_report.\",\n inputSchema: {\n type: \"object\",\n properties: {\n objective: {\n type: \"string\",\n description: \"The goal of the call in plain language, e.g. 'Confirm whether we should ship the release tonight or wait for QA.'\",\n },\n context: {\n type: \"string\",\n description: \"Everything the agent should know to handle the call well — the situation, relevant facts, constraints. Dump freely; it won't read it aloud.\",\n },\n questions: {\n type: \"array\",\n items: { type: \"string\" },\n description: \"Specific questions you need answered. Each becomes a field in the returned report.\",\n },\n number: {\n type: \"string\",\n description: \"E.164 number to dial, e.g. +15551234567. Defaults to the human_number from your connection URL.\",\n },\n first_message: {\n type: \"string\",\n description: \"The exact opening line the agent speaks on pickup. Optional — a sensible default is used.\",\n },\n caller_identity: {\n type: \"string\",\n description: \"Who the agent should present as, e.g. 'Charlie's AI assistant'. Optional.\",\n },\n max_minutes: {\n type: \"number\",\n description: \"Hard cap on call length in minutes (default 10).\",\n },\n },\n required: [\"objective\"],\n },\n run: async (args: Record, ctx: Ctx) => {\n const { vapiKey, tenant } = creds(ctx);\n const phoneNumberId = ctx.phoneNumberId || String(args.phone_number_id || \"\");\n if (!phoneNumberId) {\n throw new Error(\"phone_number_id missing — add &phone_number_id= to your connection URL.\");\n }\n const prev = await db.latestCall(tenant);\n if (prev && ACTIVE.includes(prev.status)) {\n let stillActive = false;\n try {\n const live = await getCallLive(vapiKey, prev.id);\n if (live.status && live.status !== prev.status) {\n await db.setCallStatus(prev.id, live.status, live.endedReason ?? null);\n }\n stillActive = ACTIVE.includes(live.status);\n } catch (e) {\n console.log(\"dispatch_call: live status check failed, allowing new call:\", String(e).slice(0, 120));\n }\n if (stillActive) throw new Error(`Call ${prev.id} is still active — end_call it first.`);\n }\n const number = String(args.number || ctx.humanNumber || \"\");\n if (!number) {\n throw new Error(\n \"No number to dial — pass `number`, or add &human_number=%2B15551234567 to your connection URL.\",\n );\n }\n const objective = String(args.objective || \"\").trim();\n if (!objective) throw new Error(\"`objective` is required — tell the agent what the call is for.\");\n const context = String(args.context || \"\");\n const questions = Array.isArray(args.questions) ? args.questions.map(String).filter(Boolean) : [];\n const callerIdentity = String(args.caller_identity || \"an AI voice assistant\");\n const maxMinutes = Math.min(Math.max(Number(args.max_minutes ?? 10), 1), 15);\n const firstMessage = String(\n args.first_message ||\n \"Hi! This is your AI assistant calling — I've got a quick thing to run by you, do you have a sec?\",\n );\n const systemPrompt = buildSystemPrompt({ objective, context, questions, callerIdentity, maxMinutes });\n\n const call = await createDispatchCall({\n vapiKey,\n phoneNumberId,\n number,\n firstMessage,\n systemPrompt,\n questions,\n model: ctx.model,\n maxDurationSeconds: maxMinutes * 60,\n origin: ctx.origin,\n tenant,\n });\n const controlUrl = call.monitor?.controlUrl ?? \"\";\n await db.insertCall(tenant, call.id, controlUrl, number);\n await db.addEvent(tenant, call.id, \"status\", \"system\", `dispatching ${number} · objective: ${objective.slice(0, 120)}`);\n return {\n call_id: call.id,\n status: call.status ?? \"queued\",\n dialing: number,\n questions_tracked: questions.length,\n watch_url: `${ctx.origin}/?t=${tenant}`,\n next:\n \"Call `await_report` now and keep calling it. It returns either needs_answer:true (the agent hit an off-brief question — reply with `provide_answer`, then await_report again) or done:true with the summary + answers. Optional: `listen` / `say` to eavesdrop or barge in.\",\n };\n },\n },\n {\n name: \"await_report\",\n description:\n \"Block until the dispatched call finishes, then return the structured outcome: a summary, an answer to each question you asked, anything the human raised for follow-up, and the full transcript. Long-polls up to wait_seconds — keep calling it (it's cheap) until you get done:true. While done:false the call is still in progress or the post-call analysis is still being written.\",\n inputSchema: {\n type: \"object\",\n properties: {\n wait_seconds: { type: \"number\", description: \"Max seconds to long-poll this call (1-25, default 20).\" },\n },\n },\n run: async (args: Record, ctx: Ctx) => {\n const { vapiKey, tenant } = creds(ctx);\n const call = await db.latestCall(tenant);\n if (!call) throw new Error(\"No call yet — use dispatch_call first.\");\n const wait = Math.min(Math.max(Number(args.wait_seconds ?? 20), 1), 25);\n const deadline = Date.now() + wait * 1000;\n\n const buildReport = async (status: string, endedReason: string | null) => {\n const analysis = await db.latestEventOfType(call.id, \"analysis\");\n const summaryEv = await db.latestEventOfType(call.id, \"report\");\n let structured: Record | null = null;\n if (analysis?.content) {\n try {\n structured = JSON.parse(analysis.content);\n } catch { /* leave null */ }\n }\n const transcript = (await db.transcriptLines(call.id)).map((e) => ({ role: e.role, text: e.content }));\n return {\n done: true,\n call_status: status,\n ended_reason: endedReason,\n summary: summaryEv?.content ?? null,\n objective_met: structured?.objective_met ?? null,\n answers: structured?.answers ?? null,\n followups: structured?.followups ?? null,\n transcript,\n ...(structured ? {} : { note: \"Call ended but structured analysis isn't ready yet — call await_report once more in a few seconds.\" }),\n };\n };\n\n while (true) {\n // Escape hatch: if the agent is waiting on YOU for an off-brief question,\n // surface it immediately so you can provide_answer.\n const esc = await db.pendingEscalation(tenant);\n if (esc) {\n return {\n done: false,\n needs_answer: true,\n escalation: { id: esc.id, question: esc.question },\n note:\n \"The agent hit a question outside its brief and is waiting on YOU. Answer it with provide_answer({ text }) — it will relay your answer to the human — then call await_report again.\",\n };\n }\n let current = await db.getCall(call.id);\n const terminal = current && !ACTIVE.includes(current.status);\n // Done = call ended AND the post-call analysis has landed (or we've waited it out).\n if (terminal) {\n const analysis = await db.latestEventOfType(call.id, \"analysis\");\n if (analysis) return await buildReport(current!.status, current!.ended_reason);\n }\n if (Date.now() > deadline) {\n // Sync from Vapi in case a webhook was missed.\n try {\n const live = await getCallLive(vapiKey, call.id);\n if (live?.status && live.status !== current?.status) {\n await db.setCallStatus(call.id, String(live.status), (live.endedReason as string) ?? null);\n current = await db.getCall(call.id);\n }\n } catch (e) {\n console.log(\"await_report: live status check failed:\", String(e).slice(0, 120));\n }\n const stillTerminal = current && !ACTIVE.includes(current.status);\n if (stillTerminal) return await buildReport(current!.status, current!.ended_reason);\n return {\n done: false,\n call_status: current?.status ?? \"unknown\",\n ...(current?.live_partial ? { hearing_now: current.live_partial } : {}),\n note: \"Call still in progress — call await_report again to keep waiting.\",\n };\n }\n await new Promise((r) => setTimeout(r, 1000));\n }\n },\n },\n {\n name: \"provide_answer\",\n description:\n \"Answer a question the agent escalated to you mid-call (when await_report returns needs_answer:true). Your text is handed back to the agent as the result of its ask_operator call, and it relays it to the human in its own words. Keep it brief and factual — it will be spoken aloud. After answering, call await_report again to keep waiting for the report or the next question.\",\n inputSchema: {\n type: \"object\",\n properties: {\n text: {\n type: \"string\",\n description: \"The answer to relay, in plain language. It's spoken to the human, so keep it concise.\",\n },\n },\n required: [\"text\"],\n },\n run: async (args: Record, ctx: Ctx) => {\n const { tenant } = creds(ctx);\n const esc = await db.pendingEscalation(tenant);\n if (!esc) {\n throw new Error(\"No pending question from the agent right now — call await_report to see if it asks one.\");\n }\n const text = String(args.text ?? \"\").trim();\n if (!text) throw new Error(\"`text` is required — provide the answer to relay to the human.\");\n await db.answerEscalation(esc.id, text);\n return { ok: true, answered: esc.question, next: \"Relayed to the agent. Call await_report again to continue.\" };\n },\n },\n {\n name: \"listen\",\n description:\n \"Optional: eavesdrop on a live dispatched call. Long-polls for new events (the human's speech, the agent's lines, status changes) up to wait_seconds. Use this if you want to watch the conversation unfold in realtime; you do NOT need it for the normal dispatch→await_report flow.\",\n inputSchema: {\n type: \"object\",\n properties: {\n wait_seconds: { type: \"number\", description: \"Max seconds to wait (1-25, default 20).\" },\n },\n },\n run: async (args: Record, ctx: Ctx) => {\n const { vapiKey, tenant } = creds(ctx);\n const call = await db.latestCall(tenant);\n if (!call) throw new Error(\"No call yet — use dispatch_call first.\");\n const wait = Math.min(Math.max(Number(args.wait_seconds ?? 20), 1), 25);\n const deadline = Date.now() + wait * 1000;\n let cursor = call.cursor;\n while (true) {\n const events = await db.eventsAfter(call.id, cursor);\n const maxId = events.length ? events[events.length - 1].id : cursor;\n if (events.length) {\n await db.setCursor(call.id, maxId);\n const current = await db.getCall(call.id);\n const over = current && !ACTIVE.includes(current.status);\n return {\n events: events.map(fmt),\n call_status: current?.status ?? call.status,\n ...(over ? { note: `Call is over (${current?.ended_reason ?? current?.status}). Use await_report for the result.` } : {}),\n };\n }\n const current = await db.getCall(call.id);\n if (current && !ACTIVE.includes(current.status)) {\n return {\n events: [],\n call_status: current.status,\n note: `Call is over (${current.ended_reason ?? current.status}). Use await_report for the result.`,\n };\n }\n if (Date.now() > deadline) {\n try {\n const live = await getCallLive(vapiKey, call.id);\n if (live?.status && live.status !== current?.status) {\n await db.setCallStatus(call.id, String(live.status), (live.endedReason as string) ?? null);\n }\n } catch (e) {\n console.log(\"listen: live status check failed:\", String(e).slice(0, 120));\n }\n const synced = await db.getCall(call.id);\n if (synced && !ACTIVE.includes(synced.status)) {\n return {\n events: [],\n call_status: synced.status,\n note: `Call is over (${synced.ended_reason ?? synced.status}). Use await_report for the result.`,\n };\n }\n return {\n events: [],\n call_status: synced?.status ?? \"unknown\",\n ...(synced?.live_partial ? { hearing_now: synced.live_partial } : {}),\n note: \"Nothing new yet — the agent is handling it. listen again, or just await_report.\",\n };\n }\n await new Promise((r) => setTimeout(r, 800));\n }\n },\n },\n {\n name: \"say\",\n description:\n \"Optional supervisor barge-in: speak a verbatim line over the live call yourself (TTS), e.g. to correct the agent or relay a fact it didn't have. Normally unnecessary — the agent drives the call. Set end_call_after true to hang up after the line plays.\",\n inputSchema: {\n type: \"object\",\n properties: {\n text: { type: \"string\", description: \"What to say, verbatim.\" },\n end_call_after: { type: \"boolean\", description: \"Hang up after this line finishes playing.\" },\n },\n required: [\"text\"],\n },\n run: async (args: Record, ctx: Ctx) => {\n const { tenant } = creds(ctx);\n const call = await requireActiveCall(tenant);\n if (!call.control_url) throw new Error(\"No controlUrl stored for this call — cannot inject speech.\");\n const r = await sayOnCall(call.control_url, String(args.text), Boolean(args.end_call_after));\n await db.addEvent(tenant, call.id, \"say\", \"assistant\", String(args.text));\n if (r.status >= 400) throw new Error(`Vapi control rejected say (${r.status}): ${r.body.slice(0, 200)}`);\n return { ok: true, vapi_status: r.status, next: \"Use listen to hear their response, or await_report for the final result.\" };\n },\n },\n {\n name: \"get_status\",\n description:\n \"Snapshot of your latest call: live status straight from Vapi plus the recent event feed. Does not consume listen's cursor. Includes a watch_url where you can see the live transcript.\",\n inputSchema: { type: \"object\", properties: {} },\n run: async (_args: Record, ctx: Ctx) => {\n const { vapiKey, tenant } = creds(ctx);\n const call = await db.latestCall(tenant);\n if (!call) return { note: \"No calls yet.\", watch_url: `${ctx.origin}/?t=${tenant}` };\n let live: Record | null = null;\n try {\n live = await getCallLive(vapiKey, call.id);\n if (live?.status && live.status !== call.status) {\n await db.setCallStatus(call.id, String(live.status), (live.endedReason as string) ?? null);\n }\n } catch (e) {\n live = { error: String(e) };\n }\n const events = await db.recentEvents(call.id, 15);\n return {\n call_id: call.id,\n number: call.number,\n db_status: call.status,\n vapi_status: live?.status ?? null,\n ended_reason: live?.endedReason ?? call.ended_reason ?? null,\n started_at: call.created_at,\n watch_url: `${ctx.origin}/?t=${tenant}`,\n recent_events: events.map(fmt),\n };\n },\n },\n {\n name: \"end_call\",\n description: \"Hang up the live call immediately (e.g. to abort a dispatched call). The agent normally ends calls itself.\",\n inputSchema: { type: \"object\", properties: {} },\n run: async (_args: Record, ctx: Ctx) => {\n const { tenant } = creds(ctx);\n const call = await requireActiveCall(tenant);\n const r = await endCallOnVapi(call.control_url);\n await db.addEvent(tenant, call.id, \"status\", \"system\", \"end-call requested\");\n return { ok: r.status < 400, vapi_status: r.status };\n },\n },\n];\n\nexport async function runTool(name: string, args: Record, ctx: Ctx) {\n const tool = TOOLS.find((t) => t.name === name);\n if (!tool) throw new Error(`Unknown tool: ${name}`);\n console.log(\"tool:\", name, \"tenant:\", ctx.tenant ?? \"none\", JSON.stringify(args ?? {}).slice(0, 200));\n return await tool.run(args ?? {}, ctx);\n}\n",["D",1781488662285],{"_34":53,"_36":52,"_37":38,"_39":54,"_41":55,"_43":14,"_44":45,"_28":29},"mcp.ts","019ec8ff-b70b-705e-aff8-9df2f2aee4ef","// Minimal remote MCP server: stateless streamable HTTP, plain JSON responses,\n// no SDK. Handles initialize / ping / tools/list / tools/call; notifications get 202.\n\nimport { type Ctx, runTool, TOOLS } from \"./tools.ts\";\n\nconst KNOWN_VERSIONS = [\"2024-11-05\", \"2025-03-26\", \"2025-06-18\"];\n\nconst SERVER_INSTRUCTIONS =\n `dispatch-my-human-escape: dispatch an autonomous voice agent to phone your human and run the call itself — WITH an escape hatch back to you.\nThe agent has a REAL brain and drives the conversation. But when the human asks something outside its brief, it calls for backup and the call PAUSES until YOU answer.\nPrimary loop:\n 1. dispatch_call({ objective, context?, questions?, number?, first_message?, max_minutes? }) — hand off the call.\n 2. await_report({ wait_seconds }) — long-polls. It returns ONE of:\n • needs_answer:true with an { escalation: { question } } — the agent is stuck on an off-brief question. Reply with provide_answer({ text }), then call await_report again.\n • done:true with { summary, objective_met, answers[], followups, transcript } — the call is over.\n 3. provide_answer({ text }) — your answer is fed back to the agent (a \"let me check on that\" plays for the human meanwhile) and it relays it in its own words.\nGive a crisp objective, dump context, and list the questions you want answered. Optional: listen (eavesdrop), say (barge in), get_status, end_call.\nSetup: connection URL needs vapi_key and phone_number_id (and ideally human_number, E.164 with + as %2B) from dashboard.vapi.ai. Brain runs on your Vapi OpenAI model (gpt-4o default; &model= to override).`;\n\nconst rpcResult = (id: unknown, result: unknown) => ({ jsonrpc: \"2.0\", id, result });\nconst rpcError = (id: unknown, code: number, message: string) => ({ jsonrpc: \"2.0\", id, error: { code, message } });\n\nasync function handleOne(msg: any, ctx: Ctx) {\n if (!msg || typeof msg !== \"object\" || typeof msg.method !== \"string\") {\n return rpcError(msg?.id ?? null, -32600, \"invalid request\");\n }\n if (msg.id === undefined) {\n console.log(\"mcp notification:\", msg.method);\n return null; // notifications get no body\n }\n console.log(\"mcp request:\", msg.method, \"tenant:\", ctx.tenant ?? \"none\");\n switch (msg.method) {\n case \"initialize\": {\n const v = msg.params?.protocolVersion;\n return rpcResult(msg.id, {\n protocolVersion: KNOWN_VERSIONS.includes(v) ? v : \"2025-06-18\",\n capabilities: { tools: { listChanged: false } },\n serverInfo: { name: \"dispatch-my-human-escape\", version: \"1.0.0\" },\n instructions: SERVER_INSTRUCTIONS,\n });\n }\n case \"ping\":\n return rpcResult(msg.id, {});\n case \"tools/list\":\n return rpcResult(msg.id, {\n tools: TOOLS.map(({ name, description, inputSchema }) => ({ name, description, inputSchema })),\n });\n case \"tools/call\": {\n try {\n const out = await runTool(msg.params?.name, msg.params?.arguments ?? {}, ctx);\n const text = typeof out === \"string\" ? out : JSON.stringify(out, null, 2);\n return rpcResult(msg.id, { content: [{ type: \"text\", text }], isError: false });\n } catch (e) {\n return rpcResult(msg.id, { content: [{ type: \"text\", text: String(e) }], isError: true });\n }\n }\n default:\n return rpcError(msg.id, -32601, `method not found: ${msg.method}`);\n }\n}\n\nexport async function handleMcp(req: Request, ctx: Ctx): Promise {\n if (req.method !== \"POST\") {\n return new Response(\"call-my-human: POST JSON-RPC here (stateless streamable HTTP MCP). GET / for setup.\", {\n status: 405,\n });\n }\n let body: unknown;\n try {\n body = await req.json();\n } catch {\n return Response.json(rpcError(null, -32700, \"parse error\"), { status: 400 });\n }\n const msgs = Array.isArray(body) ? body : [body];\n const replies: unknown[] = [];\n for (const m of msgs) {\n const r = await handleOne(m, ctx);\n if (r) replies.push(r);\n }\n if (!replies.length) return new Response(null, { status: 202 });\n return Response.json(Array.isArray(body) ? replies : replies[0]);\n}\n",["D",1781488662285],{"_34":58,"_36":57,"_37":59,"_39":60,"_41":61,"_43":14,"_44":45,"_28":29},"main.ts","019ec8ff-b70b-705e-aff8-99553a016c64","http","// dispatch-my-human — a PUBLIC remote MCP server that dispatches an autonomous\n// voice agent to phone your human, handle the conversation itself, and report back.\n// Unlike the puppet sibling (call-my-human), the Vapi agent here has a REAL brain:\n// it runs the whole call in-stack (low latency, no per-turn round-trip), then Vapi's\n// post-call analysis returns a structured report.\n// BYOK: connecting users pass their own Vapi creds in the connection URL.\n// No env vars, no server-side keys, no signup.\n//\n// /mcp?vapi_key=…&phone_number_id=…&human_number=%2B1555… ← connect here\n// /api/call/:action same tools as REST (dispatch, report, listen, say, status, end)\n// /webhook/:tenant Vapi server events → SQLite (transcripts + end-of-call analysis)\n// / plain GET = setup instructions; /?t= = live transcript feed\n//\n// A tenant is a short hash of the caller's Vapi key — it scopes call state per user\n// and routes Vapi's webhooks back to the right feed. Keys are never stored.\n\nimport { Hono } from \"npm:hono\";\nimport * as db from \"./db.ts\";\nimport { handleMcp } from \"./mcp.ts\";\nimport { type Ctx, runTool } from \"./tools.ts\";\n\nconst app = new Hono();\napp.onError((err) => Promise.reject(err));\n\nasync function tenantOf(key: string): Promise {\n const d = await crypto.subtle.digest(\"SHA-256\", new TextEncoder().encode(key));\n return [...new Uint8Array(d)].slice(0, 6).map((b) => b.toString(16).padStart(2, \"0\")).join(\"\");\n}\n\nasync function buildCtx(c: any): Promise {\n const q = (k: string) => c.req.query(k) || null;\n const bearer = (c.req.header(\"authorization\") ?? \"\").replace(/^Bearer\\s+/i, \"\") || null;\n const vapiKey = q(\"vapi_key\") ?? bearer;\n return {\n origin: new URL(c.req.url).origin,\n vapiKey,\n phoneNumberId: q(\"phone_number_id\"),\n humanNumber: q(\"human_number\"),\n model: q(\"model\") || \"gpt-4o\", // the agent's brain; override with &model= in the URL\n tenant: vapiKey ? await tenantOf(vapiKey) : null,\n };\n}\n\n// ---------- remote MCP ----------\napp.all(\"/mcp\", async (c) => handleMcp(c.req.raw, await buildCtx(c)));\n\n// ---------- REST mirror of the tools ----------\nconst REST: Record = {\n dispatch: \"dispatch_call\",\n report: \"await_report\",\n answer: \"provide_answer\",\n listen: \"listen\",\n say: \"say\",\n status: \"get_status\",\n end: \"end_call\",\n};\n\napp.all(\"/api/call/:action\", async (c) => {\n const tool = REST[c.req.param(\"action\")];\n if (!tool) return c.json({ error: \"unknown action — use dispatch | report | answer | listen | say | status | end\" }, 404);\n let args: Record = {};\n if (c.req.method === \"POST\") {\n try {\n args = await c.req.json();\n } catch { /* empty body is fine */ }\n }\n try {\n return c.json({ ok: true, result: await runTool(tool, args, await buildCtx(c)) });\n } catch (e) {\n return c.json({ ok: false, error: String(e) }, 400);\n }\n});\n\n// state for the live feed page (tenant id is required — it is unguessable without the key)\napp.get(\"/api/state\", async (c) => {\n const t = c.req.query(\"t\");\n if (!t) return c.json({ error: \"pass ?t= (shown in start_call/get_status results)\" }, 400);\n const call = await db.latestCall(t);\n if (!call) return c.json({ call: null, events: [] });\n const events = await db.recentEvents(call.id, 120);\n return c.json({ call, events });\n});\n\n// ---------- Vapi webhook (per tenant) ----------\napp.post(\"/webhook/:tenant\", async (c) => {\n const tenant = c.req.param(\"tenant\");\n if ((c.req.header(\"x-vapi-secret\") ?? \"\") !== tenant) {\n console.log(\"webhook: bad or missing x-vapi-secret for tenant\", tenant);\n return c.json({ error: \"bad secret\" }, 401);\n }\n const payload = await c.req.json().catch(() => ({}));\n const m = payload?.message ?? {};\n const callId: string = m?.call?.id ?? (await db.latestCall(tenant))?.id ?? \"unknown\";\n console.log(\"webhook:\", tenant, m.type, m.status ?? m.transcriptType ?? \"\", String(m.transcript ?? \"\").slice(0, 120));\n\n const mtype = String(m.type ?? \"\");\n if (mtype.startsWith(\"transcript\")) {\n // type is \"transcript\" or the documented variant 'transcript[transcriptType=\"final\"]'\n const ttype = m.transcriptType ?? (mtype.includes(\"final\") ? \"final\" : \"partial\");\n if (ttype === \"final\") {\n await db.addEvent(tenant, callId, \"transcript\", m.role ?? \"user\", m.transcript ?? \"\");\n await db.setPartial(callId, null);\n } else {\n await db.setPartial(callId, (m.role ?? \"?\") + \": \" + (m.transcript ?? \"\"));\n }\n } else if (mtype === \"conversation-update\") {\n // Fallback transcript source: backfill any user lines the transcript events missed.\n const conv = (m.conversation ?? m.messages ?? []) as Array>;\n const users = conv\n .filter((x) => x.role === \"user\")\n .map((x) => String(x.message ?? x.content ?? \"\"))\n .filter(Boolean);\n if (users.length) {\n const seen = new Set(\n (await db.recentEvents(callId, 80))\n .filter((e) => e.type === \"transcript\" && e.role === \"user\")\n .map((e) => e.content),\n );\n for (const u of users) {\n if (!seen.has(u)) {\n await db.addEvent(tenant, callId, \"transcript\", \"user\", u);\n seen.add(u);\n }\n }\n }\n } else if (mtype === \"status-update\") {\n await db.setCallStatus(callId, m.status ?? \"unknown\", m.endedReason ?? null);\n await db.addEvent(tenant, callId, \"status\", \"system\", String(m.status) + (m.endedReason ? \" (\" + m.endedReason + \")\" : \"\"));\n } else if (mtype === \"end-of-call-report\") {\n // Analysis (summary + structuredData) is computed at end-of-call and rides\n // along in this report. await_report waits for the \"analysis\" event below.\n await db.setCallStatus(callId, \"ended\", m.endedReason ?? null);\n const analysis = m?.analysis ?? {};\n const summary = analysis.summary ?? m.summary ?? \"call ended\";\n await db.addEvent(tenant, callId, \"report\", \"system\", String(summary).slice(0, 1000));\n if (analysis.structuredData !== undefined && analysis.structuredData !== null) {\n await db.addEvent(tenant, callId, \"analysis\", \"system\", JSON.stringify(analysis.structuredData));\n }\n }\n return c.json({});\n});\n\n// ---------- escape hatch: blocking tool endpoint (per tenant) ----------\n// The agent calls ask_operator; Vapi POSTs here and waits up to the tool's\n// server timeout. We record the question, then block until the operator answers\n// via provide_answer (or we time out), and return the answer as the tool result.\napp.post(\"/tool/:tenant\", async (c) => {\n const tenant = c.req.param(\"tenant\");\n const secret = c.req.header(\"x-vapi-secret\") ?? \"\";\n if (secret && secret !== tenant) {\n console.log(\"tool: bad x-vapi-secret for tenant\", tenant);\n return c.json({ error: \"bad secret\" }, 401);\n }\n const payload = await c.req.json().catch(() => ({}));\n const m = payload?.message ?? {};\n const tc = (m.toolCallList ?? [])[0] ?? {};\n const toolCallId: string = tc.id ?? tc.toolCall?.id ?? \"unknown\";\n // Vapi may send arguments as an object OR a JSON string, and under .arguments\n // or .function.arguments depending on shape — handle all of them.\n let rawArgs: unknown = tc.arguments ?? tc.function?.arguments ?? tc.toolCall?.function?.arguments ?? {};\n if (typeof rawArgs === \"string\") {\n try { rawArgs = JSON.parse(rawArgs); } catch { rawArgs = {}; }\n }\n const a = (rawArgs ?? {}) as Record;\n const question = String(a.question ?? a.q ?? \"\").trim() || \"(the agent asked for help but gave no question)\";\n const callId: string = m?.call?.id ?? (await db.latestCall(tenant))?.id ?? \"unknown\";\n console.log(\"tool ask_operator:\", tenant, toolCallId, question.slice(0, 160));\n\n const escId = await db.insertEscalation(tenant, callId, toolCallId, question);\n await db.addEvent(tenant, callId, \"escalation\", \"system\", question);\n\n // Block until the operator answers (provide_answer) — stay under the tool's 45s timeout.\n const deadline = Date.now() + 42_000;\n while (Date.now() < deadline) {\n const esc = await db.getEscalation(escId);\n if (esc?.answer != null) {\n await db.addEvent(tenant, callId, \"answer\", \"assistant\", esc.answer);\n return c.json({ results: [{ toolCallId, result: esc.answer }] });\n }\n await new Promise((r) => setTimeout(r, 700));\n }\n // No operator answer in time — clear the pending flag and hand the agent a graceful line.\n await db.answerEscalation(escId, \"(timed out — operator did not answer in time)\");\n await db.addEvent(tenant, callId, \"escalation\", \"system\", \"(no operator answer in time — agent moved on)\");\n return c.json({\n results: [{\n toolCallId,\n result: \"I couldn't reach my operator on that just now — let's keep going and I'll have them follow up.\",\n }],\n });\n});\n\n// ---------- landing + live feed ----------\nfunction landing(origin: string): string {\n return `dispatch-my-human — send an agent to phone your human (public remote MCP server)\n\nDispatch an autonomous voice agent to call your human, run the whole\nconversation itself, and hand you back a structured report. You brief it once\n(objective + context + questions); it talks, hangs up, and you collect the\nresult. The agent has a real LLM brain running in-stack, so the call is\nlow-latency and natural — you don't drive it turn by turn.\n\nTools: dispatch_call · await_report · listen · say · get_status · end_call.\nThe headline loop is just dispatch_call → await_report. listen/say are optional\nsupervisor hooks (eavesdrop on, or barge into, a live call).\n\nBring your own keys from https://dashboard.vapi.ai (private key + phone number ID).\nThe agent's brain uses your Vapi account's bundled OpenAI model (gpt-4o by\ndefault; override with &model=). No extra LLM key needed for OpenAI models.\n\nConnect from Claude Code:\n\n claude mcp add --transport http dispatch-my-human \\\\\n \"${origin}/mcp?vapi_key=YOUR_KEY&phone_number_id=YOUR_PHONE_ID&human_number=%2B15551234567\"\n\nNo MCP client? The tools speak plain REST with the same query params:\n POST ${origin}/api/call/dispatch {\"objective\": \"...\", \"context\": \"...\", \"questions\": [\"...\"]}\n POST ${origin}/api/call/report {\"wait_seconds\": 25} (long-polls; use a 35s timeout, repeat until done:true)\n POST ${origin}/api/call/listen {\"wait_seconds\": 25} (optional: eavesdrop live)\n POST ${origin}/api/call/say {\"text\": \"...\", \"end_call_after\": false} (optional: barge in)\n POST ${origin}/api/call/status · POST ${origin}/api/call/end\n\nNotes:\n • human_number is the default number dispatch_call dials — your cell. The +\n MUST be URL-encoded as %2B.\n • Works in any MCP client that takes a URL (claude.ai custom connectors too).\n • Watch a call live: dispatch_call returns a watch_url.\n • Free Vapi numbers are flaky (occasional dead bridges, a DAILY outbound\n limit). Import a Twilio number into Vapi for reliability.\n • Privacy: your key is read per-request and never stored. Call transcripts\n and reports ARE stored in this val's SQLite, scoped to a hash of your key.\n Want full custody? Remix this val — it has no other config.\n\nSibling: dcm31/call-my-human is the puppet version (you drive every word).\nSource + README: https://www.val.town/x/dcm31/dispatch-my-human\n`;\n}\n\nconst PAGE = `\n\n\ndispatch-my-human — live\n\n\n

📞 dispatch-my-human no call

\n\n`;\n\napp.get(\"/\", (c) => {\n if (c.req.query(\"t\")) return c.html(PAGE);\n return c.text(landing(new URL(c.req.url).origin));\n});\n\nexport default app.fetch;\n",["D",1781488662285],{"_34":64,"_36":63,"_37":38,"_39":65,"_41":66,"_43":14,"_44":45,"_28":29},"db.ts","019ec8ff-b70b-705e-aff8-9775ffb4795b","// SQLite layer: calls + an append-only event feed per call, scoped by tenant.\n// A tenant is a short hash of the caller's Vapi key — every connecting user\n// gets their own call history on this shared public server.\n\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nawait sqlite.batch([\n `CREATE TABLE IF NOT EXISTS calls (\n id TEXT PRIMARY KEY,\n tenant TEXT,\n control_url TEXT,\n status TEXT DEFAULT 'starting',\n ended_reason TEXT,\n live_partial TEXT,\n cursor INTEGER DEFAULT 0,\n number TEXT,\n created_at TEXT\n )`,\n `CREATE TABLE IF NOT EXISTS events (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n tenant TEXT,\n call_id TEXT,\n type TEXT,\n role TEXT,\n content TEXT,\n created_at TEXT\n )`,\n // Escape hatch: a mid-call question the agent routes to the operator. The\n // blocking /tool endpoint inserts a row and waits for `answer` to be filled.\n `CREATE TABLE IF NOT EXISTS escalations (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n tenant TEXT,\n call_id TEXT,\n tool_call_id TEXT,\n question TEXT,\n answer TEXT,\n created_at TEXT,\n answered_at TEXT\n )`,\n]);\n// Remixed schema may predate the tenant column — add it if missing.\ntry {\n await sqlite.execute(`ALTER TABLE calls ADD COLUMN tenant TEXT`);\n} catch { /* already there */ }\ntry {\n await sqlite.execute(`ALTER TABLE events ADD COLUMN tenant TEXT`);\n} catch { /* already there */ }\n\nconst now = () => new Date().toISOString();\n\nexport interface CallRow {\n id: string;\n tenant: string;\n control_url: string;\n status: string;\n ended_reason: string | null;\n live_partial: string | null;\n cursor: number;\n number: string;\n created_at: string;\n}\n\nexport interface EventRow {\n id: number;\n tenant: string;\n call_id: string;\n type: string;\n role: string;\n content: string;\n created_at: string;\n}\n\nexport async function insertCall(tenant: string, id: string, controlUrl: string, number: string) {\n await sqlite.execute({\n sql: `INSERT INTO calls (id, tenant, control_url, status, cursor, number, created_at)\n VALUES (?, ?, ?, 'starting', 0, ?, ?)`,\n args: [id, tenant, controlUrl, number, now()],\n });\n}\n\nexport async function latestCall(tenant: string): Promise {\n const r = await sqlite.execute({\n sql: `SELECT * FROM calls WHERE tenant = ? ORDER BY created_at DESC LIMIT 1`,\n args: [tenant],\n });\n return (r.rows[0] as unknown as CallRow) ?? null;\n}\n\nexport async function getCall(id: string): Promise {\n const r = await sqlite.execute({ sql: `SELECT * FROM calls WHERE id = ?`, args: [id] });\n return (r.rows[0] as unknown as CallRow) ?? null;\n}\n\nexport async function setCallStatus(id: string, status: string, endedReason?: string | null) {\n await sqlite.execute({\n sql: `UPDATE calls SET status = ?, ended_reason = COALESCE(?, ended_reason) WHERE id = ?`,\n args: [status, endedReason ?? null, id],\n });\n}\n\nexport async function setPartial(id: string, partial: string | null) {\n await sqlite.execute({ sql: `UPDATE calls SET live_partial = ? WHERE id = ?`, args: [partial, id] });\n}\n\nexport async function setCursor(id: string, cursor: number) {\n await sqlite.execute({ sql: `UPDATE calls SET cursor = ? WHERE id = ?`, args: [cursor, id] });\n}\n\nexport async function addEvent(tenant: string, callId: string, type: string, role: string, content: string) {\n await sqlite.execute({\n sql: `INSERT INTO events (tenant, call_id, type, role, content, created_at) VALUES (?, ?, ?, ?, ?, ?)`,\n args: [tenant, callId, type, role, content, now()],\n });\n}\n\nexport async function eventsAfter(callId: string, afterId: number): Promise {\n const r = await sqlite.execute({\n sql: `SELECT * FROM events WHERE call_id = ? AND id > ? ORDER BY id ASC`,\n args: [callId, afterId],\n });\n return r.rows as unknown as EventRow[];\n}\n\nexport async function hasTranscript(callId: string): Promise {\n const r = await sqlite.execute({\n sql: `SELECT 1 FROM events WHERE call_id = ? AND type = 'transcript' LIMIT 1`,\n args: [callId],\n });\n return r.rows.length > 0;\n}\n\nexport async function latestEventOfType(callId: string, type: string): Promise {\n const r = await sqlite.execute({\n sql: `SELECT * FROM events WHERE call_id = ? AND type = ? ORDER BY id DESC LIMIT 1`,\n args: [callId, type],\n });\n return (r.rows[0] as unknown as EventRow) ?? null;\n}\n\nexport async function transcriptLines(callId: string, limit = 200): Promise {\n const r = await sqlite.execute({\n sql: `SELECT * FROM events WHERE call_id = ? AND type = 'transcript' ORDER BY id ASC LIMIT ?`,\n args: [callId, limit],\n });\n return r.rows as unknown as EventRow[];\n}\n\nexport async function recentEvents(callId: string, limit = 100): Promise {\n const r = await sqlite.execute({\n sql: `SELECT * FROM events WHERE call_id = ? ORDER BY id DESC LIMIT ?`,\n args: [callId, limit],\n });\n return (r.rows as unknown as EventRow[]).reverse();\n}\n\n// ---------- escalations (the escape hatch) ----------\n\nexport interface EscalationRow {\n id: number;\n tenant: string;\n call_id: string;\n tool_call_id: string;\n question: string;\n answer: string | null;\n created_at: string;\n answered_at: string | null;\n}\n\nexport async function insertEscalation(\n tenant: string,\n callId: string,\n toolCallId: string,\n question: string,\n): Promise {\n const r = await sqlite.execute({\n sql: `INSERT INTO escalations (tenant, call_id, tool_call_id, question, created_at)\n VALUES (?, ?, ?, ?, ?) RETURNING id`,\n args: [tenant, callId, toolCallId, question, now()],\n });\n return Number((r.rows[0] as unknown as { id: number }).id);\n}\n\nexport async function getEscalation(id: number): Promise {\n const r = await sqlite.execute({ sql: `SELECT * FROM escalations WHERE id = ?`, args: [id] });\n return (r.rows[0] as unknown as EscalationRow) ?? null;\n}\n\n// The oldest still-unanswered question for this tenant (FIFO).\nexport async function pendingEscalation(tenant: string): Promise {\n const r = await sqlite.execute({\n sql: `SELECT * FROM escalations WHERE tenant = ? AND answer IS NULL ORDER BY id ASC LIMIT 1`,\n args: [tenant],\n });\n return (r.rows[0] as unknown as EscalationRow) ?? null;\n}\n\nexport async function answerEscalation(id: number, answer: string) {\n await sqlite.execute({\n sql: `UPDATE escalations SET answer = ?, answered_at = ? WHERE id = ? AND answer IS NULL`,\n args: [answer, now(), id],\n });\n}\n",["D",1781488662285],{"_34":69,"_36":68,"_37":25,"_39":70,"_41":71,"_43":14,"_44":45,"_28":29},"README.md","019ec8ff-b70b-705e-aff8-93d0bee43f4e","# dispatch-my-human — send an agent to phone your human 📞\n\nA **public remote MCP server**: connect it to any AI agent and it can dispatch an *autonomous* voice agent to phone your human, **run the whole conversation itself**, hang up, and hand back a structured report. The sibling [dcm31/call-my-human](https://www.val.town/x/dcm31/call-my-human) is a *puppet* — you drive every word over a dumb pipe, which is high-latency. This one un-lobotomizes the agent: it has a real LLM brain running **inside Vapi's stack**, so there's no per-turn round-trip back to your reasoning loop. Same BYOK design: **no env vars, no server-side keys, no signup**.\n\n```\nyour agent (any MCP client)\n │ dispatch_call({ objective, context, questions }) ← brief it ONCE\n ▼\nthis val ──── POST api.vapi.ai/call (your key) ────▶ Vapi ─── gpt-4o brain ──▶ 📱 you\n ▲ │ │ (runs the call itself,\n │ │ │ ends it with endCall)\n │ └── await_report ◀── end-of-call analysis ──────┘\n └── /webhook/ ◀── transcripts + structured report ──┘\n```\n\nThe agent carries the call: it opens, stays on objective, gets your answers, and uses Vapi's `endCall` tool to hang up. When it ends, Vapi's **analysis plan** auto-extracts a summary + an answer to each question you asked + any follow-ups, and `await_report` returns it.\n\n## The loop\n\nJust two tools for the common case:\n\n1. **`dispatch_call`** `{ objective, context?, questions?, number?, first_message?, caller_identity?, max_minutes? }` — hand off the call.\n2. **`await_report`** `{ wait_seconds }` — long-polls; keep calling it until `done:true`. Returns `{ summary, objective_met, answers[], followups, transcript }`.\n\nOptional supervisor hooks (you usually won't need them):\n\n- **`listen`** — eavesdrop on the live call in realtime.\n- **`say`** — barge in with a verbatim line (e.g. correct the agent or feed it a fact).\n- **`get_status`**, **`end_call`** — snapshot / abort.\n\n## Connect\n\nYou need two values from [dashboard.vapi.ai](https://dashboard.vapi.ai): your **private key** and a **phone number ID** (free Vapi numbers work, US-only).\n\n```sh\nclaude mcp add --transport http dispatch-my-human \\\n \"https://dcm31--019ec8902328734fa4beeb375dc81ac4.web.val.run/mcp?vapi_key=YOUR_KEY&phone_number_id=YOUR_PHONE_ID&human_number=%2B15551234567\"\n```\n\n- `human_number` = your cell, the default callee. **The `+` must be URL-encoded as `%2B`.**\n- The brain runs on your Vapi account's bundled **OpenAI** model (`gpt-4o` default). No extra LLM key needed for OpenAI models. Override with `&model=gpt-4o-mini` (faster) or any Vapi-supported model.\n- Any MCP client that takes a URL works (claude.ai custom connectors included). `Authorization: Bearer ` is accepted in place of the `vapi_key` param.\n- Then tell your agent: *\"if you get stuck, dispatch a call to me and ask.\"*\n\n## Example\n\n> Agent: `dispatch_call({ objective: \"Decide whether to ship the v2 release tonight\", context: \"QA found one minor cosmetic bug, nothing functional. The marketing email is scheduled for 8am.\", questions: [\"Ship tonight or hold for the fix?\", \"If we hold, what's the new target?\"], caller_identity: \"Charlie's AI assistant\" })`\n>\n> …agent calls, talks it through, hangs up…\n>\n> Agent: `await_report({})` → `{ objective_met: true, answers: [{question:\"Ship tonight or hold for the fix?\", answer:\"Ship tonight\"}, {question:\"If we hold, what's the new target?\", answer:\"N/A — shipping\"}], summary: \"...\", followups: \"Wants a Slack ping once it's live.\" }`\n\n## Watching a call live\n\n`dispatch_call` and `get_status` return a `watch_url` (`/?t=`) — a self-refreshing feed of statuses, both-sides transcript, and the final structured report.\n\n## Testing with curl\n\n```sh\nBASE=\"https://dcm31--019ec8902328734fa4beeb375dc81ac4.web.val.run\"\nQ=\"vapi_key=YOUR_KEY&phone_number_id=YOUR_PHONE_ID&human_number=%2B15551234567\"\ncurl -X POST \"$BASE/api/call/dispatch?$Q\" -d '{\"objective\":\"Confirm Friday dinner\",\"questions\":[\"Still on for Friday?\",\"What time?\"]}'\ncurl -X POST \"$BASE/api/call/report?$Q\" -d '{\"wait_seconds\":25}' --max-time 35 # repeat until done:true\n```\n\n## Files\n\n- `main.ts` — routes, per-tenant Vapi webhook (transcripts + end-of-call analysis), landing + live feed\n- `tools.ts` — the tools, shared by MCP and REST; builds the agent's system prompt from your brief\n- `vapi.ts` — Vapi REST client: native-model call creation with the `endCall` tool + structured-data analysis plan\n- `mcp.ts` — minimal stateless streamable-HTTP MCP plumbing (no SDK)\n- `db.ts` — SQLite: tenant-scoped `calls` + append-only `events` (transcripts, report, structured analysis)\n\n## Multi-tenancy & privacy\n\n- Your Vapi key is read per-request and **never stored**. It travels TLS-encrypted to this val and on to Vapi, like any BYOK MCP server.\n- Call state, transcripts, and reports **are stored** in this val's SQLite, scoped by a `tenant` = first 12 hex chars of SHA-256(your key) — unguessable without the key, and it's how Vapi's webhooks find their way back (`/webhook/`, verified via `x-vapi-secret`).\n- Want full custody? **Remix this val** — it needs zero configuration.\n\n## Notes\n\n- The agent ends calls itself via Vapi's `endCall` tool once the objective is met; `max_minutes` (default 10) is a hard cap. 30s of mutual silence also ends it.\n- Latency is set by Vapi's STT→LLM→TTS pipeline (~1-2s/turn), not your agent's reasoning loop — that's the whole point vs. the puppet.\n- Post-call analysis (summary + structured data) completes a few seconds *after* the call ends, so `await_report` may return `done:false` once right at hangup — just call it again.\n- Free Vapi numbers are test-grade (occasional dead bridges, a daily outbound limit). Import a Twilio number into Vapi for reliability.\n- Only call numbers you have consent to call — automated calls without consent violate TCPA/FCC rules.\n",["D",1781488662285],"id","f8ce04b7-1471-4c48-8b9d-3105b5ad1b75","dispatch-my-human-escape",["D",1781486817181],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","Public remote MCP: your agent phones you. 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