Files
famapp/src/app/api/agent/chat/route.ts
T
ginnoir c8db5475d3 feat(agent): add voice input and photo attachments to assistant
Wire mic through Whisper-compatible transcriptions on LLM_BASE_URL.

Photos upload to MinIO and reach the vision model as base64 image_url parts.
2026-07-05 02:01:48 -05:00

93 lines
2.6 KiB
TypeScript

import { apiError, apiJson } from "@/lib/api-handler";
import { resolveApiAuth } from "@/lib/api-auth";
import { getAssistantPreferences, resolveAssistantSystemPrompt } from "@/lib/assistant-preference";
import { isLlmConfigured } from "@/lib/llm";
import { clientChatInputSchema } from "@/modules/agent/messages";
import { encodeSseEvent } from "@/modules/agent/server/progress";
import { runAgentChat } from "@/modules/agent/server/run";
export async function POST(request: Request) {
const auth = await resolveApiAuth(request);
if (!auth?.userId) {
return apiError("Unauthorized", 401);
}
const assistant = await getAssistantPreferences(auth.userId);
if (!assistant.enabled) {
return apiError("Assistant not enabled", 403);
}
const systemPrompt = resolveAssistantSystemPrompt(assistant.systemPrompt);
let body: unknown;
try {
body = await request.json();
} catch {
return apiError("Invalid JSON body", 400);
}
const parsed = clientChatInputSchema.safeParse(body);
if (!parsed.success) {
return apiError(parsed.error.issues[0]?.message ?? "Validation error", 400);
}
if (parsed.data.stream) {
const stream = new ReadableStream<Uint8Array>({
async start(controller) {
const encoder = new TextEncoder();
const send = (event: Parameters<typeof encodeSseEvent>[0]) => {
controller.enqueue(encoder.encode(encodeSseEvent(event)));
};
try {
const result = await runAgentChat({
messages: parsed.data.messages,
request,
systemPrompt,
onProgress: send,
});
send({
type: "done",
message: {
role: "assistant",
content: result.message.content,
},
toolCalls: result.toolCalls,
});
} catch (err) {
const message = err instanceof Error ? err.message : "Agent request failed";
send({ type: "error", message });
} finally {
controller.close();
}
},
});
return new Response(stream, {
headers: {
"Content-Type": "text/event-stream; charset=utf-8",
"Cache-Control": "no-cache, no-transform",
Connection: "keep-alive",
},
});
}
try {
const result = await runAgentChat({
messages: parsed.data.messages,
request,
systemPrompt,
});
return apiJson({
...result,
configured: isLlmConfigured(),
provider: isLlmConfigured() ? "openai" : "mock",
});
} catch (err) {
const message = err instanceof Error ? err.message : "Agent request failed";
return apiError(message, 502);
}
}