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import { useChat, DefaultChatTransport } from '@ai-sdk/react';
import { useMemo } from 'react';

const BOX_URL = 'https://your-box.intelligencebox.it';
const API_KEY = 'YOUR_API_KEY';

export function ChatComponent({ chatId }: { chatId: string }) {
  // Create transport with your box server URL
  const transport = useMemo(() => new DefaultChatTransport({
    api: `${BOX_URL}/api/ai/chat`,
    headers: async () => ({
      'x-api-key': API_KEY,
    }),
    body: {
      id: chatId,
      boxAddress: BOX_URL,
    }
  }), [chatId]);

  const { messages, sendMessage, status, stop } = useChat({
    id: chatId,
    transport,
    onFinish: () => console.log('Stream completed'),
    onError: (error) => console.error('Error:', error),
  });

  const handleSubmit = async (text: string) => {
    await sendMessage({ text });
  };

  return (
    <div>
      {/* Messages */}
      {messages.map((message) => (
        <div key={message.id} className={message.role}>
          <strong>{message.role}:</strong>
          {message.content}
        </div>
      ))}

      {/* Input */}
      <form onSubmit={(e) => {
        e.preventDefault();
        const input = e.currentTarget.querySelector('input');
        if (input?.value) {
          handleSubmit(input.value);
          input.value = '';
        }
      }}>
        <input type="text" placeholder="Type a message..." />
        <button type="submit" disabled={status === 'streaming'}>
          Send
        </button>
      </form>

      {/* Stop button */}
      {status === 'streaming' && (
        <button onClick={stop}>Stop Generation</button>
      )}
    </div>
  );
}

import { parseUIMessageStream } from 'ai';

const BOX_URL = 'https://your-box.intelligencebox.it';

async function streamChat(message: string) {
  const response = await fetch(`${BOX_URL}/api/ai/chat`, {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      'x-api-key': 'YOUR_API_KEY',
    },
    body: JSON.stringify({
      id: 'chat-' + Date.now(),
      messages: [{ role: 'user', content: message }],
      boxAddress: BOX_URL,
    }),
  });

  let fullText = '';

  // Parse the UI message stream
  for await (const part of parseUIMessageStream(response)) {
    switch (part.type) {
      case 'text':
        // Incremental text chunk
        fullText += part.text;
        console.log('Chunk:', part.text);
        break;

      case 'tool-call':
        // AI is calling a tool (web search, etc.)
        console.log('Tool call:', part.toolName, part.args);
        break;

      case 'tool-result':
        // Tool execution result
        console.log('Tool result:', part.toolName, part.result);
        break;

      case 'finish':
        // Stream completed
        console.log('Finished:', part.finishReason);
        break;

      case 'error':
        // Error occurred
        console.error('Error:', part.error);
        break;
    }
  }

  return fullText;
}

// Usage
const answer = await streamChat('What is AI?');

import { ref, onUnmounted } from 'vue';
import { parseUIMessageStream } from 'ai';

const BOX_URL = 'https://your-box.intelligencebox.it';

export function useChat() {
  const messages = ref<Array<{ role: string; content: string }>>([]);
  const isStreaming = ref(false);
  let abortController: AbortController | null = null;

  async function sendMessage(content: string) {
    isStreaming.value = true;
    abortController = new AbortController();

    // Add user message
    messages.value.push({ role: 'user', content });
    // Add empty assistant message for streaming
    messages.value.push({ role: 'assistant', content: '' });
    const assistantIndex = messages.value.length - 1;

    try {
      const response = await fetch(`${BOX_URL}/api/ai/chat`, {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json',
          'x-api-key': 'YOUR_API_KEY',
        },
        body: JSON.stringify({
          id: 'chat-' + Date.now(),
          messages: messages.value.slice(0, -1),
          boxAddress: BOX_URL,
        }),
        signal: abortController.signal,
      });

      for await (const part of parseUIMessageStream(response)) {
        if (part.type === 'text') {
          messages.value[assistantIndex].content += part.text;
        }
      }
    } catch (error) {
      if ((error as Error).name !== 'AbortError') {
        console.error('Error:', error);
      }
    } finally {
      isStreaming.value = false;
    }
  }

  function stop() {
    abortController?.abort();
  }

  onUnmounted(() => stop());

  return { messages, isStreaming, sendMessage, stop };
}

import requests
import json
import time

BOX_URL = 'https://your-box.intelligencebox.it'

def chat(message, assistant_id=None, vector_ids=None):
    payload = {
        'id': f'chat-{int(time.time())}',
        'messages': [{'role': 'user', 'content': message}],
        'boxAddress': BOX_URL
    }

    if assistant_id:
        payload['assistantId'] = assistant_id
    if vector_ids:
        payload['vector'] = vector_ids

    response = requests.post(
        f'{BOX_URL}/api/ai/chat',
        headers={
            'Content-Type': 'application/json',
            'x-api-key': 'YOUR_API_KEY'
        },
        json=payload,
        stream=True
    )

    full_response = ''

    for line in response.iter_lines():
        if line:
            line = line.decode('utf-8')
            if line.startswith('data: '):
                try:
                    data = json.loads(line[6:])
                    event_type = data.get('type')

                    if event_type == 'text':
                        chunk = data.get('text', '')
                        full_response += chunk
                        print(chunk, end='', flush=True)
                    elif event_type == 'tool-call':
                        print(f"\n[Tool: {data.get('toolName')}]")
                    elif event_type == 'error':
                        print(f"\nError: {data.get('error')}")
                    elif event_type == 'finish':
                        print('\n[Done]')

                except json.JSONDecodeError:
                    pass

    return full_response

# Usage
answer = chat('What is AI?')
answer = chat('Summarize my docs', vector_ids=['folder-id'])
answer = chat('Help me', assistant_id='assistant-id')

curl -N -X POST BOX_URL/api/ai/chat \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"id":"chat-1","messages":[{"role":"user","content":"Hello"}],"boxAddress":"BOX_URL"}'

data: {"type":"text","text":"Hello"}
data: {"type":"text","text":"! How"}
data: {"type":"text","text":" can I help you today?"}
data: {"type":"finish","finishReason":"stop"}