import React, { useEffect, useRef, useState } from "react";
import { supabase } from "@/auth/supabase";
import ReactMarkdown from "react-markdown";
/* ---------- UI Mocks (sin cambios) ---------- */
const Paperclip = (props) => (
);
const Dialog = ({ open, onOpenChange, children }) =>
open ?
{children}
: null;
const DialogContent = ({ className, children }) =>
e.stopPropagation()}>{children}
;
const DialogHeader = ({ children }) => {children}
;
const DialogTitle = ({ className, children }) => {children}
;
const Button = ({ onClick, disabled, className, variant, children }) => (
);
const Card = ({ className, children }) => {children}
;
const CardContent = ({ className, children }) => {children}
;
const ScrollArea = ({ className, children }) => {children}
;
/* ------------- COMPONENT ------------- */
export default function AIChatModal({ open, onClose, context, onAccept, plan_format }) {
const [vectorStores, setVectorStores] = useState([]);
const [vectorFiles, setVectorFiles] = useState([]);
const [selectedVector, setSelectedVector] = useState(null);
const [selectedFiles, setSelectedFiles] = useState([]);
const [attachedFiles, setAttachedFiles] = useState([]);
const [attachedPreviews, setAttachedPreviews] = useState([]);
// chat
const [messages, setMessages] = useState([]);
const [input, setInput] = useState("");
// loading states
const [loading, setLoading] = useState(false);
const [loadingFiles, setLoadingFiles] = useState(false);
const [loadingVectors, setLoadingVectors] = useState(false);
// conversation control
const [conversationId, setConversationId] = useState(null);
const [creatingConversation, setCreatingConversation] = useState(false);
const messagesEndRef = useRef(null);
const scrollToBottom = () => messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
useEffect(scrollToBottom, [messages]);
const normalizeInvokeResponse = (resp) => {
if (!resp) return null;
const raw = resp.data;
if (typeof raw === "string") {
try { return JSON.parse(raw); } catch (e) { console.warn("❗ No se pudo parsear resp.data:", raw); return null; }
}
if (typeof raw === "object" && raw !== null) return raw;
return null;
};
// Al abrir: reset o crear conversación
useEffect(() => {
if (!open) {
if (conversationId) {
deleteConversation(conversationId).catch((e) => console.error(e));
}
setMessages([]);
setInput("");
setSelectedFiles([]);
setAttachedFiles([]);
setAttachedPreviews([]);
setConversationId(null);
setSelectedVector(null);
setVectorFiles([]);
return;
}
if (context) {
setMessages([
{
role: "system",
//content: `Contexto académico:\n${context.section || "—"}\n\nTexto original:\n${context.originalText || "—"}`
content: `Contexto académico:\n${context.section || "—"}\n\nTexto original:\n${context.originalText || "—"}`
}
]);
}
(async () => {
await createConversation();
fetchVectorStores();
})();
}, [open]);
// ---------- CREATE CONVERSATION ----------
const createConversation = async () => {
try {
setCreatingConversation(true);
const { data: { session } } = await supabase.auth.getSession();
const token = session?.access_token;
const resp = await supabase.functions.invoke("modal-conversation", {
headers: { Authorization: `Bearer ${token}` },
body: { action: "start", role: "system", content: context?.cont_conversation ?? "" }
});
let parsed = null;
if (typeof resp?.data === "string") {
try { parsed = JSON.parse(resp.data); } catch (e) { parsed = null; }
} else if (typeof resp?.data === "object" && resp.data !== null) parsed = resp.data;
else parsed = resp;
const convId =
parsed?.conversationId ||
parsed?.data?.conversationId ||
parsed?.data?.id ||
parsed?.id ||
parsed?.conversation_id ||
parsed?.data?.conversation_id;
if (!convId) { setCreatingConversation(false); return; }
setConversationId(convId);
} catch (err) {
console.error("Error creando conversación:", err);
} finally {
setCreatingConversation(false);
}
};
// ---------- DELETE CONVERSATION ----------
const deleteConversation = async (convIdParam) => {
try {
const convIdToUse = convIdParam ?? conversationId;
if (!convIdToUse) return;
const { data: { session } } = await supabase.auth.getSession();
const token = session?.access_token;
await supabase.functions.invoke("modal-conversation", {
headers: { Authorization: `Bearer ${token}` },
body: { action: "end", conversationId: convIdToUse }
});
setConversationId(null);
} catch (err) {
console.error("Error eliminando conversación:", err);
}
};
// ---------- CONVERT FILE TO BASE64 ----------
const fileToBase64 = (file) =>
new Promise((resolve, reject) => {
const reader = new FileReader();
reader.onerror = (e) => reject(e);
reader.onload = () => resolve(reader.result.split(",")[1]);
reader.readAsDataURL(file);
});
// ---------- HANDLE CONVERSATION (envío) ----------
const handleConversation = async ({ text }) => {
let contextText = "";
if (context?.originalText) contextText += `CONTEXTO DEL CAMPO:\n${context.originalText}\n`;
if (!conversationId) {
console.warn("No hay conversación activa todavía. conversationId:", conversationId);
return;
}
try {
setLoading(true);
const { data: { session } } = await supabase.auth.getSession();
const token = session?.access_token;
// archivos adjuntos (locales) -> base64
let filesInput = [];
if (attachedFiles.length > 0) {
for (const file of attachedFiles) {
const base64 = await fileToBase64(file);
filesInput.push({
type: "input_file",
filename: file.name,
file_data: `data:${file.type};base64,${base64}`
});
}
}
// archivos seleccionados del vector (por id)
if (selectedFiles.length > 0) {
const filesFromVectors = selectedFiles.map(f => ({
type: "input_file",
file_id: f.id
}));
filesInput = [...filesInput, ...filesFromVectors];
}
const promptFinal = `${contextText}\nPREGUNTA DEL USUARIO:\n${text}`;
const payload = {
action: "message",
format: plan_format,
conversationId,
vectorStoreId: selectedVector ?? null,
fileIds: selectedFiles.length ? selectedFiles.map(f => f.id) : [],
input: [
{
role: "user",
content: [
{ type: "input_text", text: promptFinal },
...filesInput
]
}
]
};
const { data: invokeData, error } = await supabase.functions.invoke(
"modal-conversation",
{
headers: { Authorization: `Bearer ${token}` },
body: payload
}
);
if (error) throw error;
const parsed = normalizeInvokeResponse({ data: invokeData });
// Extraer texto del assistant (robusto)
let assistantText = null;
if (parsed?.data?.output_text) assistantText = parsed.data.output_text;
if (!assistantText && Array.isArray(parsed?.data?.output)) {
const msgBlock = parsed.data.output.find(o => o.type === "message");
if (msgBlock?.content?.[0]?.text) assistantText = msgBlock.content[0].text;
}
assistantText = assistantText || "Sin respuesta del modelo.";
setMessages(prev => [...prev, { role: "assistant", content: cleanAssistantResponse(assistantText) }]);
// limpiar attachments locales (pero mantener seleccionados del vector si quieres — aquí los limpiamos)
setAttachedFiles([]);
setAttachedPreviews([]);
// si quieres mantener los selectedFiles tras el envío, comenta la siguiente línea:
setSelectedFiles([]);
} catch (err) {
console.error("Error en handleConversation:", err);
setMessages(prev => [...prev, { role: "assistant", content: "Ocurrió un error al procesar tu mensaje." }]);
} finally {
setLoading(false);
}
};
// ---------- VECTORES ----------
const fetchVectorStores = async () => {
try {
setLoadingVectors(true);
const { data: { session } } = await supabase.auth.getSession();
const token = session?.access_token;
const { data, error } = await supabase.functions.invoke("files-and-vector-stores-api", {
headers: { Authorization: `Bearer ${token}` },
body: { module: "vectorStores", action: "list" }
});
if (error) throw error;
setVectorStores(Array.isArray(data) ? data : (data?.data ?? []));
} catch (err) {
console.error("Error loading vector stores:", err);
setVectorStores([]);
} finally {
setLoadingVectors(false);
}
};
useEffect(() => {
if (open) fetchVectorStores();
}, [open]);
const loadFilesForVector = async (vectorStoreId) => {
try {
setLoadingFiles(true);
const { data: { session } } = await supabase.auth.getSession();
const token = session?.access_token;
const { data, error } = await supabase.functions.invoke("files-and-vector-stores-api", {
headers: { Authorization: `Bearer ${token}` },
body: { module: "vectorStoreFiles", action: "list", params: { vector_store_id: vectorStoreId } }
});
if (error) throw error;
setVectorFiles(Array.isArray(data) ? data : (data?.data ?? []));
} catch (err) {
console.error("Error loading vector files:", err);
setVectorFiles([]);
} finally {
setLoadingFiles(false);
}
};
// ---------- UI helpers ----------
const handleAttach = (e) => {
const files = Array.from(e.target.files);
if (!files.length) return;
setAttachedFiles(prev => [...prev, ...files]);
setAttachedPreviews(prev => [...prev, ...files.map(f => f.name)]);
};
// Al hacer click en un vector: expandir (solo uno a la vez) y cargar sus archivos
const handleVectorClick = async (vector) => {
if (selectedVector === vector.id) {
// colapsar
setSelectedVector(null);
setVectorFiles([]);
setSelectedFiles([]);
return;
}
setSelectedVector(vector.id);
setSelectedFiles([]);
await loadFilesForVector(vector.id);
};
// Toggle selección de archivo (checkbox)
const toggleFileSelection = (file) => {
if (selectedFiles.some(f => f.id === file.id)) {
setSelectedFiles(prev => prev.filter(f => f.id !== file.id));
} else {
setSelectedFiles(prev => [...prev, file]);
}
};
const removeSelectedFile = (fileId) => {
setSelectedFiles(prev => prev.filter(f => f.id !== fileId));
};
// ---------- Send flow ----------
const handleSend = async () => {
// no permitir enviar si no hay nada
if (!input.trim() && attachedFiles.length === 0 && selectedFiles.length === 0) return;
if (creatingConversation) {
// no bloqueo visible aquí por diseño; simplemente ignoramos el envío si aún creando
return;
}
if (!conversationId) {
await createConversation();
if (!conversationId) {
setMessages(prev => [...prev, { role: "assistant", content: "No se pudo crear la conversación. Intenta de nuevo." }]);
return;
}
}
const userText = input.trim() || (selectedFiles.length ? `Consultar ${selectedFiles.length} archivo(s) del repositorio` : "");
setMessages(prev => [...prev, { role: "user", content: userText }]);
setInput("");
await handleConversation({ text: userText });
};
function cleanAIResponse(text) {
if (!text) return text;
let cleaned = text;
// -------------------------
// 1. Eliminar emojis
// -------------------------
cleaned = cleaned.replace(/[\p{Emoji}\uFE0F]/gu, "");
// -------------------------
// 2. Eliminar separadores tipo ---
// -------------------------
cleaned = cleaned.replace(/^---+$/gm, "");
// -------------------------
// 3. Eliminar saludos y frases meta
// -------------------------
const metaPatterns = [
/^hola[!¡., ]*/i,
/^buen(os|as) (días|tardes|noches)[!¡., ]*/i,
/estoy aquí para ayudarte[.! ]*/gi,
/aquí tienes[,:]*/gi,
/claro[,:]*/gi,
/como pediste[,:]*/gi,
/como solicitaste[,:]*/gi,
/el texto íntegro que compartiste.*$/gi,
/te lo dejo a continuación.*$/gi,
/¿te gustaría.*$/gi,
/¿en qué más puedo.*$/gi,
/si necesitas algo más.*$/gi,
/con gusto.*$/gi,
];
metaPatterns.forEach(p => {
cleaned = cleaned.replace(p, "").trim();
});
// -------------------------
// 4. Extraer solo contenido útil
// -------------------------
const startMarker = "CONTEXTO DEL CAMPO";
const startIndex = cleaned.indexOf(startMarker);
if (startIndex !== -1) {
cleaned = cleaned.substring(startIndex).trim();
}
// -------------------------
// 5. Eliminar líneas vacías múltiples
// -------------------------
cleaned = cleaned.replace(/\n{2,}/g, "\n\n");
// -------------------------
// 6. Quitar numeraciones de cortesía (opcional)
// Ejemplo: “1. ” al inicio de líneas
// -------------------------
cleaned = cleaned.replace(/^\s*\d+\.\s+/gm, "");
return cleaned.trim();
}
const handleApply = () => {
const last = [...messages].reverse().find(m => m.role === "assistant");
if (last && onAccept) {
const cleaned = cleanAIResponse(last.content);
onAccept(cleaned);
onClose();
}
};
const cleanAssistantResponse = (text) => {
if (!text) return text;
const patterns = [/^claro[, ]*/i, /^por supuesto[, ]*/i, /^aquí tienes[, ]*/i, /^con gusto[, ]*/i, /^hola[, ]*/i, /^perfecto[, ]*/i, /^entendido[, ]*/i, /^muy bien[, ]*/i, /^ok[, ]*/i];
let cleaned = text.trim();
for (const p of patterns) cleaned = cleaned.replace(p, "").trim();
return cleaned;
};
return (
);
}