import asyncio import anthropic class AnthropicClient(): def __init__(self, api_key: str): self._client = anthropic.Anthropic(api_key=api_key) @classmethod def new(cls, api_key: str) -> "AnthropicClient": return cls(api_key) def _create_summarise_text_system_prompt( self, complexity_level: str, from_language: str, to_language: str, length_preference="200-400 words", ) -> str: return ( f"You are a language learning content creator.\n" f"The user will provide input, you will generate an engaging realistic summary text in {to_language} " f"at {complexity_level} proficiency level (CEFR scale).\n\n" f"The text you generate will:\n" f"- Contain ONLY the generated text in {to_language}.\n" f"- Be appropriate for a {complexity_level} {to_language} speaker.\n" f"- Never generate inappropriate (hateful, sexual, violent) content. It is preferable to return no text than to generate such content.\n" f"- Speak directly to the reader/listener, adopting the tone and style of a semi-formal news reporter or podcaster.\n" f"- Where appropriate (fluency level, content), use a small number of idiomatic expressions.\n" f"- Be formatted in markdown with paragraphs and line breaks.\n" f"- Be {length_preference} long.\n" f"- Be inspired by the following source material " f"(but written originally in {from_language}):\n\n" ) def _create_prompt_summarise_text( self, source_material: str, ) -> str: return ( f"Source material follows: \n\n" f"{source_material}" ) async def generate_summary_text( self, content_to_summarise: str, complexity_level: str, from_language: str, to_language: str, length_preference="200-400 words") -> str: """Generate text using Anthropic.""" def _call() -> str: message = self._client.messages.create( model="claude-sonnet-4-6", max_tokens=1024, system=self._create_summarise_text_system_prompt( complexity_level=complexity_level, from_language=from_language, to_language=to_language, length_preference=length_preference, ), messages=[ { "role": "user", "content": self._create_prompt_summarise_text( content_to_summarise ) } ], ) return message.content[0].text return await asyncio.to_thread(_call)