Anthropic

npm install @llamaindex/anthropic

import { Anthropic } from "@llamaindex/anthropic";

const llm = new Anthropic({
  model: "claude-3-5-sonnet-20241022",
  temperature: 0.7
});

const response = await llm.chat({
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Explain quantum computing" }
  ]
});

console.log(response.message.content);

const stream = await llm.chat({
  messages: [{ role: "user", content: "Write a short story" }],
  stream: true
});

for await (const chunk of stream) {
  process.stdout.write(chunk.delta);
}

import { tool } from "@llamaindex/core/tools";
import { z } from "zod";

const weatherTool = tool({
  name: "get_weather",
  description: "Get weather for a location",
  parameters: z.object({
    location: z.string(),
    units: z.enum(["celsius", "fahrenheit"]).optional()
  }),
  execute: async ({ location, units = "celsius" }) => {
    return `Weather in ${location}: 22°${units === "celsius" ? "C" : "F"}`;
  }
});

const response = await llm.chat({
  messages: [{ role: "user", content: "What's the weather in London?" }],
  tools: [weatherTool]
});

const llm = new Anthropic({
  model: "claude-4-5-sonnet",
  additionalChatOptions: {
    thinking: "enabled"  // Enable thinking blocks
  }
});

const response = await llm.chat({
  messages: [{ role: "user", content: "Solve this complex problem..." }]
});

// Access thinking process
if (response.message.options?.thinking) {
  console.log("Thinking:", response.message.options.thinking);
  console.log("Signature:", response.message.options.thinking_signature);
}

const response = await llm.chat({
  messages: [
    {
      role: "user",
      content: [
        { type: "text", text: "Describe this image" },
        {
          type: "image",
          data: imageBase64,
          mimeType: "image/jpeg"  // or png, gif, webp
        }
      ]
    }
  ]
});

const response = await llm.chat({
  messages: [
    {
      role: "user",
      content: [
        { type: "text", text: "Summarize this PDF" },
        {
          type: "file",
          data: pdfBase64,
          mimeType: "application/pdf"
        }
      ]
    }
  ]
});

const response = await llm.chat({
  messages: [
    {
      role: "system",
      content: "You are an expert on this large document...",
      options: {
        cache_control: { type: "ephemeral" }
      }
    },
    { role: "user", content: "What does it say about topic X?" }
  ]
});

ANTHROPIC_API_KEY=sk-ant-...

import { Settings } from "llamaindex";
import { Anthropic } from "@llamaindex/anthropic";

Settings.llm = new Anthropic({
  model: "claude-3-5-sonnet-20241022"
});

const extractionTool = tool({
  name: "extract_info",
  description: "Extract structured information",
  parameters: z.object({
    name: z.string(),
    age: z.number(),
    email: z.string().email()
  }),
  execute: async (data) => data
});

const response = await llm.chat({
  messages: [{ role: "user", content: "Extract: John is 30, [email protected]" }],
  tools: [extractionTool]
});

const response = await llm.chat({
  messages: [
    { role: "system", content: "System prompt" },  // Extracted automatically
    { role: "user", content: "User message" },
    { role: "assistant", content: "Assistant response" },
    { role: "user", content: "Follow-up" }
  ]
});

// ✅ Correct
[
  { role: "user", content: "Message 1" },
  { role: "assistant", content: "Response 1" },
  { role: "user", content: "Message 2" }
]

// ❌ Incorrect - consecutive user messages
[
  { role: "user", content: "Message 1" },
  { role: "user", content: "Message 2" }  // Will be merged automatically
]

try {
  const response = await llm.chat({ messages });
} catch (error) {
  if (error.status === 429) {
    console.error("Rate limit exceeded");
  } else if (error.status === 401) {
    console.error("Invalid API key");
  } else {
    console.error("Error:", error.message);
  }
}