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