Assistants Completions API

data: {"type":"message","content":"Hallo"}
data: {"type":"message","content":" Welt"}
data: {"type":"done"}

const response = await fetch('https://api.langdock.com/assistant/v1/chat/completions', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    assistantId: 'asst_123',
    messages: [{ role: 'user', content: 'Hallo' }],
    stream: true
  }),
});

const reader = response.body.getReader();
const decoder = new TextDecoder();

while (true) {
  const { done, value } = await reader.read();
  if (done) break;

  const chunk = decoder.decode(value);
  const lines = chunk.split('\n');

  for (const line of lines) {
    if (line.startsWith('data: ')) {
      const data = JSON.parse(line.slice(6));
      if (data.type === 'message') {
        process.stdout.write(data.content);
      }
    }
  }
}

const axios = require("axios");

async function chatWithAssistant() {
  const response = await axios.post(
    "https://api.langdock.com/assistant/v1/chat/completions",
    {
      assistantId: "asst_123",
      messages: [
        {
          role: "user",
          content: "Kannst du dieses Dokument für mich analysieren?",
          attachmentIds: ["550e8400-e29b-41d4-a716-446655440000"], // Erhalte attachmentIds vom Upload-Attachment-Endpunkt
        },
      ],
      stream: true, // Streaming-Antworten aktivieren
    },
    {
      headers: {
        Authorization: "Bearer YOUR_API_KEY",
      },
    }
  );

  console.log(response.data.result);
}

const axios = require("axios");

async function chatWithNewAssistant() {
  const response = await axios.post(
    "https://api.langdock.com/assistant/v1/chat/completions",
    {
      assistant: {
        name: "Document Analyzer",
        instructions:
          "You are a helpful agent who analyzes documents and answers questions about them",
        temperature: 0.7,
        model: "gpt-5",
        capabilities: {
          webSearch: true,
        },
        attachmentIds: ["550e8400-e29b-41d4-a716-446655440000"], // Erhalte attachmentIds vom Upload-Attachment-Endpunkt
      },
      messages: [
        {
          role: "user",
          content: "What are the key points in the document?",
        },
      ],
    },
    {
      headers: {
        Authorization: "Bearer YOUR_API_KEY",
      },
    }
  );

  console.log(response.data.result);
}

const axios = require("axios");

async function getStructuredWeather() {
  const response = await axios.post(
    "https://api.langdock.com/assistant/v1/chat/completions",
    {
      assistant: {
        name: "Weather Assistant",
        instructions: "You are a helpful weather agent",
        model: "gpt-5.1",
        capabilities: {
          webSearch: true,
        },
      },
      messages: [
        {
          role: "user",
          content: "What's the weather in paris, berlin and london today?",
        },
      ],
      output: {
        type: "array",
        schema: {
          type: "object",
          properties: {
            weather: {
              type: "object",
              properties: {
                city: {
                  type: "string",
                },
                tempInCelsius: {
                  type: "number",
                },
                tempInFahrenheit: {
                  type: "number",
                },
              },
              required: ["city", "tempInCelsius", "tempInFahrenheit"],
            },
          },
        },
      },
    },
    {
      headers: {
        Authorization: "Bearer YOUR_API_KEY",
      },
    }
  );

  // Access the structured data directly from output
  console.log(response.data.output);
  // Output:
  // [
  //   { "weather": { "city": "Paris", "tempInCelsius": 1, "tempInFahrenheit": 33 } },
  //   { "weather": { "city": "Berlin", "tempInCelsius": 1, "tempInFahrenheit": 35 } },
  //   { "weather": { "city": "London", "tempInCelsius": 7, "tempInFahrenheit": 45 } }
  // ]
}

const axios = require("axios");

async function extractContactInfo() {
  const response = await axios.post(
    "https://api.langdock.com/assistant/v1/chat/completions",
    {
      assistant: {
        name: "Contact Extractor",
        instructions: "You extract contact information from text",
      },
      messages: [
        {
          role: "user",
          content:
            "Extract the contact info: John Smith is our new sales lead. You can reach him at john.smith@example.com or call +1-555-123-4567.",
        },
      ],
      output: {
        type: "object",
        schema: {
          type: "object",
          properties: {
            name: {
              type: "string",
            },
            email: {
              type: "string",
            },
            phone: {
              type: "string",
            },
            role: {
              type: "string",
            },
          },
          required: ["name", "email"],
        },
      },
    },
    {
      headers: {
        Authorization: "Bearer YOUR_API_KEY",
      },
    }
  );

  // Access the structured data directly from output
  console.log(response.data.output);
  // Output:
  // {
  //   "name": "John Smith",
  //   "email": "john.smith@example.com",
  //   "phone": "+1-555-123-4567",
  //   "role": "sales lead"
  // }
}

const axios = require("axios");

async function getSentimentAnalysis() {
  const response = await axios.post(
    "https://api.langdock.com/assistant/v1/chat/completions",
    {
      assistant: {
        name: "Sentiment Analyzer",
        instructions: "You analyze the sentiment of text",
      },
      messages: [
        {
          role: "user",
          content:
            "How would you rate this review: 'This product exceeded my expectations!'",
        },
      ],
      output: {
        type: "enum",
        enum: ["positive", "neutral", "negative"],
      },
    },
    {
      headers: {
        Authorization: "Bearer YOUR_API_KEY",
      },
    }
  );

  // Access the enum result directly from output
  console.log(response.data.output);
  // Output: "positive"
}

{
  // Standard message results - always present
  result: Array<{
    id: string;
    role: "tool" | "assistant";
    content: Array<{
      type: string;
      toolCallId?: string;
      toolName?: string;
      result?: object;
      args?: object;
      text?: string;
    }>;
  }>;

  // Structured output - included by default
  output?: object | array | string;
}

// Request
{
  "output": {
    "type": "array",
    "schema": {
      "type": "object",
      "properties": {
        "weather": {
          "type": "object",
          "properties": {
            "city": { "type": "string" },
            "tempInCelsius": { "type": "number" },
            "tempInFahrenheit": { "type": "number" }
          },
          "required": ["city", "tempInCelsius", "tempInFahrenheit"]
        }
      }
    }
  }
}

// Response
{
  "result": [
    // Full conversation including tool calls (e.g., web searches)
    { "role": "assistant", "content": [...], "id": "..." },
    { "role": "tool", "content": [...], "id": "..." },
    { "role": "assistant", "content": "...", "id": "..." }
  ],
  "output": [
    { "weather": { "city": "Paris", "tempInCelsius": 1, "tempInFahrenheit": 33 } },
    { "weather": { "city": "Berlin", "tempInCelsius": 1, "tempInFahrenheit": 35 } },
    { "weather": { "city": "London", "tempInCelsius": 7, "tempInFahrenheit": 45 } }
  ]
}

try {
  const response = await axios.post('https://api.langdock.com/assistant/v1/chat/completions', ...);
} catch (error) {
  if (error.response) {
    switch (error.response.status) {
      case 400:
        console.error('Invalid parameters:', error.response.data.message);
        break;
      case 429:
        console.error('Rate limit exceeded');
        break;
      case 500:
        console.error('Server error');
        break;
    }
  }
}