623e5bcd34
Chatbot (general assistant + per-recipe Q&A) now resolves its default model from its own site setting (DEFAULT_CHAT_PROVIDER/MODEL) instead of sharing the generic "text" use case with recipe generation, so admins can point it at a different model. Added AI_TOOL_CALLING_ENABLED: turns off the chatbot's createRecipe/ addToShoppingList tools (and the forced-retry pass) for models that don't reliably support tool calling — it falls back to plain text answers. Simplified the admin AI Configuration page: it showed provider keys and routing settings twice (a read-only card, then an identical edit form). Merged into one editable section; the resolved fallback provider is now a one-line note instead of its own card. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
158 lines
9.1 KiB
TypeScript
158 lines
9.1 KiB
TypeScript
import { NextRequest, NextResponse } from "next/server";
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import { z } from "zod";
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import { generateText, stepCountIs } from "ai";
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import { db, chatMessages, aiConversations, sql } from "@epicure/db";
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import { requireSessionOrApiKey } from "@/lib/api-auth";
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import { applyRateLimit } from "@/lib/rate-limit";
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import { withAiQuota, resolveAiConfigOrError } from "@/lib/ai/ai-error";
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import { getModelConfigForUseCase } from "@/lib/ai/resolve-user-key";
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import { resolveModel } from "@/lib/ai/factory";
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import { isAiToolCallingEnabled } from "@/lib/site-settings";
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import { getUserPrivateBio, buildUserBioContext } from "@/lib/ai/user-bio";
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import { createRecipeTool } from "@/lib/ai/tools/create-recipe-tool";
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import { addToShoppingListTool } from "@/lib/ai/tools/add-to-shopping-list-tool";
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const Schema = z.object({
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question: z.string().min(1).max(500),
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conversationId: z.string().uuid().optional(),
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});
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const LANG: Record<string, string> = { en: "English", fr: "French" };
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// Forcing toolChoice to a specific tool makes some providers return the tool
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// call with no accompanying text at all (their "forced function calling" is
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// content-free by design) — the chat needs some reply, so fall back to this
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// rather than showing an empty assistant bubble.
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const DRAFT_FALLBACK_TEXT: Record<string, string> = {
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en: "Here's a draft — check it below and confirm if it looks right.",
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fr: "Voici un brouillon — vérifie-le ci-dessous et confirme si ça te convient.",
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};
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/** Weaker/free-tier models sometimes ignore the system prompt's "call the
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* tool, don't write it out" rule and answer with the recipe spelled out as
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* a numbered/bulleted list instead. That's the exact shape the tool call
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* itself would have captured structurally — a reliable enough signal to
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* self-correct with a forced-tool retry rather than surfacing prose. */
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function looksLikeUnstructuredRecipe(text: string): boolean {
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const listLines = text.split("\n").filter((line) => /^\s*(\d+[.)]|[-*•])\s+\S/.test(line));
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return listLines.length >= 3;
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}
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// The above only catches the model spelling the whole recipe out. A second,
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// more common failure with weaker models: it gives a short reply that even
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// *claims* to have drafted something ("here's a draft, check below") without
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// ever calling the tool — so nothing renders below it. Rather than guess from
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// that claim (fragile across models/phrasing), detect intent from the user's
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// own message instead: same noun+verb pattern the system prompt itself uses
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// as its createRecipe examples, checked in whichever of the two supported
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// locales the request is in.
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const RECIPE_INTENT: Record<string, { noun: RegExp; verb: RegExp }> = {
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en: { noun: /\brecipe\b/i, verb: /\b(create|make|generate|give|write|save|invent)\b/i },
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fr: { noun: /\brecettes?\b/i, verb: /\b(cr[ée]e?r?|fais|donne|[ée]cri[st]|note[rz]?|sauvegard\w*|enregistr\w*|invente\w*|g[ée]n[èe]re\w*)\b/i },
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};
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function looksLikeRecipeCreationRequest(question: string, locale: string): boolean {
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const pattern = RECIPE_INTENT[locale] ?? RECIPE_INTENT["en"]!;
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return pattern.noun.test(question) && pattern.verb.test(question);
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}
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export async function POST(req: NextRequest) {
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const { session, response } = await requireSessionOrApiKey(req);
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if (response) return response;
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const body = await req.json() as unknown;
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const parsed = Schema.safeParse(body);
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if (!parsed.success) {
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return NextResponse.json({ error: "Validation error" }, { status: 400 });
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}
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const limited = await applyRateLimit(`rl:ai:${session!.user.id}`, 30, 60);
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if (limited) return limited;
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const [configResult, privateBio, toolCallingEnabled] = await Promise.all([
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resolveAiConfigOrError(() => getModelConfigForUseCase(session!.user.id, "chat")),
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getUserPrivateBio(session!.user.id),
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isAiToolCallingEnabled(),
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]);
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if (!configResult.ok) return configResult.response;
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const aiConfig = configResult.data;
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const model = resolveModel(aiConfig);
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const bioContext = buildUserBioContext(privateBio);
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const locale = (session!.user as { locale?: string }).locale ?? "en";
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const lang = LANG[locale] ?? "English";
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const toolsInstructions = toolCallingEnabled
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? `\n\nYou have two tools. Using one only drafts something for the user to review — it never saves by itself.\n- createRecipe: the user is asking you to create, save, or write down a recipe (e.g. "make me a recipe for X", "give me a recipe for Y", "write that down"). This includes any request for a full recipe, not only ones that say the word "create" or "save".\n- addToShoppingList: the user is asking to add ingredients/items to a shopping list.\n\nIMPORTANT: when the user's request matches createRecipe, you MUST call that tool instead of writing the recipe's ingredients or steps directly in your text reply. Never output a full ingredient list or numbered steps as plain text — that content belongs in the tool call, not the message. Your text reply in that case should just be a short line like "Here's a draft — check it below and confirm if it looks right." Only skip the tool if the user is asking a general question (no specific recipe requested) or explicitly wants prose, not a structured recipe.`
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: "";
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const system = `You are Epicure, a helpful culinary assistant answering general cooking questions — not tied to any specific recipe (techniques, substitutions, timing, equipment, food safety, etc). If asked who you are or what model/AI you're built on, say you're Epicure — never name the underlying model or provider. If a question has nothing to do with cooking or food, politely redirect. Keep answers under 200 words. Respond in ${lang}.${toolsInstructions}${bioContext}`;
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const result = await withAiQuota(session!.user.id, session!.user.tier as "free" | "pro" | "family", () =>
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generateText(
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toolCallingEnabled
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? {
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model,
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system,
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prompt: parsed.data.question,
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tools: { createRecipe: createRecipeTool, addToShoppingList: addToShoppingListTool },
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stopWhen: stepCountIs(3),
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}
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: { model, system, prompt: parsed.data.question }
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), { skipQuota: aiConfig.isByok }
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);
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if (!result.ok) return result.response;
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let final = result.data;
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// Weaker/free-tier models sometimes ignore the MUST-call-the-tool rule
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// above — either by spelling the recipe out in prose, or (more common,
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// and easy to miss) giving a short reply that *claims* a draft exists
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// without ever calling the tool, so nothing actually renders below it.
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// Catch both: the prose-list shape, or the user's own message clearly
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// asking for a recipe in the first place. Rather than surface either
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// failure, force the tool call on one extra pass — same system+prompt,
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// just no longer letting the model opt out. Skipped entirely when tool
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// calling is turned off admin-side (e.g. a local model that can't
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// reliably call tools) — there's no tool to force in that case.
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if (toolCallingEnabled && final.toolCalls.length === 0 && (looksLikeUnstructuredRecipe(final.text) || looksLikeRecipeCreationRequest(parsed.data.question, locale))) {
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try {
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const forced = await generateText({
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model,
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system,
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prompt: parsed.data.question,
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// Same tool set as the first pass (just forcing createRecipe via
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// toolChoice below) — keeps the result type identical to `result.data`
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// so `final` can hold either without a type mismatch.
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tools: { createRecipe: createRecipeTool, addToShoppingList: addToShoppingListTool },
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toolChoice: { type: "tool", toolName: "createRecipe" },
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stopWhen: stepCountIs(1),
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});
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final = { ...forced, text: forced.text || (DRAFT_FALLBACK_TEXT[locale] ?? DRAFT_FALLBACK_TEXT["en"]!) };
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} catch (err) {
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console.error("[cooking-chat] forced-tool retry failed, keeping prose answer", err);
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}
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}
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const { conversationId } = parsed.data;
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const proposedRecipe = final.toolCalls.find((c) => c.toolName === "createRecipe")?.input;
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const proposedShoppingList = final.toolCalls.find((c) => c.toolName === "addToShoppingList")?.input;
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void db.insert(chatMessages).values([
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{ id: crypto.randomUUID(), userId: session!.user.id, recipeId: null, conversationId, role: "user", content: parsed.data.question },
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{ id: crypto.randomUUID(), userId: session!.user.id, recipeId: null, conversationId, role: "assistant", content: final.text },
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]).catch((err) => console.error("[cooking-chat] failed to persist chat history", err));
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if (conversationId) {
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// Bumps updatedAt (for the conversation list's sort order) and, only if
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// this is the conversation's first message, auto-titles it from the
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// opening question — so users aren't left staring at "Untitled" entries;
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// they can still rename it later.
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void db.execute(sql`
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UPDATE ${aiConversations}
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SET updated_at = now(), title = COALESCE(title, ${parsed.data.question.slice(0, 60)})
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WHERE ${aiConversations.id} = ${conversationId} AND ${aiConversations.userId} = ${session!.user.id}
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`).catch((err) => console.error("[cooking-chat] failed to touch conversation", err));
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}
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return NextResponse.json({ answer: final.text, proposedRecipe, proposedShoppingList });
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}
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