api-docs

import { type DocEntry } from "./openai";

export const anthropicDocs: DocEntry[] = [
  {
    id: "anthropic-messages",
    title: "Messages API (Claude)",
    category: "chat",
    provider: "anthropic",
    keywords: ["messages", "claude", "chat", "conversation", "anthropic"],
    content: `# Anthropic Messages API (Claude)

## Endpoint
POST https://api.anthropic.com/v1/messages

## Headers
- x-api-key: YOUR_API_KEY
- anthropic-version: 2023-06-01
- content-type: application/json

## Request Body
\`\`\`json
{
  "model": "claude-sonnet-4-20250514" | "claude-3-5-sonnet-20241022" | "claude-3-5-haiku-20241022" | "claude-3-opus-20240229" | "claude-3-haiku-20240307",
  "max_tokens": number (required, max 8192 for most, 64000 for some),
  "messages": [
    {
      "role": "user" | "assistant",
      "content": "string" | [
        {"type": "text", "text": "string"},
        {"type": "image", "source": {"type": "base64", "media_type": "image/jpeg"|"image/png"|"image/gif"|"image/webp", "data": "base64string"}},
        {"type": "document", "source": {"type": "base64", "media_type": "application/pdf", "data": "base64string"}},
        {"type": "tool_result", "tool_use_id": "string", "content": "string"}
      ]
    }
  ],
  "system": "string" | [{"type": "text", "text": "string"}, {"type": "tool_result", ...}],
  "temperature": number (0-1, default varies),
  "top_p": number (0-1),
  "top_k": number (1-40),
  "stop_sequences": string[],
  "stream": boolean,
  "tools": [
    {
      "name": "string",
      "description": "string",
      "input_schema": {JSON Schema object}
    }
  ],
  "tool_choice": {"type": "auto" | "any" | "tool", "name": "string (if type=tool)"},
  "metadata": {"user_id": "string"}
}
\`\`\`

## Response
\`\`\`json
{
  "id": "msg_01xxx",
  "type": "message",
  "role": "assistant",
  "content": [
    {"type": "text", "text": "Hello! How can I help you?"},
    {
      "type": "tool_use",
      "id": "toolu_01xxx",
      "name": "get_weather",
      "input": {"location": "San Francisco"}
    }
  ],
  "model": "claude-sonnet-4-20250514",
  "stop_reason": "end_turn" | "max_tokens" | "stop_sequence" | "tool_use",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 10,
    "output_tokens": 25,
    "cache_creation_input_tokens": 0,
    "cache_read_input_tokens": 0
  }
}
\`\`\`

## Key Differences from OpenAI
1. "system" is a top-level field, not a message role
2. Messages can only be "user" or "assistant" (no "system" role)
3. Tool definitions use "input_schema" instead of "parameters"
4. Tool results use "tool_result" type in content array
5. Response content is an array (can have text + tool_use)
6. Max tokens is REQUIRED in every request

## Available Models (2024-2025)
- claude-sonnet-4-20250514: Latest flagship, best overall
- claude-3-5-sonnet-20241022: Previous flagship, great coding
- claude-3-5-haiku-20241022: Fast, cost-effective
- claude-3-opus-20240229: Most capable (older)
- claude-3-haiku-20240307: Fastest, cheapest

## Python SDK Example
\`\`\`python
import anthropic

client = anthropic.Anthropic(api_key="sk-ant-...")

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    system="You are a helpful assistant",
    messages=[
        {"role": "user", "content": "Hello, Claude!"}
    ],
    temperature=0.7
)

print(message.content[0].text)
\`\`\`

## Node.js SDK Example
\`\`\`javascript
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic({ apiKey: "sk-ant-..." });

const message = await client.messages.create({
  model: "claude-sonnet-4-20250514",
  max_tokens: 1024,
  system: "You are a helpful assistant",
  messages: [
    { role: "user", content: "Hello, Claude!" }
  ],
  temperature: 0.7
});

console.log(message.content[0].text);
\`\`\`

## cURL Example
\`\`\`bash
curl https://api.anthropic.com/v1/messages \\
  -H "x-api-key: $ANTHROPIC_API_KEY" \\
  -H "anthropic-version: 2023-06-01" \\
  -H "content-type: application/json" \\
  -d '{
    "model": "claude-sonnet-4-20250514",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Hello!"}]
  }'
\`\`\``
  },
  {
    id: "anthropic-tools",
    title: "Tool Use (Function Calling)",
    category: "tools",
    provider: "anthropic",
    keywords: ["tools", "function", "tool use", "function calling"],
    content: `# Anthropic Tool Use

## Tool Definition Format
\`\`\`json
{
  "name": "get_weather",
  "description": "Get current weather for a location",
  "input_schema": {
    "type": "object",
    "properties": {
      "location": {
        "type": "string",
        "description": "City name"
      },
      "unit": {
        "type": "string",
        "enum": ["celsius", "fahrenheit"]
      }
    },
    "required": ["location"]
  }
}
\`\`\`

## Tool Choice Options
- {"type": "auto"}: Model decides (default)
- {"type": "any"}: Model MUST use at least one tool
- {"type": "tool", "name": "specific_tool"}: Force specific tool

## Handling Tool Calls
\`\`\`python
import anthropic

client = anthropic.Anthropic()

tools = [
    {
        "name": "get_weather",
        "description": "Get weather for location",
        "input_schema": {
            "type": "object",
            "properties": {
                "location": {"type": "string"},
                "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
            },
            "required": ["location"]
        }
    }
]

response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "What's the weather in London?"}],
    tools=tools
)

# Check for tool use
for content in response.content:
    if content.type == "tool_use":
        tool_name = content.name
        tool_input = content.input
        tool_id = content.id
        
        # Execute tool
        result = get_weather(tool_input["location"])
        
        # Send result back
        response2 = client.messages.create(
            model="claude-sonnet-4-20250514",
            max_tokens=1024,
            messages=[
                {"role": "user", "content": "What's the weather in London?"},
                {"role": "assistant", "content": response.content},
                {
                    "role": "user",
                    "content": [
                        {
                            "type": "tool_result",
                            "tool_use_id": tool_id,
                            "content": str(result)
                        }
                    ]
                }
            ],
            tools=tools
        )
\`\`\`

## Important Notes
- Tool results are sent as "user" role messages
- Tool result content is an array with "tool_result" type
- Each tool_result must include tool_use_id from the tool_use block
- Model can call multiple tools in one response`
  },
  {
    id: "anthropic-vision",
    title: "Vision (Image Input)",
    category: "multimodal",
    provider: "anthropic",
    keywords: ["vision", "image", "picture", "photo", "multimodal"],
    content: `# Anthropic Vision (Image Input)

## Supported Models
All Claude 3+ models support images:
- claude-sonnet-4-20250514
- claude-3-5-sonnet-20241022
- claude-3-5-haiku-20241022
- claude-3-opus-20240229
- claude-3-haiku-20240307

## Image Format
\`\`\`json
{
  "role": "user",
  "content": [
    {"type": "text", "text": "Describe this image"},
    {
      "type": "image",
      "source": {
        "type": "base64",
        "media_type": "image/jpeg" | "image/png" | "image/gif" | "image/webp",
        "data": "base64encodedstring..."
      }
    }
  ]
}
\`\`\`

## Multiple Images
\`\`\`json
{
  "role": "user",
  "content": [
    {"type": "text", "text": "Compare these images"},
    {"type": "image", "source": {"type": "base64", "media_type": "image/jpeg", "data": "..."}},
    {"type": "image", "source": {"type": "base64", "media_type": "image/png", "data": "..."}}
  ]
}
\`\`\`

## Python Example
\`\`\`python
import anthropic
import base64

client = anthropic.Anthropic()

with open("image.jpg", "rb") as f:
    image_data = base64.b64encode(f.read()).decode()

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "What is in this image?"},
            {
                "type": "image",
                "source": {
                    "type": "base64",
                    "media_type": "image/jpeg",
                    "data": image_data
                }
            }
        ]
    }]
)
\`\`\`

## Image Limits
- Max 20 images per request
- Max image size: 10MB each`
  },
  {
    id: "anthropic-prompt-caching",
    title: "Prompt Caching",
    category: "optimization",
    provider: "anthropic",
    keywords: ["cache", "caching", "optimization", "cost"],
    content: `# Anthropic Prompt Caching

## How It Works
Cache prefixes of your prompt (system prompt + early messages) for faster, cheaper responses.

## Usage
Add "cache_control": {"type": "ephemeral"} to content blocks:

\`\`\`python
message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    system=[
        {
            "type": "text",
            "text": "Long system prompt that repeats...",
            "cache_control": {"type": "ephemeral"}
        }
    ],
    messages=[
        {"role": "user", "content": "Hello"}
    ]
)
\`\`\`

## Pricing with Caching
- Cache creation: 25% of input token price (one-time)
- Cache read: 10% of input token price (subsequent)
- Regular input: 100%

## Requirements
- Minimum 1024 tokens for cache prefix
- Cache expires after 5 minutes of inactivity
- Only available on claude-3-5-sonnet and newer models

## Response Usage Fields
- cache_creation_input_tokens: Tokens cached this request
- cache_read_input_tokens: Tokens read from cache`
  },
  {
    id: "anthropic-rate-limits",
    title: "Rate Limits & Pricing",
    category: "limits",
    provider: "anthropic",
    keywords: ["rate limit", "pricing", "cost", "tokens", "limits"],
    content: `# Anthropic Rate Limits & Pricing

## Rate Limits (Tier 1 - Free)
- Requests per minute: 50 RPM
- Tokens per minute: 40,000 TPM
- Tokens per day: 1,000,000

## Higher Tiers
Increase automatically with usage and payment method.

## Pricing (per 1M tokens)
- claude-sonnet-4: Input $3.00, Output $15.00
- claude-3-5-sonnet: Input $3.00, Output $15.00
- claude-3-5-haiku: Input $0.80, Output $4.00
- claude-3-opus: Input $15.00, Output $75.00
- claude-3-haiku: Input $0.25, Output $1.25

## Error Codes
- 400: Bad Request
- 401: Invalid API key
- 403: Permission denied
- 429: Rate limit exceeded
- 500: Internal server error
- 529: Overloaded (temporary)

## Context Windows
- claude-sonnet-4: 200K tokens
- claude-3-5-sonnet: 200K tokens
- claude-3-5-haiku: 200K tokens
- claude-3-opus: 200K tokens
- claude-3-haiku: 200K tokens`
  }
];