| """ |
| summarizer.py |
| Summarizes YouTube transcript text in multiple modes via the Anthropic API. |
| Author: algorembrant |
| """ |
|
|
| from __future__ import annotations |
|
|
| from config import DEFAULT_MODEL, MAX_TOKENS, QUALITY_MODEL |
| from ai_client import complete_long |
|
|
| |
| |
| |
|
|
| _SYSTEM_BASE = """You are an expert content analyst specializing in video transcripts. |
| Your summaries are accurate, concise, and written in clear professional prose. |
| Never hallucinate or add information not present in the transcript. |
| Do not add a preamble or closing statement — output only the requested summary. |
| """ |
|
|
| _MODE_PROMPTS: dict[str, dict[str, str]] = { |
|
|
| "brief": { |
| "system": _SYSTEM_BASE + ( |
| "Write a brief 3-5 sentence executive summary that captures the core message, " |
| "key argument, and main conclusion of the transcript." |
| ), |
| "user_prefix": ( |
| "Write a brief 3-5 sentence executive summary of the following transcript.\n\n" |
| "TRANSCRIPT:" |
| ), |
| }, |
|
|
| "detailed": { |
| "system": _SYSTEM_BASE + ( |
| "Write a detailed, multi-section summary with clearly labeled sections. " |
| "Sections should include: Overview, Key Points, Supporting Details, and Conclusion. " |
| "Each section should be written as flowing prose paragraphs — no bullet points." |
| ), |
| "user_prefix": ( |
| "Write a detailed multi-section summary (Overview, Key Points, Supporting Details, Conclusion) " |
| "of the following transcript. Use flowing prose — no bullet points.\n\n" |
| "TRANSCRIPT:" |
| ), |
| }, |
|
|
| "bullets": { |
| "system": _SYSTEM_BASE + ( |
| "Extract the most important takeaways as a structured bullet list. " |
| "Group bullets under 3-5 thematic headings. Each bullet should be one clear sentence. " |
| "Use markdown bold for headings." |
| ), |
| "user_prefix": ( |
| "Extract the key takeaways from the following transcript as a structured bullet list " |
| "grouped under bold thematic headings.\n\n" |
| "TRANSCRIPT:" |
| ), |
| }, |
|
|
| "outline": { |
| "system": _SYSTEM_BASE + ( |
| "Create a hierarchical topic outline of the transcript. " |
| "Use Roman numerals for top-level topics, capital letters for sub-topics, " |
| "and Arabic numerals for specific points. Keep entries concise (one line each)." |
| ), |
| "user_prefix": ( |
| "Create a hierarchical outline (Roman numerals, sub-letters, sub-numbers) " |
| "of the following transcript.\n\n" |
| "TRANSCRIPT:" |
| ), |
| }, |
| } |
|
|
| _MERGE_SYSTEM = """You are an expert content analyst. |
| You will receive several summary sections from different parts of a long transcript. |
| Merge them into a single cohesive, unified summary in the same format. |
| Remove duplicate points. Maintain a logical flow. Output only the final merged summary. |
| """ |
|
|
|
|
| |
| |
| |
|
|
| def summarize( |
| text: str, |
| mode: str = "brief", |
| model: str = DEFAULT_MODEL, |
| max_tokens: int = MAX_TOKENS, |
| stream: bool = True, |
| ) -> str: |
| """ |
| Summarize a transcript in the specified mode. |
| |
| Args: |
| text: Transcript text (raw or already cleaned). |
| mode: One of 'brief', 'detailed', 'bullets', 'outline'. |
| model: Anthropic model to use. |
| max_tokens: Max output tokens per API call. |
| stream: Stream progress tokens to stderr. |
| |
| Returns: |
| Formatted summary string. |
| """ |
| if not text or not text.strip(): |
| raise ValueError("Cannot summarize an empty transcript.") |
|
|
| if mode not in _MODE_PROMPTS: |
| valid = ", ".join(_MODE_PROMPTS.keys()) |
| raise ValueError(f"Unknown summary mode: {mode!r}. Valid modes: {valid}") |
|
|
| prompts = _MODE_PROMPTS[mode] |
|
|
| |
| |
| return complete_long( |
| system=prompts["system"], |
| user_prefix=prompts["user_prefix"], |
| text=text.strip(), |
| model=model, |
| max_tokens=max_tokens, |
| merge_system=_MERGE_SYSTEM, |
| stream=stream, |
| ) |
|
|
