'use server';

/**
 * @fileOverview A Genkit flow for generating chatbot responses.
 *
 * - generateChatbotResponse - A function that generates chatbot responses.
 * - GenerateChatbotResponseInput - The input type for the generateChatbotResponse function.
 * - GenerateChatbotResponseOutput - The return type for the generateChatbotResponse function.
 */

import {ai} from '@/ai/genkit';
import {z} from 'genkit';
import fs from 'fs';
import path from 'path';

const systemInstructionsPath = path.join(
  process.cwd(),
  'src',
  'ai',
  'flows',
  'chatbot_system_instructions.txt'
);
const systemInstructions = fs.readFileSync(systemInstructionsPath, 'utf-8');

const GenerateChatbotResponseInputSchema = z.object({
  message: z.string().describe('The user message to respond to.'),
  chatHistory: z
    .array(z.object({role: z.enum(['user', 'assistant']), content: z.string()}))
    .optional()
    .describe('The chat history to maintain context.'),
  photoDataUri: z
    .string()
    .optional()
    .describe(
      "A photo, as a data URI that must include a MIME type and use Base64 encoding. Expected format: 'data:<mimetype>;base64,<encoded_data>'."
    ),
});
export type GenerateChatbotResponseInput = z.infer<
  typeof GenerateChatbotResponseInputSchema
>;

const GenerateChatbotResponseOutputSchema = z.object({
  response: z.string().describe('The chatbot response.'),
});
export type GenerateChatbotResponseOutput = z.infer<
  typeof GenerateChatbotResponseOutputSchema
>;

export async function generateChatbotResponse(
  input: GenerateChatbotResponseInput
): Promise<GenerateChatbotResponseOutput> {
  return generateChatbotResponseFlow(input);
}

const prompt = ai.definePrompt({
  name: 'generateChatbotResponsePrompt',
  system: systemInstructions,
  input: {schema: GenerateChatbotResponseInputSchema},
  output: {schema: GenerateChatbotResponseOutputSchema},
  prompt: `Here's the chat history (if any):
  {{#each chatHistory}}
  {{role}}: {{{content}}}
  {{/each}}

  {{#if photoDataUri}}
  [User has uploaded an image, analyze it and answer based on that and the user message.]
  Photo: {{media url=photoDataUri}}
  {{/if}}
  User message: {{{message}}}
  `,
});

const generateChatbotResponseFlow = ai.defineFlow(
  {
    name: 'generateChatbotResponseFlow',
    inputSchema: GenerateChatbotResponseInputSchema,
    outputSchema: GenerateChatbotResponseOutputSchema,
  },
  async (input) => {
    const {output} = await prompt(input);
    return output!;
  }
);