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@ -535,7 +535,7 @@ def generate_title_from_summary(summary): |
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messages=[ |
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{"role": "system", "content": ( |
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"Generate a concise, engaging title (under 100 characters) based on this summary, covering food topics. " |
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"Craft it with Upworthy/Buzzfeed flair—think ‘you won’t believe this’ or ‘this is nuts’—for food insiders. " |
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"Craft it with Upworthy/Buzzfeed flair—think 'you won't believe this' or 'this is nuts'—for food insiders. " |
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"Avoid quotes, emojis, special characters, or the words 'elevate', 'elevating', 'elevated'. " |
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"End with a question to spark shares." |
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)}, |
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@ -622,8 +622,8 @@ def insert_link_naturally(summary, source_name, source_url): |
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return summary |
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# Find paragraphs with at least two sentences |
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eligible_paragraphs = [p for p in paragraphs if p.strip() and len(re.split(r'(?<=[.!?])\s+', p.strip())) >= 2] |
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if not eligible_paragraphs: |
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eligible_paragraph_indices = [i for i, p in enumerate(paragraphs) if p.strip() and len(re.split(r'(?<=[.!?])\s+', p.strip())) >= 2] |
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if not eligible_paragraph_indices: |
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logging.warning("No paragraph with multiple sentences found, using fallback.") |
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return append_link_as_fallback(summary, source_name, source_url) |
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@ -636,33 +636,29 @@ def insert_link_naturally(summary, source_name, source_url): |
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best_candidate = None |
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best_score = -1 |
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best_paragraph_idx = None |
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best_paragraph = None |
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# Score each paragraph and sentence for suitability |
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for para in eligible_paragraphs: |
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# Score each eligible paragraph and sentence for suitability |
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for idx in eligible_paragraph_indices: |
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para = paragraphs[idx] |
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sentences = re.split(r'(?<=[.!?])\s+', para.strip()) |
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eligible_sentences = [ |
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(i, s) for i, s in enumerate(sentences) |
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if s.strip() and not s.endswith('?') # Exclude sentences ending with '?' |
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and not s.endswith('!') # Exclude exclamations for smoother integration |
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if s.strip() and not s.endswith('?') and not s.endswith('!') |
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] |
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if not eligible_sentences: |
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continue |
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# Score sentences based on suitability (prefer declarative sentences) |
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for idx, sentence in eligible_sentences: |
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for s_idx, sentence in eligible_sentences: |
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score = 0 |
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# Favor sentences with factual content (simplified heuristic) |
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if any(word in sentence.lower() for word in ["is", "are", "has", "shows", "reveals"]): |
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score += 2 |
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# Prefer longer sentences for better context |
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score += len(sentence.split()) // 5 |
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# Prefer middle sentences for natural flow |
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score += abs(idx - len(sentences) / 2) * -1 # Penalize sentences far from the middle |
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score += abs(s_idx - len(sentences) / 2) * -1 |
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if score > best_score: |
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best_score = score |
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best_candidate = (idx, sentence) |
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best_candidate = (s_idx, sentence) |
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best_paragraph_idx = idx |
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best_paragraph = para |
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if best_candidate is None: |
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@ -676,10 +672,11 @@ def insert_link_naturally(summary, source_name, source_url): |
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formatted_link = link_phrase.format(source=link_pattern) |
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# Insert the link at the end of the selected sentence (no capitalization needed) |
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sentences = re.split(r'(?<=[.!?])\s+', best_paragraph.strip()) |
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new_sentence = f"{sentence.rstrip('.')} {formatted_link}." |
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sentences[sentence_idx] = new_sentence |
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new_para = ' '.join(sentences) |
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paragraphs[paragraphs.index(best_paragraph)] = new_para |
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paragraphs[best_paragraph_idx] = new_para |
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# Rejoin paragraphs with \n\n |
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new_summary = '\n\n'.join(paragraphs) |
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