chore: initial public snapshot for github upload
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"""Anthropic Skills API integration"""
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from .transformation import AnthropicSkillsConfig
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__all__ = ["AnthropicSkillsConfig"]
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# Anthropic Skills API Integration
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This module provides comprehensive support for the Anthropic Skills API through LiteLLM.
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## Features
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The Skills API allows you to:
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- **Create skills**: Define reusable AI capabilities
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- **List skills**: Browse all available skills
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- **Get skills**: Retrieve detailed information about a specific skill
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- **Delete skills**: Remove skills that are no longer needed
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## Quick Start
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### Prerequisites
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Set your Anthropic API key:
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```python
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import os
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os.environ["ANTHROPIC_API_KEY"] = "your-api-key-here"
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```
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### Basic Usage
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#### Create a Skill
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```python
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import litellm
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# Create a skill with files
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# Note: All files must be in the same top-level directory
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# and must include a SKILL.md file at the root
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skill = litellm.create_skill(
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files=[
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# List of file objects to upload
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# Must include SKILL.md
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],
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display_title="Python Code Generator",
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custom_llm_provider="anthropic"
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)
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print(f"Created skill: {skill.id}")
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# Asynchronous version
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skill = await litellm.acreate_skill(
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files=[...], # Your files here
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display_title="Python Code Generator",
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custom_llm_provider="anthropic"
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)
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```
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#### List Skills
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```python
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# List all skills
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skills = litellm.list_skills(
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custom_llm_provider="anthropic"
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)
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for skill in skills.data:
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print(f"{skill.display_title}: {skill.id}")
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# With pagination and filtering
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skills = litellm.list_skills(
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limit=20,
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source="custom", # Filter by 'custom' or 'anthropic'
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custom_llm_provider="anthropic"
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)
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# Get next page if available
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if skills.has_more:
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next_page = litellm.list_skills(
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page=skills.next_page,
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custom_llm_provider="anthropic"
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)
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```
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#### Get a Skill
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```python
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skill = litellm.get_skill(
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skill_id="skill_abc123",
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custom_llm_provider="anthropic"
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)
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print(f"Skill: {skill.display_title}")
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print(f"Created: {skill.created_at}")
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print(f"Latest version: {skill.latest_version}")
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print(f"Source: {skill.source}")
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```
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#### Delete a Skill
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```python
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result = litellm.delete_skill(
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skill_id="skill_abc123",
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custom_llm_provider="anthropic"
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)
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print(f"Deleted skill {result.id}, type: {result.type}")
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```
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## API Reference
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### `create_skill()`
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Create a new skill.
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**Parameters:**
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- `files` (List[Any], optional): Files to upload for the skill. All files must be in the same top-level directory and must include a SKILL.md file at the root.
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- `display_title` (str, optional): Display title for the skill
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- `custom_llm_provider` (str, optional): Provider name (default: "anthropic")
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- `extra_headers` (dict, optional): Additional HTTP headers
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- `timeout` (float, optional): Request timeout
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**Returns:**
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- `Skill`: The created skill object
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**Async version:** `acreate_skill()`
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### `list_skills()`
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List all skills.
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**Parameters:**
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- `limit` (int, optional): Number of results to return per page (max 100, default 20)
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- `page` (str, optional): Pagination token for fetching a specific page of results
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- `source` (str, optional): Filter skills by source ('custom' or 'anthropic')
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- `custom_llm_provider` (str, optional): Provider name (default: "anthropic")
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- `extra_headers` (dict, optional): Additional HTTP headers
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- `timeout` (float, optional): Request timeout
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**Returns:**
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- `ListSkillsResponse`: Object containing a list of skills and pagination info
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**Async version:** `alist_skills()`
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### `get_skill()`
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Get a specific skill by ID.
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**Parameters:**
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- `skill_id` (str, required): The skill ID
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- `custom_llm_provider` (str, optional): Provider name (default: "anthropic")
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- `extra_headers` (dict, optional): Additional HTTP headers
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- `timeout` (float, optional): Request timeout
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**Returns:**
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- `Skill`: The requested skill object
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**Async version:** `aget_skill()`
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### `delete_skill()`
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Delete a skill.
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**Parameters:**
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- `skill_id` (str, required): The skill ID to delete
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- `custom_llm_provider` (str, optional): Provider name (default: "anthropic")
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- `extra_headers` (dict, optional): Additional HTTP headers
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- `timeout` (float, optional): Request timeout
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**Returns:**
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- `DeleteSkillResponse`: Object with `id` and `type` fields
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**Async version:** `adelete_skill()`
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## Response Types
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### `Skill`
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Represents a skill from the Anthropic Skills API.
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**Fields:**
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- `id` (str): Unique identifier
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- `created_at` (str): ISO 8601 timestamp
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- `display_title` (str, optional): Display title
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- `latest_version` (str, optional): Latest version identifier
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- `source` (str): Source ("custom" or "anthropic")
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- `type` (str): Object type (always "skill")
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- `updated_at` (str): ISO 8601 timestamp
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### `ListSkillsResponse`
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Response from listing skills.
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**Fields:**
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- `data` (List[Skill]): List of skills
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- `next_page` (str, optional): Pagination token for the next page
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- `has_more` (bool): Whether more skills are available
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### `DeleteSkillResponse`
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Response from deleting a skill.
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**Fields:**
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- `id` (str): The deleted skill ID
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- `type` (str): Deleted object type (always "skill_deleted")
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## Architecture
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The Skills API implementation follows LiteLLM's standard patterns:
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1. **Type Definitions** (`litellm/types/llms/anthropic_skills.py`)
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- Pydantic models for request/response types
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- TypedDict definitions for request parameters
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2. **Base Configuration** (`litellm/llms/base_llm/skills/transformation.py`)
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- Abstract base class `BaseSkillsAPIConfig`
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- Defines transformation interface for provider-specific implementations
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3. **Provider Implementation** (`litellm/llms/anthropic/skills/transformation.py`)
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- `AnthropicSkillsConfig` - Anthropic-specific transformations
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- Handles API authentication, URL construction, and response mapping
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4. **Main Handler** (`litellm/skills/main.py`)
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- Public API functions (sync and async)
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- Request validation and routing
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- Error handling
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5. **HTTP Handlers** (`litellm/llms/custom_httpx/llm_http_handler.py`)
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- Low-level HTTP request/response handling
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- Connection pooling and retry logic
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## Beta API Support
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The Skills API is in beta. The beta header (`skills-2025-10-02`) is automatically added by the Anthropic provider configuration. You can customize it if needed:
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```python
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skill = litellm.create_skill(
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display_title="My Skill",
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extra_headers={
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"anthropic-beta": "skills-2025-10-02" # Or any other beta version
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},
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custom_llm_provider="anthropic"
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)
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```
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The default beta version is configured in `litellm.constants.ANTHROPIC_SKILLS_API_BETA_VERSION`.
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## Error Handling
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All Skills API functions follow LiteLLM's standard error handling:
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```python
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import litellm
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try:
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skill = litellm.create_skill(
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display_title="My Skill",
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custom_llm_provider="anthropic"
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)
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except litellm.exceptions.AuthenticationError as e:
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print(f"Authentication failed: {e}")
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except litellm.exceptions.RateLimitError as e:
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print(f"Rate limit exceeded: {e}")
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except litellm.exceptions.APIError as e:
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print(f"API error: {e}")
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```
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## Contributing
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To add support for Skills API to a new provider:
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1. Create provider-specific configuration class inheriting from `BaseSkillsAPIConfig`
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2. Implement all abstract methods for request/response transformations
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3. Register the config in `ProviderConfigManager.get_provider_skills_api_config()`
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4. Add appropriate tests
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## Related Documentation
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- [Anthropic Skills API Documentation](https://platform.claude.com/docs/en/api/beta/skills/create)
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- [LiteLLM Responses API](../../../responses/)
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- [Provider Configuration System](../../base_llm/)
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## Support
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For issues or questions:
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- GitHub Issues: https://github.com/BerriAI/litellm/issues
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- Discord: https://discord.gg/wuPM9dRgDw
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@@ -0,0 +1,204 @@
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"""
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Anthropic Skills API configuration and transformations
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"""
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from typing import Any, Dict, Optional, Tuple
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import httpx
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from litellm._logging import verbose_logger
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from litellm.llms.base_llm.skills.transformation import (
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BaseSkillsAPIConfig,
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LiteLLMLoggingObj,
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)
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from litellm.types.llms.anthropic_skills import (
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CreateSkillRequest,
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DeleteSkillResponse,
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ListSkillsParams,
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ListSkillsResponse,
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Skill,
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)
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from litellm.types.router import GenericLiteLLMParams
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from litellm.types.utils import LlmProviders
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class AnthropicSkillsConfig(BaseSkillsAPIConfig):
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"""Anthropic-specific Skills API configuration"""
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@property
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def custom_llm_provider(self) -> LlmProviders:
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return LlmProviders.ANTHROPIC
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def validate_environment(
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self, headers: dict, litellm_params: Optional[GenericLiteLLMParams]
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) -> dict:
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"""Add Anthropic-specific headers"""
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from litellm.llms.anthropic.common_utils import AnthropicModelInfo
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# Get API key
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api_key = None
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if litellm_params:
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api_key = litellm_params.api_key
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api_key = AnthropicModelInfo.get_api_key(api_key)
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if not api_key:
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raise ValueError("ANTHROPIC_API_KEY is required for Skills API")
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# Add required headers
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headers["x-api-key"] = api_key
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headers["anthropic-version"] = "2023-06-01"
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# Add beta header for skills API
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from litellm.constants import ANTHROPIC_SKILLS_API_BETA_VERSION
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if "anthropic-beta" not in headers:
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headers["anthropic-beta"] = ANTHROPIC_SKILLS_API_BETA_VERSION
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elif isinstance(headers["anthropic-beta"], list):
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if ANTHROPIC_SKILLS_API_BETA_VERSION not in headers["anthropic-beta"]:
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headers["anthropic-beta"].append(ANTHROPIC_SKILLS_API_BETA_VERSION)
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elif isinstance(headers["anthropic-beta"], str):
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if ANTHROPIC_SKILLS_API_BETA_VERSION not in headers["anthropic-beta"]:
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headers["anthropic-beta"] = [
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headers["anthropic-beta"],
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ANTHROPIC_SKILLS_API_BETA_VERSION,
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]
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headers["content-type"] = "application/json"
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return headers
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def get_complete_url(
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self,
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api_base: Optional[str],
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endpoint: str,
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skill_id: Optional[str] = None,
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) -> str:
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"""Get complete URL for Anthropic Skills API"""
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from litellm.llms.anthropic.common_utils import AnthropicModelInfo
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if api_base is None:
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api_base = AnthropicModelInfo.get_api_base()
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if skill_id:
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return f"{api_base}/v1/skills/{skill_id}"
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return f"{api_base}/v1/{endpoint}"
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def transform_create_skill_request(
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self,
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create_request: CreateSkillRequest,
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litellm_params: GenericLiteLLMParams,
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headers: dict,
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) -> Dict:
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"""Transform create skill request for Anthropic"""
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verbose_logger.debug("Transforming create skill request: %s", create_request)
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# Anthropic expects the request body directly
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request_body = {k: v for k, v in create_request.items() if v is not None}
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return request_body
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def transform_create_skill_response(
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self,
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raw_response: httpx.Response,
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logging_obj: LiteLLMLoggingObj,
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) -> Skill:
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"""Transform Anthropic response to Skill object"""
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response_json = raw_response.json()
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verbose_logger.debug("Transforming create skill response: %s", response_json)
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return Skill(**response_json)
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def transform_list_skills_request(
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self,
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list_params: ListSkillsParams,
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litellm_params: GenericLiteLLMParams,
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headers: dict,
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) -> Tuple[str, Dict]:
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"""Transform list skills request for Anthropic"""
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from litellm.llms.anthropic.common_utils import AnthropicModelInfo
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api_base = AnthropicModelInfo.get_api_base(
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litellm_params.api_base if litellm_params else None
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)
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url = self.get_complete_url(api_base=api_base, endpoint="skills")
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# Build query parameters
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query_params: Dict[str, Any] = {}
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if "limit" in list_params and list_params["limit"]:
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query_params["limit"] = list_params["limit"]
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if "page" in list_params and list_params["page"]:
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query_params["page"] = list_params["page"]
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if "source" in list_params and list_params["source"]:
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query_params["source"] = list_params["source"]
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verbose_logger.debug(
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"List skills request made to Anthropic Skills endpoint with params: %s",
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query_params,
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)
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return url, query_params
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def transform_list_skills_response(
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self,
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raw_response: httpx.Response,
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logging_obj: LiteLLMLoggingObj,
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) -> ListSkillsResponse:
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"""Transform Anthropic response to ListSkillsResponse"""
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response_json = raw_response.json()
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verbose_logger.debug("Transforming list skills response: %s", response_json)
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return ListSkillsResponse(**response_json)
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def transform_get_skill_request(
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self,
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skill_id: str,
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api_base: str,
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litellm_params: GenericLiteLLMParams,
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headers: dict,
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) -> Tuple[str, Dict]:
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"""Transform get skill request for Anthropic"""
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url = self.get_complete_url(
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api_base=api_base, endpoint="skills", skill_id=skill_id
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)
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verbose_logger.debug("Get skill request - URL: %s", url)
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return url, headers
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def transform_get_skill_response(
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self,
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raw_response: httpx.Response,
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logging_obj: LiteLLMLoggingObj,
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) -> Skill:
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"""Transform Anthropic response to Skill object"""
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response_json = raw_response.json()
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verbose_logger.debug("Transforming get skill response: %s", response_json)
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return Skill(**response_json)
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def transform_delete_skill_request(
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self,
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skill_id: str,
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api_base: str,
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litellm_params: GenericLiteLLMParams,
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headers: dict,
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) -> Tuple[str, Dict]:
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"""Transform delete skill request for Anthropic"""
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url = self.get_complete_url(
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api_base=api_base, endpoint="skills", skill_id=skill_id
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)
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verbose_logger.debug("Delete skill request - URL: %s", url)
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return url, headers
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def transform_delete_skill_response(
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self,
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raw_response: httpx.Response,
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logging_obj: LiteLLMLoggingObj,
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) -> DeleteSkillResponse:
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"""Transform Anthropic response to DeleteSkillResponse"""
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response_json = raw_response.json()
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verbose_logger.debug("Transforming delete skill response: %s", response_json)
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return DeleteSkillResponse(**response_json)
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