Ajustes de estructura
This commit is contained in:
Jordan Diaz
@@ -128,6 +128,17 @@ Cuando creas una tabla con `enlace` (noticias, vacantes, blog), añade por defec
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NO añadas un campo "estado" calculado si ya tienes `visible` + fechas.
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## Schema (.ini.php) — NUNCA editar a mano
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Los `cms/data/schema/*.ini.php` se modifican **exclusivamente** con las tools de schema: `create_table`, `update_table_metadata`, `delete_table`, `reorder_tables`, `create_field`, `update_field`, `delete_field`, `reorder_fields`. NO uses `acai-write` ni `acai-line-replace` sobre estos archivos:
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- Saltarías validaciones (regex, tipos, etc.)
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- No invalidas la cache de schemas — el frontend ve schema viejo
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- No sincronizas con MySQL (no crea/borra columnas reales)
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- Puedes romper el formato INI con un escape mal puesto
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Para subcampos de un `multitext`, llama a `update_field` con `props.descriptionjson` como **string JSON** del array `[{id_campo, nombre_campo, tipo}, ...]`. La tool docu lo explica.
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## Formularios embebidos en detalles
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Si un detalle necesita un formulario (postular, pedir info), embebe el módulo del formulario **dentro** de la sección general pasándole el `num`:
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@@ -1,17 +1,32 @@
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import { z } from "zod";
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import { withAuth, getSessionCredentials } from "../../auth/index.js";
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import { handleApiResponse, handleToolError, validateRequired } from "../helpers/errorHandler.js";
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import { AcaiHttpClient } from "../helpers/acaiHttpClient.js";
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import { withAuth } from "../../auth/index.js";
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import { withAuthParams } from "../helpers/authSchema.js";
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import { handleToolError, validateRequired } from "../helpers/errorHandler.js";
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import { pythonGet } from "../helpers/pythonServerClient.js";
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import { getCurrentProjectInfo } from "../files/helpers.js";
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// get_module_config_vars
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//
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// Pasa por el server Python (/api/creator/get-module-vars) en lugar de ir
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// directamente al PHP. Asi obtenemos `varsMeta`: para cada variable del
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// modulo, su ubicacion fisica en `builder_custom` (recordNum + columna real).
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// Sin esto el agente solo conoce el nombre humano de la variable (ej.
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// `titulo`) y al hacer create_or_update_record adivina el campo y suele
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// fallar silenciosamente porque la columna real es algo como `title2`.
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export function registerGetModuleConfigVarsTool(server) {
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server.tool(
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"get_module_config_vars",
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`Get the current configuration variable values for a module instance on a page record. Returns resolved values (text, HTML, etc.) for simple vars and arrays of objects for multi/repeater vars.
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`Get the current configuration variable values for a module instance on a page record. Returns:
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- vars: resolved values (text, HTML, etc.) for simple vars and arrays for multi/repeater vars
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- varsMeta: per-var physical location { tableName: 'builder_custom', recordNum, fieldName, type }. USE THIS to know exactly which row + column to update with create_or_update_record. The variable's display name (e.g. 'titulo') is NOT the same as the physical column name (e.g. 'title2').
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- uploadFields: per-var upload location for upload_record_image / replace_record_image
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- moduleId, sectionId
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Required params:
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- tableName (string) without 'cms_' prefix
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- recordNum (number) record primary key ('num' field, never 'id')
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- tableName (string) without 'cms_' prefix (parent page table, e.g. 'apartados')
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- recordNum (number) parent record primary key ('num', never 'id')
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- sectionId (string) section ID of the module instance`,
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withAuthParams({
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tableName: z.string().describe("Parent table name (e.g. 'apartados')"),
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@@ -19,44 +34,62 @@ Required params:
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sectionId: z.string().describe("Section ID of the module instance"),
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}),
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{ readOnlyHint: true, destructiveHint: false },
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withAuth(async ({ tableName, recordNum, sectionId }, extra) => {
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withAuth(async ({ tableName, recordNum, sectionId }, _extra) => {
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try {
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const validationError = validateRequired({ tableName, recordNum, sectionId }, ['tableName', 'recordNum', 'sectionId'], 'get_module_config_vars');
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const validationError = validateRequired(
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{ tableName, recordNum, sectionId },
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["tableName", "recordNum", "sectionId"],
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"get_module_config_vars"
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);
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if (validationError) return validationError;
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const sessionId = extra.sessionId;
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const credentials = await getSessionCredentials(sessionId);
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const payload = {
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tableName,
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recordNum,
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sectionId
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const { projectSlug } = getCurrentProjectInfo();
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const result = await pythonGet("/api/creator/get-module-vars", {
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project: projectSlug,
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table: tableName,
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num: recordNum,
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sectionId,
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});
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// El endpoint Python devuelve la respuesta del PHP envuelta:
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// { success, data: { moduleId, vars, configVars, uploadFields, varsMeta, ... } }
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// o directamente las claves en raiz. Normalizamos.
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const inner = result?.data && typeof result.data === "object" ? result.data : result;
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if (!inner || inner.success === false) {
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return {
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content: [{
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type: "text",
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text: JSON.stringify({
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success: false,
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error: inner?.error || "Could not read module config vars",
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}),
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}],
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isError: true,
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};
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const response = await AcaiHttpClient.getModuleConfigVars(
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credentials,
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credentials.token,
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credentials.tokenHash,
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payload
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);
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const apiError = handleApiResponse(response.data, 'get_module_config_vars');
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if (apiError) return apiError;
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}
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return {
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content: [{
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type: "text",
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text: JSON.stringify({
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success: true,
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action: 'get_module_config_vars',
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action: "get_module_config_vars",
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tableName,
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recordNum,
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sectionId,
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data: response.data?.data ?? response.data
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}, null, 2)
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}]
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data: {
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moduleId: inner.moduleId,
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sectionId: inner.sectionId,
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vars: inner.vars || {},
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varsMeta: inner.varsMeta || {},
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uploadFields: inner.uploadFields || {},
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configVars: inner.configVars || {},
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},
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}, null, 2),
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}],
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};
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} catch (error) {
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return handleToolError(error, 'get_module_config_vars', { tableName, recordNum, sectionId });
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return handleToolError(error, "get_module_config_vars", { tableName, recordNum, sectionId });
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}
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})
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);
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@@ -31,7 +31,48 @@ Field types:
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- separator: visual separator in the form (no data column)
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'initialProps' is optional; use it to override defaults (e.g. {isRequired:1, maxLength:100}).
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Table names WITHOUT 'cms_' prefix. Primary key is always 'num'.`,
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Table names WITHOUT 'cms_' prefix. Primary key is always 'num'.
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MULTITEXT FIELDS (type='multitext') — initialProps shape:
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A multitext field is a repeater of N sub-fields per row. Each row in the
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admin form gives the user a set of sub-fields to fill (e.g. a list of FAQ
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items where each one has 'question' + 'answer' + 'category').
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- tablaAuxiliar (string, opcional): nombre de tabla auxiliar para el repeater.
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- descriptionjson (REQUIRED): JSON STRING (not object) with the array of
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sub-fields. Each sub-field is an object with:
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- id_campo (string): clave tecnica, slug. Estable: NO se cambia despues.
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- nombre_campo (string): etiqueta visible en la UI.
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- tipo (string '0'..'5'): '0'=texto, '1'=tabla CMS, '3'=fecha, '4'=color, '5'=icono.
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- When tipo='1': also pass tabla (target table without 'cms_'),
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campo_valor (default 'num'), campo_muestra (label field).
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Example (correct):
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"descriptionjson": "[{\\"id_campo\\":\\"pregunta\\",\\"nombre_campo\\":\\"Pregunta\\",\\"tipo\\":\\"0\\"},{\\"id_campo\\":\\"respuesta\\",\\"nombre_campo\\":\\"Respuesta\\",\\"tipo\\":\\"0\\"}]"
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⚠ It MUST be a JSON-encoded string. If you pass an object the backend
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rejects it. Strings, single-quoted JSON, or other formats break the editor.
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LIST FIELDS (type='list') — initialProps shape:
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- listType (REQUIRED): one of 'pulldown' | 'radios' | 'pulldownMulti' | 'checkboxes'.
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NOT 'select' nor 'dropdown' — use 'pulldown'.
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- optionsType (REQUIRED): one of 'text' | 'table' | 'query'.
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- When optionsType='text': pass 'optionsText' as a SINGLE string with one
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option per line, separated by REAL NEWLINE CHARACTERS ('\\n' in JSON).
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Each line is either 'value|Label' (preferred) or just 'label' (value=label).
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⚠ Do NOT separate options with commas. Commas inside an option are valid
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data — Acai uses '\\n' as the option delimiter, period.
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Example (correct):
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"optionsText": "indefinido|Indefinido\\ntemporal|Temporal\\nfreelance|Freelance"
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Example (WRONG, will store all 4 as a single option):
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"optionsText": "Indefinido,Temporal,Prácticas,Freelance"
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- When optionsType='table': pass 'optionsTablename' (target table without cms_),
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'optionsValueField' (default 'num'), 'optionsLabelField'. Optional 'filterField'
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is a SQL WHERE clause without the WHERE keyword (e.g. "visible=1").
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- When optionsType='query': pass 'optionsQuery' as raw SQL. Acai uses POSITIONAL
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columns: column 0 is the value, column 1 is the label. So write
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"SELECT num, titulo FROM cms_xxx WHERE active=1" — the 'AS value/label'
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aliases have NO effect.`,
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withAuthParams({
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tableName: z.string().describe("Table name without 'cms_' prefix"),
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fieldName: z.string().describe("New field name (SQL-safe identifier)"),
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@@ -29,7 +29,27 @@ Destructive cases:
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drops HTML). The backend returns 'warnings' in the response — surface them
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to the user.
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Table names WITHOUT 'cms_' prefix.`,
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Table names WITHOUT 'cms_' prefix.
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MULTITEXT FIELDS — when 'props' touches multitext config:
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- descriptionjson: JSON STRING (not object) with the array of sub-fields.
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Each: {id_campo, nombre_campo, tipo} where tipo is '0'(texto)|'1'(tabla)|
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'3'(fecha)|'4'(color)|'5'(icono). For tipo='1' also include tabla,
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campo_valor, campo_muestra.
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⚠ MUST be JSON-encoded string. Backend rejects objects directly.
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Example: "descriptionjson":"[{\\"id_campo\\":\\"pregunta\\",\\"nombre_campo\\":\\"Pregunta\\",\\"tipo\\":\\"0\\"}]"
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LIST FIELDS — when 'props' touches list config:
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- listType: 'pulldown' | 'radios' | 'pulldownMulti' | 'checkboxes' (NOT 'select').
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- optionsType: 'text' | 'table' | 'query'.
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- optionsText (for optionsType='text'): one option per LINE, separated by
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'\\n' (real newline). Each line is 'value|Label' or just 'label'.
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⚠ Do NOT use commas as the option separator — commas are valid inside
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a label. Example (correct): "indef|Indefinido\\ntemp|Temporal".
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- optionsTablename / optionsValueField / optionsLabelField / filterField
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for optionsType='table'.
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- optionsQuery for optionsType='query' — column 0 is the value, column 1
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the label (positional, 'AS value/label' aliases are ignored).`,
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withAuthParams({
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tableName: z.string().describe("Table name without 'cms_' prefix"),
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fieldName: z.string().describe("Current field name"),
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@@ -5,6 +5,8 @@ from __future__ import annotations
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import asyncio
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import json
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import logging
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import re
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import uuid
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from typing import Any, AsyncIterator
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import anthropic
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@@ -15,6 +17,75 @@ from .base import ModelAdapter, ModelConfig, ModelResponse, StreamChunk
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logger = logging.getLogger(__name__)
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# Algunos fine-tunes (sobre todo MiniMax) ocasionalmente emiten las tool calls
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# como texto literal en lugar de usar los `tool_use` blocks nativos:
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# <minimax:tool_call>
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# <invoke name="acai_code__acai_view">
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# <parameter name="file_path">...</parameter>
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# </invoke>
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# </minimax:tool_call>
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#
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# Cuando eso pasa el orquestador ve "texto" y la tool nunca se ejecuta — el
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# usuario ve el XML crudo en el chat. Detectamos y convertimos a tool_use
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# sintetico mientras streameamos. Es un parche defensivo: el caso normal
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# (tool_use blocks) sigue por el camino estandar.
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_TOOL_CALL_OPEN_RE = re.compile(r"<(?:minimax:tool_call|invoke\s+name)", re.IGNORECASE)
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_INVOKE_RE = re.compile(
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r"<invoke\s+name=\"([^\"]+)\"\s*>(.*?)</invoke>",
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re.IGNORECASE | re.DOTALL,
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)
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_PARAM_RE = re.compile(
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r"<parameter\s+name=\"([^\"]+)\"\s*>(.*?)</parameter>",
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re.IGNORECASE | re.DOTALL,
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)
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def _safe_emit_split(buf: str) -> str:
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"""Devuelve el prefijo del buffer que es seguro emitir como texto sin
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perder un posible inicio de tag XML que esta llegando fragmentado.
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Mantenemos en hold los ultimos 30 chars si terminan con `<` o con un
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prefijo parcial de `<minimax:tool_call` / `<invoke`. Si el buffer es
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largo y no termina con `<`, todo es seguro.
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"""
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if not buf:
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return ""
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# Buscar el ultimo `<` y comprobar si lo que sigue puede ser apertura.
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idx = buf.rfind("<")
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if idx == -1:
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return buf
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tail = buf[idx:]
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# Si el tail ya tiene `>` cerrado, es un tag normal — emitir todo.
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if ">" in tail:
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return buf
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# Si el tail puede ser inicio de tool_call/invoke, retenerlo.
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candidates = ("<minimax:tool_call", "<invoke")
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for cand in candidates:
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if cand.startswith(tail.lower()) or tail.lower().startswith(cand[:len(tail)].lower()):
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return buf[:idx]
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# No coincide con ninguna apertura sospechosa — emitir todo.
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return buf
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def _parse_xml_tool_calls(text: str) -> list[dict[str, Any]]:
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"""Extrae tool calls del texto. Devuelve lista de {id, name, arguments}.
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Si no encuentra patrones validos devuelve []."""
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calls = []
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for m in _INVOKE_RE.finditer(text):
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name = m.group(1).strip()
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body = m.group(2)
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args = {}
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for p in _PARAM_RE.finditer(body):
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args[p.group(1).strip()] = p.group(2).strip()
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if name:
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calls.append({
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"id": "xml_{}".format(uuid.uuid4().hex[:12]),
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"name": name,
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"arguments": args,
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})
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return calls
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# Errores transitorios del proxy del modelo (MiniMax/Anthropic). Reintentamos
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# con backoff exponencial: 1s, 3s, 9s. 529 es overloaded_error de Anthropic;
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# 429 rate-limit; 503 service unavailable.
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@@ -98,6 +169,14 @@ class ClaudeAdapter(ModelAdapter):
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current_tool_name = ""
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accumulated_args = ""
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input_tokens = 0
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# Buffer + flag para detectar XML tool calls inline (MiniMax).
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# En modo "text", emitimos delta directamente. Si vemos `<invoke`
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# o `<minimax:tool_call`, pasamos a modo "buffer" y dejamos de
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# emitir hasta cerrar el bloque o terminar el mensaje. Al final
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# parseamos y emitimos un tool_use sintetico.
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text_buffer = ""
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in_xml_capture = False
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xml_buffer = ""
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async for event in stream:
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yielded_any = True
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@@ -121,7 +200,29 @@ class ClaudeAdapter(ModelAdapter):
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if event.type == "content_block_delta":
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delta = event.delta
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if delta.type == "text_delta":
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yield StreamChunk(delta=delta.text)
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text_buffer += delta.text
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if in_xml_capture:
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xml_buffer += delta.text
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else:
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# Detectar inicio del bloque XML antes de emitir.
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m = _TOOL_CALL_OPEN_RE.search(text_buffer)
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if m:
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# Emitir el texto previo al match (texto
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# legitimo que el modelo escribio antes del XML).
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prev = text_buffer[:m.start()]
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if prev:
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yield StreamChunk(delta=prev)
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in_xml_capture = True
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xml_buffer = text_buffer[m.start():]
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text_buffer = ""
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else:
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# Holdback: si el final del buffer parece
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# arrancar una apertura ('<', '<i', '<inv'...)
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# esperamos al siguiente delta antes de emitir.
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safe = _safe_emit_split(text_buffer)
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if safe:
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yield StreamChunk(delta=safe)
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text_buffer = text_buffer[len(safe):]
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elif delta.type == "input_json_delta":
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accumulated_args += delta.partial_json
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yield StreamChunk(
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@@ -145,9 +246,40 @@ class ClaudeAdapter(ModelAdapter):
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continue
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if event.type == "message_delta":
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output_tokens = getattr(event.usage, "output_tokens", 0) if event.usage else 0
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# Antes de cerrar, vaciar buffers.
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if in_xml_capture and xml_buffer:
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# Parsear el XML capturado y emitir tool_use sinteticos.
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calls = _parse_xml_tool_calls(xml_buffer)
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if calls:
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logger.info(
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"Detected %d inline XML tool call(s) — converting to tool_use",
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len(calls),
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||||
)
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for c in calls:
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yield StreamChunk(
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||||
finish_reason=event.delta.stop_reason or "",
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||||
tool_call_id=c["id"],
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||||
tool_name=c["name"],
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||||
)
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||||
yield StreamChunk(
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||||
tool_call_id=c["id"],
|
||||
tool_name=c["name"],
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||||
tool_arguments=json.dumps(c["arguments"]),
|
||||
finish_reason="tool_use",
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||||
)
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||||
else:
|
||||
# No se pudo parsear — devolver al usuario el
|
||||
# texto crudo para no perderlo silenciosamente.
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||||
yield StreamChunk(delta=xml_buffer)
|
||||
xml_buffer = ""
|
||||
in_xml_capture = False
|
||||
elif text_buffer:
|
||||
yield StreamChunk(delta=text_buffer)
|
||||
text_buffer = ""
|
||||
output_tokens = getattr(event.usage, "output_tokens", 0) if event.usage else 0
|
||||
# Si convertimos XML a tool_use, override el stop_reason.
|
||||
stop_reason = event.delta.stop_reason or ""
|
||||
yield StreamChunk(
|
||||
finish_reason=stop_reason,
|
||||
usage={
|
||||
"input_tokens": input_tokens,
|
||||
"output_tokens": output_tokens,
|
||||
|
||||
@@ -64,8 +64,6 @@ class BaseAgent:
|
||||
total_output_tokens = 0
|
||||
# Real conversation history: assistant messages + tool results
|
||||
conversation: list[dict[str, Any]] = []
|
||||
tool_fingerprints: dict[str, ToolExecution] = {}
|
||||
all_duplicates_streak = 0 # consecutive steps where ALL calls are duplicates
|
||||
|
||||
for step in range(max_steps):
|
||||
# Build context with real conversation
|
||||
@@ -205,14 +203,19 @@ class BaseAgent:
|
||||
]
|
||||
conversation.append(assistant_msg)
|
||||
|
||||
# Execute tool calls and add COMPLETE results to conversation
|
||||
duplicates_this_step = 0
|
||||
# Execute tool calls and add COMPLETE results to conversation.
|
||||
# Antes habia dos capas anti-duplicado: (a) cachear resultado y
|
||||
# devolver "[DUPLICADO]" en lugar de re-ejecutar y (b) cortar el
|
||||
# step si TODAS las llamadas del paso eran duplicadas. Las quitamos
|
||||
# porque en conversaciones largas el agente puede LEGITIMAMENTE
|
||||
# repetir una llamada (p.ej. re-leer un fichero tras editarlo) y
|
||||
# las heuristicas bloqueaban acciones validas. El usuario prefiere
|
||||
# libertad — runaway loops se mitigan con limit de steps externo.
|
||||
for tc in tool_calls:
|
||||
# Si los args no se pudieron parsear (p.ej. truncados por max_tokens),
|
||||
# NO ejecutamos la tool. En su lugar devolvemos un mensaje al modelo
|
||||
# explicando el problema para que pueda ajustar el siguiente intento
|
||||
# (dividir el contenido, acortar, etc.). Fingerprint incluye el hash
|
||||
# del raw para distinguir fallos distintos.
|
||||
# (dividir el contenido, acortar, etc.).
|
||||
if tc.get("parse_error"):
|
||||
pe = tc["parse_error"]
|
||||
conversation.append({
|
||||
@@ -229,24 +232,6 @@ class BaseAgent:
|
||||
),
|
||||
})
|
||||
continue
|
||||
fp_raw = f"{tc['name']}:{json.dumps(tc.get('parsed_arguments', {}), sort_keys=True)}"
|
||||
fp = hashlib.md5(fp_raw.encode()).hexdigest()
|
||||
|
||||
if fp in tool_fingerprints:
|
||||
prev_exec = tool_fingerprints[fp]
|
||||
tool_executions.append(prev_exec)
|
||||
duplicates_this_step += 1
|
||||
# Return cached result as tool message
|
||||
conversation.append({
|
||||
"role": "tool",
|
||||
"tool_call_id": tc["id"],
|
||||
"content": (
|
||||
"[DUPLICADO] Ya ejecutada con mismos argumentos. Resultado: "
|
||||
f"{prev_exec.raw_output[:settings.tool_raw_output_max_chars]}"
|
||||
),
|
||||
})
|
||||
logger.warning("Duplicate tool call skipped: %s (fingerprint: %s)", tc["name"], fp[:8])
|
||||
continue
|
||||
|
||||
tool_exec = await self._execute_tool(
|
||||
session=session,
|
||||
@@ -255,7 +240,6 @@ class BaseAgent:
|
||||
artifacts=artifacts,
|
||||
tool_call_id=tc["id"],
|
||||
)
|
||||
tool_fingerprints[fp] = tool_exec
|
||||
tool_executions.append(tool_exec)
|
||||
|
||||
# COMPLETE result in conversation (truncated to safe limit)
|
||||
@@ -269,32 +253,6 @@ class BaseAgent:
|
||||
),
|
||||
})
|
||||
|
||||
# Loop detection: if ALL tool calls in this step were duplicates
|
||||
if duplicates_this_step == len(tool_calls):
|
||||
all_duplicates_streak += 1
|
||||
if all_duplicates_streak >= 2:
|
||||
logger.warning("Loop detected: %d consecutive steps with all duplicate calls. Breaking.", all_duplicates_streak)
|
||||
conversation.append({
|
||||
"role": "user",
|
||||
"content": "[SISTEMA] Se detectaron llamadas repetidas. Ya tienes toda la información necesaria. Genera tu respuesta final ahora.",
|
||||
})
|
||||
# One more chance to generate a final response
|
||||
ctx = await self.context.build_context(
|
||||
session=session, agent=self.profile,
|
||||
artifacts=artifacts, conversation=conversation,
|
||||
)
|
||||
async for chunk in self.model.stream(
|
||||
messages=ctx.to_messages(),
|
||||
config=config,
|
||||
):
|
||||
if chunk.delta:
|
||||
accumulated_content += chunk.delta
|
||||
if chunk.finish_reason:
|
||||
break
|
||||
break
|
||||
else:
|
||||
all_duplicates_streak = 0
|
||||
|
||||
return {
|
||||
"content": accumulated_content,
|
||||
"artifacts": artifacts,
|
||||
|
||||
Reference in New Issue
Block a user