Creación de planes y asignaturas en segundo plano y con webhook de openai #40
@@ -21,6 +21,7 @@
|
||||
"jsr:@zod/zod@^4.3.5": "4.3.5",
|
||||
"npm:@supabase/supabase-js@2": "2.90.1",
|
||||
"npm:@supabase/supabase-js@^2.90.1": "2.90.1",
|
||||
"npm:@toon-format/toon@^2.1.0": "2.1.0",
|
||||
"npm:@types/bun@^1.3.5": "1.3.5",
|
||||
"npm:deno@^2.6.4": "2.6.4",
|
||||
"npm:openai@6.16.0": "6.16.0_zod@3.25.76",
|
||||
@@ -186,6 +187,9 @@
|
||||
"@supabase/storage-js"
|
||||
]
|
||||
},
|
||||
"@toon-format/toon@2.1.0": {
|
||||
"integrity": "sha512-JwWptdF5eOA0HaQxbKAzkpQtR4wSWTEfDlEy/y3/4okmOAX1qwnpLZMmtEWr+ncAhTTY1raCKH0kteHhSXnQqg=="
|
||||
},
|
||||
"@types/bun@1.3.5": {
|
||||
"integrity": "sha512-RnygCqNrd3srIPEWBd5LFeUYG7plCoH2Yw9WaZGyNmdTEei+gWaHqydbaIRkIkcbXwhBT94q78QljxN0Sk838w==",
|
||||
"dependencies": [
|
||||
@@ -519,8 +523,7 @@
|
||||
"minipass",
|
||||
"minizlib",
|
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"yallist"
|
||||
],
|
||||
"deprecated": true
|
||||
]
|
||||
},
|
||||
"tr46@0.0.3": {
|
||||
"integrity": "sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw=="
|
||||
@@ -591,6 +594,7 @@
|
||||
"packageJson": {
|
||||
"dependencies": [
|
||||
"npm:@supabase/supabase-js@^2.90.1",
|
||||
"npm:@toon-format/toon@^2.1.0",
|
||||
"npm:@types/bun@^1.3.5",
|
||||
"npm:deno@^2.6.4",
|
||||
"npm:openai@^6.16.0",
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||||
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+559
-557
File diff suppressed because it is too large
Load Diff
@@ -83,11 +83,13 @@
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||||
},
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||||
{
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||||
"cell_type": "code",
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||||
"execution_count": 26,
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||||
"execution_count": null,
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||||
"id": "1403c789",
|
||||
"metadata": {},
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||||
"outputs": [],
|
||||
"source": [
|
||||
"import { title } from \"node:process\";\n",
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||||
"\n",
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||||
"const combinedSchema = {\n",
|
||||
" type: \"object\",\n",
|
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" $defs: {\n",
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@@ -126,10 +128,12 @@
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" fabricante: { type: \"string\", maxLength: 100 },\n",
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"\n",
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" // Agregar campo del preset\n",
|
||||
" perishables: { $ref: \"#/$defs/perishables\" },\n",
|
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" origen: { $ref: \"#/$defs/origen\" },\n",
|
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" perishables: {\n",
|
||||
" $ref: \"#/$defs/perishables\",\n",
|
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" \"x-column\": \"perishables\",\n",
|
||||
" },\n",
|
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"\n",
|
||||
" perecedero: { type: \"null\", \"x-column\": \"perishable\", const: null },\n",
|
||||
" origen: { $ref: \"#/$defs/origen\" },\n",
|
||||
" },\n",
|
||||
" required: [\"nombre\", \"fabricante\", \"perishables\", \"origen\", \"perecedero\"],\n",
|
||||
" additionalProperties: false,\n",
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
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||||
"execution_count": 3,
|
||||
"execution_count": 2,
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||||
"id": "902bff53",
|
||||
"metadata": {},
|
||||
"outputs": [],
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||||
@@ -19,7 +19,7 @@
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},
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{
|
||||
"cell_type": "code",
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"execution_count": 4,
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"execution_count": 3,
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"id": "3b0acbc3",
|
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"metadata": {},
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"outputs": [],
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@@ -32,63 +32,18 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
|
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"execution_count": 1,
|
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"id": "dae842ad",
|
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"metadata": {},
|
||||
"outputs": [
|
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{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{\n",
|
||||
" object: \"list\",\n",
|
||||
" data: [\n",
|
||||
" {\n",
|
||||
" object: \"embedding\",\n",
|
||||
" index: 0,\n",
|
||||
" embedding: [\n",
|
||||
" 0.017360063269734383, 0.022553985938429832, 0.025286488234996796,\n",
|
||||
" -0.009742671623826027, -0.016438385471701622, -0.014725150540471077,\n",
|
||||
" -0.020840751007199287, 0.02215278521180153, -0.02024437114596367,\n",
|
||||
" 0.007834257557988167, 0.0029981620609760284, -0.04109596461057663,\n",
|
||||
" 0.030165957286953926, -0.03402615711092949, 0.0008369643473997712,\n",
|
||||
" 0.00044016868923790753, -0.027129843831062317, -0.04248390346765518,\n",
|
||||
" -0.058683738112449646, 0.034655068069696426, 0.013738414272665977,\n",
|
||||
" 0.02060219831764698, 0.016687780618667603, 0.0059637944214046,\n",
|
||||
" -0.010306521318852901, 0.014898642897605896, -0.008826415985822678,\n",
|
||||
" 0.042136918753385544, 0.009477011859416962, -0.03953453525900841,\n",
|
||||
" -0.012198670767247677, -0.040055014193058014, -0.019409440457820892,\n",
|
||||
" -0.0210576169192791, -0.0392959825694561, -0.005996324121952057,\n",
|
||||
" -0.0022486215457320213, 0.05209103599190712, 0.0009325206046923995,\n",
|
||||
" 0.013163721188902855, 0.0505296029150486, 0.014540815725922585,\n",
|
||||
" 0.0027921402361243963, 0.03190087899565697, 0.00004917589103570208,\n",
|
||||
" 0.03209605813026428, -0.038363464176654816, -0.02424553595483303,\n",
|
||||
" 0.014096241444349289, 0.02559009939432144, -0.06089576333761215,\n",
|
||||
" -0.011016755364835262, -0.026696112006902695, 0.050659723579883575,\n",
|
||||
" 0.019561246037483215, 0.050833214074373245, 0.014529972337186337,\n",
|
||||
" -0.023204581812024117, -0.014399852603673935, -0.009292676113545895,\n",
|
||||
" 0.003149967873468995, 0.02007087878882885, 0.025503354147076607,\n",
|
||||
" 0.0230094026774168, 0.04471761733293533, 0.01479020994156599,\n",
|
||||
" -0.06692461669445038, 0.03591288626194, -0.037127330899238586,\n",
|
||||
" 0.029558734968304634, -0.017576929181814194, 0.01953955926001072,\n",
|
||||
" -0.027888871729373932, -0.0041095963679254055, 0.0004940461367368698,\n",
|
||||
" -0.011266149580478668, -0.04200679808855057, 0.03537072241306305,\n",
|
||||
" -0.0015058581484481692, -0.05551750585436821, -0.05287174880504608,\n",
|
||||
" 0.016373327001929283, 0.005573437083512545, -0.01235047634691,\n",
|
||||
" -0.009005329571664333, -0.034047845751047134, -0.018368486315011978,\n",
|
||||
" -0.00271217105910182, 0.007731246296316385, -0.020981714129447937,\n",
|
||||
" -0.040900785475969315, -0.03727913647890091, -0.059030722826719284,\n",
|
||||
" -0.04536821320652962, 0.02257567271590233, 0.08579189330339432,\n",
|
||||
" 0.014605875127017498, -0.030686434358358383, -0.0019084142986685038,\n",
|
||||
" 0.02216362953186035,\n",
|
||||
" ... 1436 more items\n",
|
||||
" ]\n",
|
||||
" }\n",
|
||||
" ],\n",
|
||||
" model: \"text-embedding-3-small\",\n",
|
||||
" usage: { prompt_tokens: 13, total_tokens: 13 }\n",
|
||||
"}\n",
|
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"✅ Insertados textos con embeddings\n"
|
||||
"ename": "ReferenceError",
|
||||
"evalue": "openai is not defined",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"Stack trace:",
|
||||
"ReferenceError: openai is not defined",
|
||||
" at <anonymous>:5:15"
|
||||
]
|
||||
}
|
||||
],
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@@ -120,7 +75,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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||||
"execution_count": 12,
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||||
"id": "2d8fa9a9",
|
||||
"metadata": {},
|
||||
"outputs": [
|
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@@ -129,20 +84,26 @@
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||||
"output_type": "stream",
|
||||
"text": [
|
||||
"🔎 Consulta: ¿Cómo son buscados vectores?\n",
|
||||
"\n",
|
||||
"- Los vectores se usan con el cliente de OPENAI embeddings\n",
|
||||
" Similaridad: 0.5639\n",
|
||||
"\n",
|
||||
"- Supabase permite almacenar vectores usando pgvector.\n",
|
||||
" Similaridad: 0.4758\n",
|
||||
"\n",
|
||||
"- Los embeddings convierten texto en representaciones numéricas.\n",
|
||||
" Similaridad: 0.3645\n",
|
||||
"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"\u001b[32m\"code: PGRST202\\n\"\u001b[39m +\n",
|
||||
" \u001b[32m'details: \"Searched for the function public.buscar_documentos with parameters match_count, query_embedding or with a single unnamed json/jsonb parameter, but no matches were found in the schema cache.\"\\n'\u001b[39m +\n",
|
||||
" \u001b[32m\"hint: Perhaps you meant to call the function public.unaccent\\n\"\u001b[39m +\n",
|
||||
" \u001b[32m'message: \"Could not find the function public.buscar_documentos(match_count, query_embedding) in the schema cache\"'\u001b[39m"
|
||||
]
|
||||
},
|
||||
"execution_count": 12,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import { encode } from \"@toon-format/toon\";\n",
|
||||
"\n",
|
||||
"const consulta = \"¿Cómo son buscados vectores?\";\n",
|
||||
"\n",
|
||||
"const emb = await openai.embeddings.create({\n",
|
||||
@@ -157,22 +118,42 @@
|
||||
" match_count: 3,\n",
|
||||
"});\n",
|
||||
"\n",
|
||||
"if (error) throw error;\n",
|
||||
"/* if (error) throw error; */\n",
|
||||
"\n",
|
||||
"console.log(`🔎 Consulta: ${consulta}\\n`);\n",
|
||||
"for (const r of data ?? []) {\n",
|
||||
" console.log(`- ${r.contenido}`);\n",
|
||||
" console.log(` Similaridad: ${Number(r.similarity).toFixed(4)}\\n`);\n",
|
||||
"}\n"
|
||||
"encode(error, {\n",
|
||||
" indent: 2,\n",
|
||||
" delimiter: \",\",\n",
|
||||
" keyFolding: \"off\",\n",
|
||||
" flattenDepth: Infinity,\n",
|
||||
"});\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"execution_count": 10,
|
||||
"id": "791a94d8",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{\n",
|
||||
" code: \u001b[32m\"PGRST202\"\u001b[39m,\n",
|
||||
" details: \u001b[32m\"Searched for the function public.buscar_documentos with parameters match_count, query_embedding or with a single unnamed json/jsonb parameter, but no matches were found in the schema cache.\"\u001b[39m,\n",
|
||||
" hint: \u001b[32m\"Perhaps you meant to call the function public.unaccent\"\u001b[39m,\n",
|
||||
" message: \u001b[32m\"Could not find the function public.buscar_documentos(match_count, query_embedding) in the schema cache\"\u001b[39m\n",
|
||||
"}"
|
||||
]
|
||||
},
|
||||
"execution_count": 10,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"error"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
{
|
||||
"dependencies": {
|
||||
"@supabase/supabase-js": "^2.90.1",
|
||||
"@toon-format/toon": "^2.1.0",
|
||||
"deno": "^2.6.4",
|
||||
"openai": "^6.16.0",
|
||||
"supabase": "^2.72.6"
|
||||
|
||||
@@ -123,81 +123,7 @@ app.post(`${prefix}/conversations`, async (c) => {
|
||||
}
|
||||
});
|
||||
|
||||
/**
|
||||
* GET /conversations/:conversation_plan_id/messages
|
||||
* Lista mensajes (assistant/user) desde OpenAI
|
||||
*/
|
||||
app.get(`${prefix}/conversations/:id/messages`, async (c) => {
|
||||
try {
|
||||
/* const auth = c.req.header("authorization");
|
||||
await requireUser(auth); */
|
||||
|
||||
const conversation_plan_id = c.req.param("id");
|
||||
assertUuid(conversation_plan_id, "conversation_plan_id");
|
||||
|
||||
const supabase = getSupabaseServiceClient();
|
||||
const openai = getOpenAI();
|
||||
|
||||
const { data: convRow, error } = await supabase
|
||||
.from("conversaciones_plan")
|
||||
.select("openai_conversation_id, estado")
|
||||
.eq("id", conversation_plan_id)
|
||||
.single();
|
||||
|
||||
if (error || !convRow) {
|
||||
throw new HttpError(
|
||||
404,
|
||||
"conversation_not_found",
|
||||
"Conversación no encontrada",
|
||||
error,
|
||||
);
|
||||
}
|
||||
if (convRow.estado === "ARCHIVADA") {
|
||||
// si ya está archivada, devolvemos lo guardado
|
||||
const { data: archived } = await supabase
|
||||
.from("conversaciones_plan")
|
||||
.select("conversacion_json")
|
||||
.eq("id", conversation_plan_id)
|
||||
.single();
|
||||
return withCors(
|
||||
jsonResponse({
|
||||
source: "supabase",
|
||||
items: archived?.conversacion_json ?? null,
|
||||
}),
|
||||
);
|
||||
}
|
||||
|
||||
const items = await openai.conversations.items.list(
|
||||
convRow.openai_conversation_id,
|
||||
);
|
||||
|
||||
const conversacion = items.data
|
||||
.filter((it: any) =>
|
||||
it.type === "message" &&
|
||||
(it.role === "assistant" || it.role === "user")
|
||||
)
|
||||
.map((it: any) => {
|
||||
const rawText = it.content.map((c: any) => c.text).join("");
|
||||
|
||||
let parsedContent;
|
||||
|
||||
try {
|
||||
parsedContent = JSON.parse(rawText); // 👈 aquí lo convertimos
|
||||
} catch {
|
||||
parsedContent = rawText; // si no es JSON, lo dejamos normal
|
||||
}
|
||||
|
||||
return {
|
||||
role: it.role,
|
||||
content: parsedContent,
|
||||
};
|
||||
});
|
||||
|
||||
return withCors(jsonResponse({ source: "openai", items: conversacion }));
|
||||
} catch (err) {
|
||||
return withCors(handleErr(err));
|
||||
}
|
||||
});
|
||||
|
||||
/**
|
||||
* POST /conversations/:conversation_plan_id/messages
|
||||
@@ -285,6 +211,11 @@ app.post(`${prefix}/conversations/:id/messages`, async (c) => {
|
||||
"Excelente, actualmente tu plan de estudio tiene una redacción clara, pero podrías mejorar el perfil de ingreso para hacerlo más atractivo.",
|
||||
],
|
||||
},
|
||||
"is_refusal": {
|
||||
type: "boolean",
|
||||
description:
|
||||
"Indica si la respuesta es un refusal (es decir, la pregunta no tiene que ver con el plan de estudio)",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
@@ -295,12 +226,62 @@ app.post(`${prefix}/conversations/:id/messages`, async (c) => {
|
||||
}
|
||||
|
||||
// Pedimos respuesta estructurada con responses.create
|
||||
const schema = pickSchemaFields(definicion, body.campos);
|
||||
const schema = pickSchemaFields(definicion, body.campos ?? []);
|
||||
const planForPrompt = safePlanForPrompt(plan);
|
||||
|
||||
const model = CREATE_CHAT_CONVERSATION_STRUCTURED_MODELO;
|
||||
const prompt = body.user_prompt ?? body.content;
|
||||
|
||||
// append message of the user to conversacion_json (which guarantees a JSONB default to '[]')
|
||||
/**
|
||||
* appended includes timestamp, user, prompt and fields (if any)
|
||||
*/
|
||||
|
||||
type AppendedMessage = {
|
||||
timestamp: string;
|
||||
user: string;
|
||||
prompt: string;
|
||||
fields?: string[];
|
||||
};
|
||||
|
||||
type AppendedResponse = {
|
||||
timestamp: string;
|
||||
user: "assistant";
|
||||
refusal: boolean;
|
||||
message: string;
|
||||
recommendations?: {
|
||||
texto_mejora: string;
|
||||
campo_afectado: string;
|
||||
aplicada: false;
|
||||
};
|
||||
};
|
||||
|
||||
type AppendedItem = AppendedMessage | AppendedResponse;
|
||||
|
||||
let appended: AppendedItem = {
|
||||
timestamp: new Date().toISOString(),
|
||||
user: /* user.email ?? user.id ??*/ "unknown",
|
||||
prompt,
|
||||
fields: body.campos,
|
||||
};
|
||||
|
||||
const { error: appendErr } = await supabase.rpc(
|
||||
"append_conversacion_plan",
|
||||
{
|
||||
p_id: conversation_plan_id,
|
||||
p_append: appended,
|
||||
},
|
||||
);
|
||||
|
||||
if (appendErr) {
|
||||
throw new HttpError(
|
||||
500,
|
||||
"append_conversation_failed",
|
||||
"No se pudo agregar el mensaje a la conversación",
|
||||
appendErr,
|
||||
);
|
||||
}
|
||||
|
||||
const resp = await openai.responses.create({
|
||||
conversation: row.openai_conversation_id,
|
||||
model,
|
||||
@@ -322,6 +303,47 @@ app.post(`${prefix}/conversations/:id/messages`, async (c) => {
|
||||
],
|
||||
});
|
||||
|
||||
const respuestaJSON = JSON.parse(resp.output_text ?? "{}");
|
||||
const refusal = respuestaJSON["is-refusal"] === true;
|
||||
//remove the is-refusal field from respuestaJSON to avoid confusion
|
||||
delete respuestaJSON["is-refusal"];
|
||||
|
||||
// Now an item with the assistant response and the structured data (if any) should be
|
||||
appended = {
|
||||
timestamp: new Date().toISOString(),
|
||||
user: "assistant",
|
||||
refusal,
|
||||
// the ai-message field is the response
|
||||
message: respuestaJSON?.["ai-message"] ?? "",
|
||||
recommendations: resp.output_text
|
||||
? Object.entries(respuestaJSON).filter(([k]) => k !== "ai-message")
|
||||
.map(
|
||||
([campo_afectado, texto_mejora]) => ({
|
||||
campo_afectado,
|
||||
texto_mejora,
|
||||
aplicada: false,
|
||||
}),
|
||||
)
|
||||
: undefined,
|
||||
} as AppendedResponse;
|
||||
|
||||
const { error: appendRespErr } = await supabase.rpc(
|
||||
"append_conversacion_plan",
|
||||
{
|
||||
p_id: conversation_plan_id,
|
||||
p_append: appended,
|
||||
},
|
||||
);
|
||||
|
||||
if (appendRespErr) {
|
||||
throw new HttpError(
|
||||
500,
|
||||
"append_response_failed",
|
||||
"No se pudo agregar la respuesta a la conversación",
|
||||
appendRespErr,
|
||||
);
|
||||
}
|
||||
|
||||
return withCors(jsonResponse({
|
||||
ok: true,
|
||||
openai_response_id: resp.id,
|
||||
@@ -332,91 +354,7 @@ app.post(`${prefix}/conversations/:id/messages`, async (c) => {
|
||||
}
|
||||
});
|
||||
|
||||
/**
|
||||
* DELETE /conversations/:conversation_plan_id/archive
|
||||
* Guarda items en Supabase y elimina la conversación de OpenAI
|
||||
*/
|
||||
app.delete(`${prefix}/conversations/:id/archive`, async (c) => {
|
||||
try {
|
||||
/* const auth = c.req.header("authorization");
|
||||
await requireUser(auth); */
|
||||
|
||||
const conversation_plan_id = c.req.param("id");
|
||||
assertUuid(conversation_plan_id, "conversation_plan_id");
|
||||
|
||||
const supabase = getSupabaseServiceClient();
|
||||
const openai = getOpenAI();
|
||||
|
||||
const { data: row, error } = await supabase
|
||||
.from("conversaciones_plan")
|
||||
.select("id, openai_conversation_id, estado")
|
||||
.eq("id", conversation_plan_id)
|
||||
.single();
|
||||
|
||||
if (error || !row) {
|
||||
throw new HttpError(
|
||||
404,
|
||||
"conversation_not_found",
|
||||
"Conversación no encontrada",
|
||||
error,
|
||||
);
|
||||
}
|
||||
|
||||
if (row.estado === "ARCHIVADA") {
|
||||
return withCors(jsonResponse({ ok: true, already: true }));
|
||||
}
|
||||
|
||||
// Marcar estado
|
||||
await supabase.from("conversaciones_plan")
|
||||
.update({ estado: "ARCHIVANDO" })
|
||||
.eq("id", conversation_plan_id);
|
||||
|
||||
// Descargar items de OpenAI
|
||||
const items = await openai.conversations.items.list(
|
||||
row.openai_conversation_id,
|
||||
);
|
||||
|
||||
const conversacion = items.data.filter((it: any) =>
|
||||
it.type === "message" && (it.role === "assistant" || it.role === "user")
|
||||
).map((it: any) => ({
|
||||
role: it.role,
|
||||
content: it.content.map((c: any) => c.text).join(""),
|
||||
}));
|
||||
|
||||
// Guardar y marcar como ARCHIVADA
|
||||
const { error: upErr } = await supabase.from("conversaciones_plan")
|
||||
.update({
|
||||
estado: "ARCHIVADA",
|
||||
conversacion_json: conversacion,
|
||||
})
|
||||
.eq("id", conversation_plan_id);
|
||||
|
||||
if (upErr) {
|
||||
throw new HttpError(
|
||||
500,
|
||||
"archive_save_failed",
|
||||
"No se pudo guardar el archivo en Supabase",
|
||||
upErr,
|
||||
);
|
||||
}
|
||||
|
||||
// Borrar conversación en OpenAI (best effort)
|
||||
try {
|
||||
await openai.conversations.delete(row.openai_conversation_id);
|
||||
} catch (delErr) {
|
||||
// Queda archivada en Supabase, pero reportamos warning
|
||||
return withCors(jsonResponse({
|
||||
ok: true,
|
||||
warning: "Archivada en Supabase, pero no se pudo borrar en OpenAI",
|
||||
details: String(delErr),
|
||||
}, 200));
|
||||
}
|
||||
|
||||
return withCors(jsonResponse({ ok: true }));
|
||||
} catch (err) {
|
||||
return withCors(handleErr(err));
|
||||
}
|
||||
});
|
||||
|
||||
/**
|
||||
* Unknown routes
|
||||
|
||||
@@ -2,7 +2,7 @@ import { HttpError } from "./errors.ts";
|
||||
|
||||
export function pickSchemaFields(
|
||||
definicion: any,
|
||||
campos?: string[],
|
||||
campos: string[],
|
||||
) {
|
||||
if (!definicion || definicion.type !== "object" || !definicion.properties) {
|
||||
return definicion;
|
||||
@@ -18,10 +18,15 @@ export function pickSchemaFields(
|
||||
"Listo: mejoré la redacción del perfil de ingreso y propuse un tema de investigación alineado al plan.",
|
||||
],
|
||||
},
|
||||
"is-refusal": {
|
||||
type: "boolean",
|
||||
description:
|
||||
"Indica si el plan fue rechazado por el modelo. En caso de ser true, se espera un mensaje de rechazo en `ai-message`.",
|
||||
},
|
||||
},
|
||||
};
|
||||
|
||||
let out = structuredClone(definicion);
|
||||
const out = structuredClone(definicion);
|
||||
|
||||
// Si piden campos, filtramos propiedades/required a esos campos
|
||||
const entries = Object.entries(out.properties).filter(([k]) =>
|
||||
|
||||
@@ -1,5 +1,3 @@
|
||||
alter table "public"."conversaciones_plan" add column "nombre" text default ('Chat '::text || CURRENT_DATE);
|
||||
|
||||
alter table "public"."conversaciones_plan" alter column "conversacion_json" set default '[]'::jsonb;
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,21 @@
|
||||
CREATE OR REPLACE FUNCTION public.append_conversacion_asignatura(p_id uuid, p_append jsonb)
|
||||
RETURNS void
|
||||
LANGUAGE sql
|
||||
AS $function$
|
||||
update conversaciones_asignatura
|
||||
set conversacion_json = coalesce(conversacion_json, '[]'::jsonb) || p_append
|
||||
where id = p_id;
|
||||
$function$
|
||||
;
|
||||
|
||||
CREATE OR REPLACE FUNCTION public.append_conversacion_plan(p_id uuid, p_append jsonb)
|
||||
RETURNS void
|
||||
LANGUAGE sql
|
||||
AS $function$
|
||||
update conversaciones_plan
|
||||
set conversacion_json = coalesce(conversacion_json, '[]'::jsonb) || p_append
|
||||
where id = p_id;
|
||||
$function$
|
||||
;
|
||||
|
||||
|
||||
Reference in New Issue
Block a user