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Update app.py
Browse files
app.py
CHANGED
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@@ -25,9 +25,7 @@ class WebpageContentProcessor:
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response = requests.get(url, timeout=10) # Add a timeout for robustness
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response.raise_for_status() # Raise an HTTPError for bad responses (4xx or 5xx)
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html_content = response.text
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-
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soup = BeautifulSoup(html_content, 'html.parser')
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-
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# Aggressive initial removal of script, style, and meta tags that are never content.
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for tag_name in ['script', 'style', 'noscript', 'meta', 'link']:
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for element in soup.find_all(tag_name):
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@@ -41,23 +39,23 @@ class WebpageContentProcessor:
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soup.find('div', {'role': 'main'})
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# Fallback logic if main content container wasn't found
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if not content_for_conversion:
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-
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-
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candidate_container = first_h1.parent
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found_main_wrapper_via_h1_parent = False
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# Check up to 5 parent levels for a suitable content wrapper
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for _ in range(5):
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break
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-
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any(cls in candidate_container.get('class', []) for cls in ['content', 'post-body', 'article-content', 'entry-content', 'main-content']) or \
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candidate_container.get('role') == 'main':
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content_for_conversion = candidate_container
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found_main_wrapper_via_h1_parent = True
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break
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-
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-
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# If no clear wrapper found via H1's parent, take H1 and its direct siblings as a fallback
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if not found_main_wrapper_via_h1_parent:
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temp_soup = BeautifulSoup('', 'html.parser')
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@@ -67,7 +65,7 @@ class WebpageContentProcessor:
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temp_soup.append(current_element)
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current_element = current_element.next_sibling
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content_for_conversion = temp_soup
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-
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# Ultimate fallback: use the entire body if no specific content tags or H1 found
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content_for_conversion = soup.body
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@@ -81,7 +79,7 @@ class WebpageContentProcessor:
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'map', 'area', 'embed', 'object', 'param', 'applet', 'bgsound', 'frame',
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'frameset', 'noframes', 'template', 'slot', 'portal', 'datalist', 'keygen',
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'output', 'progress', 'meter', 'details', 'summary', 'dialog', 'menu',
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'menuitem', 'command', 'hr', 'figure', 'figcaption', 'cite',
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'.social-share', '.comments', '.related-posts', '.pagination',
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'.breadcrumbs', '.pop-up', '.modal', '.overlay', '.cookie-consent',
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'[role="navigation"]', '[role="banner"]', '[role="contentinfo"]',
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@@ -90,26 +88,26 @@ class WebpageContentProcessor:
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'[class*="announcement"]', '[class*="fixed-bottom"]', '[class*="fixed-top"]',
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'[id*="promo"]', '[id*="ad"]', '[id*="banner"]', '[id*="popup"]', '[id*="modal"]',
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'[id*="overlay"]', '[id*="cookie"]', '[id*="skip"]', '[id*="navbar"]', '[id*="menu"]',
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'.hidden', '.visually-hidden',
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'.no-print', '.print-hide',
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'.wp-block-navigation', '.wp-block-group.is-style-stripes',
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'[class*="column"]', '[class*="grid"]'
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for selector in unwanted_elements_in_content:
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if re.match(r'^[a-zA-Z0-9]+$', selector):
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element.decompose()
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else:
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element.decompose()
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-
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markdown_output = convert_to_markdown(str(content_for_conversion))
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# Post-processing: Clean up resulting Markdown
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markdown_output = re.sub(r'\n\s*\n\s*\n+', '\n\n', markdown_output)
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markdown_output = re.sub(r'^\s*[\*\-]\s*$', '', markdown_output, flags=re.MULTILINE)
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markdown_output = re.sub(r'\*{3,}', '', markdown_output)
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markdown_output = markdown_output.strip()
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return markdown_output
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@@ -135,21 +133,19 @@ class WebpageContentProcessor:
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print(f"✅ Parsed {len(nodes)} nodes from Markdown.") # Debug print
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structured_chunks = []
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current_id = 0
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for node in nodes:
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pure_text_content = node.get_content(metadata_mode=MetadataMode.NONE).strip()
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-
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heading_title = ""
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content_text = pure_text_content
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heading_match = re.match(r"^(#+)\s*(.*)", pure_text_content)
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if heading_match:
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heading_title = heading_match.group(2).strip()
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content_text = pure_text_content[len(heading_match.group(0)):].strip()
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if not heading_title:
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else:
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first_line = content_text.split('\n')[0].strip()
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heading_title = first_line[:70].strip() + "..." if len(first_line) > 70 else first_line
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@@ -165,7 +161,7 @@ class WebpageContentProcessor:
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"original_node": node # Keep reference to the original LlamaIndex node
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})
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current_id += 1
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-
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return structured_chunks
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class ChunkManager:
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@@ -198,14 +194,14 @@ class ChunkManager:
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(Private helper method, SRP for stats calculation)
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"""
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stats = {}
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cleaned_text = re.sub(r'#+\s*', '', text)
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cleaned_text = re.sub(r'[\*\-]\s*', '', cleaned_text)
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cleaned_text = re.sub(r'\n\s*\n+', ' ', cleaned_text).strip()
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stats['word_count'] = textstat.lexicon_count(cleaned_text, removepunct=True)
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stats['char_count'] = len(cleaned_text)
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stats['sentence_count'] = textstat.sentence_count(cleaned_text)
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if stats['sentence_count'] > 0:
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stats['avg_sentence_length'] = stats['word_count'] / stats['sentence_count']
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else:
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@@ -217,17 +213,16 @@ class ChunkManager:
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stats['flesch_reading_ease'] = textstat.flesch_reading_ease(cleaned_text)
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except Exception:
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stats['flesch_reading_ease'] = 0
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-
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try:
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stats['flesch_kincaid_grade'] = textstat.flesch_kincaid_grade(cleaned_text)
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except Exception:
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stats['flesch_kincaid_grade'] = 0
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-
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try:
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stats['gunning_fog_score'] = textstat.gunning_fog(cleaned_text)
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except Exception:
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stats['gunning_fog_score'] = 0
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-
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return stats
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def format_chunk_stats(self, stats: dict) -> str:
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@@ -262,7 +257,7 @@ class ChunkManager:
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total_chars = 0
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total_sentences = 0
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total_paragraphs = 0
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-
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all_content_text = ""
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for chunk in self._chunks:
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content_text_for_stats = chunk['content']
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@@ -280,10 +275,10 @@ class ChunkManager:
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doc_stats_str += f"- **Total Characters:** {total_chars}\n"
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doc_stats_str += f"- **Total Sentences:** {total_sentences}\n"
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doc_stats_str += f"- **Total Paragraphs:** {total_paragraphs}\n"
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-
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if len(self._chunks) > 0:
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doc_stats_str += f"- **Average Words per Chunk:** {total_words / len(self._chunks):.2f}\n"
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-
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if all_content_text.strip():
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overall_stats = self._calculate_chunk_stats(all_content_text)
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doc_stats_str += f"- **Overall Flesch Reading Ease:** {overall_stats['flesch_reading_ease']:.2f}\n"
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doc_stats_str += f"- **Overall Average Sentence Length:** {overall_stats['avg_sentence_length']:.2f} words\n"
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else:
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doc_stats_str += "- No content available for overall readability metrics.\n"
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-
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return doc_stats_str
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def get_chunk_by_id(self, chunk_id: int) -> dict | None:
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@@ -336,25 +330,21 @@ class ChunkManager:
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self._chunks = [chunk for chunk in self._chunks if chunk["id"] != chunk_id]
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if len(self._chunks) == initial_chunk_count:
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return False # Chunk not found
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-
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# Re-index IDs to be sequential again
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for i, chunk in enumerate(self._chunks):
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chunk['id'] = i
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-
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return True
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-
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def get_final_markdown(self) -> str:
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"""Compiles all current chunks into a single Markdown string."""
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final_md = ""
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if not self._chunks:
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return "No content to compile. Please process a URL first."
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-
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for chunk in self._chunks:
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# Use H1 heading if title is meaningful
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if not chunk["title"].startswith("[") and chunk["title"]:
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final_md += f"# {chunk['title']}\n\n"
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final_md += f"{chunk['content']}\n\n"
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-
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return final_md.strip()
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def set_targets(self, flesch_min: float, grade_max: float, min_words: int, max_words: int):
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@@ -365,7 +355,7 @@ class ChunkManager:
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self.target_max_chunk_words = max_words
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# Recalculate stats for all chunks to reflect new targets in color coding (if displayed)
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for chunk in self._chunks:
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chunk['stats'] = self._calculate_chunk_stats(chunk['content'])
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# --- Streamlit UI Definition ---
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st.set_page_config(layout="wide", page_title="Chunk-Powered Webpage Editor")
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@@ -384,35 +374,23 @@ if 'chunk_content_editor' not in st.session_state:
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if 'final_markdown' not in st.session_state:
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st.session_state.final_markdown = "Click 'Compile All Chunks' to see the final document with your edits."
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-
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# Instantiate the managers
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content_processor = st.session_state.content_processor
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chunk_manager = st.session_state.chunk_manager
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st.markdown("# <center>✨ Chunk-Powered Webpage Editor ✨</center>", unsafe_allow_html=True)
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st.markdown("""
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Review statistics, set targets, edit chunks, and compile your final Markdown.
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<br>
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<div style="font-size: 0.9em; margin-bottom: 12px;">
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Inspired by <a href="https://www.linkedin.com/pulse/understanding-chunking-google-ai-mode-practical-content-volpini-zseaf/" target="_blank">Andrea Volpini</a>
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</div>
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<div style="display: flex; justify-content: flex-start; align-items: center; gap: 16px;">
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<span>Runs best on Desktop. App created by <a href="https://www.linkedin.com/in/emilijagjorgjevska/" target="_blank">Emilija Gjorgjevska</a></span>
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<a href="https://buymeacoffee.com/emiliagjorgjevska" target="_blank">
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<img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 30px;">
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</a>
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<br>
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""", unsafe_allow_html=True)
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# --- URL Input and Processing ---
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col1, col2 = st.columns([4, 1])
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with col1:
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url_input = st.text_input(
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label="Enter Webpage URL",
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placeholder="e.g., https://www.llamaindex.ai/blog/what-is-llamaindex",
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key="url_input"
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)
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@@ -430,7 +408,7 @@ if process_button:
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else:
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with st.spinner("Processing URL..."):
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markdown_content = content_processor.fetch_and_convert_to_markdown(url_input)
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-
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if "Error" in markdown_content:
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chunk_manager.set_chunks([])
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st.session_state.status_message = markdown_content
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chunks = content_processor.parse_markdown_into_chunks(markdown_content)
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chunk_manager.set_chunks(chunks)
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st.session_state.status_message = "URL processed successfully!" if chunks else "URL processed, but no content chunks could be extracted."
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-
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if chunks:
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st.session_state.chunk_selector = chunk_manager.get_chunk_titles_for_dropdown()[0]
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else:
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st.session_state.chunk_selector = None
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-
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# --- Tabs for Editor and Overview ---
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tab1, tab2 = st.tabs(["Editor", "Document Overview & Targets"])
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with tab1:
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st.markdown("## Edit Chunks Individually")
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col1, col2 = st.columns([2, 1])
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with col1:
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chunk_selector_options = chunk_manager.get_chunk_titles_for_dropdown()
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if chunk_selector_options:
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try:
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# Find the index of the currently selected item to handle updates
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current_selection_index = chunk_selector_options.index(st.session_state.chunk_selector)
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except (ValueError, TypeError):
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current_selection_index = 0
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-
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selected_chunk_title = st.selectbox(
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label="Select Chunk to Edit",
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options=chunk_selector_options,
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index=current_selection_index,
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key="chunk_selector"
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)
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else:
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selected_chunk_title = st.selectbox(
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label="Select Chunk to Edit",
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options=["No chunks available"],
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disabled=True
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)
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# Get the currently selected chunk
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selected_chunk = None
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@@ -507,14 +461,14 @@ with tab1:
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value=selected_chunk["title"],
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disabled=True
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)
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-
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chunk_content_editor = st.text_area(
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label="Chunk Content",
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value=selected_chunk["content"],
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height=250,
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key=f"editor_{selected_chunk['id']}" # Unique key to prevent state loss
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)
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-
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st.markdown(
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chunk_manager.format_chunk_stats(selected_chunk['stats']),
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unsafe_allow_html=True
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@@ -537,15 +491,13 @@ with tab1:
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else:
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st.session_state.chunk_selector = None
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-
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else:
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st.text_input("Chunk Title (Auto-detected)", "Title of the selected chunk", disabled=True)
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st.text_area("Chunk Content", "Content of the selected chunk will appear here for editing.", height=250, disabled=True)
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st.markdown("Chunk statistics will appear here.")
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-
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st.markdown("---")
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st.markdown("## Final Compiled Markdown")
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-
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if st.button("Compile All Chunks", use_container_width=True):
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st.session_state.final_markdown = chunk_manager.get_final_markdown()
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@@ -556,11 +508,10 @@ with tab1:
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key="final_markdown_output",
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disabled=False
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)
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-
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with tab2:
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st.markdown("## Document Summary Statistics")
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st.markdown(chunk_manager.get_document_summary_stats(), unsafe_allow_html=True)
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-
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st.markdown("---")
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st.markdown("## Content Targets")
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st.markdown("Adjust these targets to guide your writing and see visual feedback in the chunk selector (green=good, red=needs attention).")
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@@ -573,13 +524,13 @@ with tab2:
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with col2:
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target_grade_max_input = st.number_input("Max Flesch-Kincaid Grade", value=float(chunk_manager.target_grade_max))
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target_max_chunk_words_input = st.number_input("Max Chunk Words", value=chunk_manager.target_max_chunk_words)
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-
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submitted = st.form_submit_button("Set New Targets", use_container_width=True)
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if submitted:
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chunk_manager.set_targets(
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target_flesch_min_input,
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target_grade_max_input,
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int(target_min_chunk_words_input),
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int(target_max_chunk_words_input)
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)
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st.session_state.status_message = "Target settings updated."
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response = requests.get(url, timeout=10) # Add a timeout for robustness
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response.raise_for_status() # Raise an HTTPError for bad responses (4xx or 5xx)
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html_content = response.text
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soup = BeautifulSoup(html_content, 'html.parser')
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# Aggressive initial removal of script, style, and meta tags that are never content.
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for tag_name in ['script', 'style', 'noscript', 'meta', 'link']:
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for element in soup.find_all(tag_name):
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soup.find('div', {'role': 'main'})
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# Fallback logic if main content container wasn't found
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+
if not content_for_conversion:
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+
first_h1 = soup.find('h1')
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+
if first_h1:
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candidate_container = first_h1.parent
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found_main_wrapper_via_h1_parent = False
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# Check up to 5 parent levels for a suitable content wrapper
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+
for _ in range(5):
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if candidate_container is None:
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break
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if candidate_container.name in ['article', 'main', 'section', 'div'] and \
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any(cls in candidate_container.get('class', []) for cls in ['content', 'post-body', 'article-content', 'entry-content', 'main-content']) or \
|
| 53 |
candidate_container.get('role') == 'main':
|
| 54 |
content_for_conversion = candidate_container
|
| 55 |
found_main_wrapper_via_h1_parent = True
|
| 56 |
break
|
| 57 |
+
candidate_container = candidate_container.parent
|
| 58 |
+
|
| 59 |
# If no clear wrapper found via H1's parent, take H1 and its direct siblings as a fallback
|
| 60 |
if not found_main_wrapper_via_h1_parent:
|
| 61 |
temp_soup = BeautifulSoup('', 'html.parser')
|
|
|
|
| 65 |
temp_soup.append(current_element)
|
| 66 |
current_element = current_element.next_sibling
|
| 67 |
content_for_conversion = temp_soup
|
| 68 |
+
else:
|
| 69 |
# Ultimate fallback: use the entire body if no specific content tags or H1 found
|
| 70 |
content_for_conversion = soup.body
|
| 71 |
|
|
|
|
| 79 |
'map', 'area', 'embed', 'object', 'param', 'applet', 'bgsound', 'frame',
|
| 80 |
'frameset', 'noframes', 'template', 'slot', 'portal', 'datalist', 'keygen',
|
| 81 |
'output', 'progress', 'meter', 'details', 'summary', 'dialog', 'menu',
|
| 82 |
+
'menuitem', 'command', 'hr', 'figure', 'figcaption', 'cite',
|
| 83 |
'.social-share', '.comments', '.related-posts', '.pagination',
|
| 84 |
'.breadcrumbs', '.pop-up', '.modal', '.overlay', '.cookie-consent',
|
| 85 |
'[role="navigation"]', '[role="banner"]', '[role="contentinfo"]',
|
|
|
|
| 88 |
'[class*="announcement"]', '[class*="fixed-bottom"]', '[class*="fixed-top"]',
|
| 89 |
'[id*="promo"]', '[id*="ad"]', '[id*="banner"]', '[id*="popup"]', '[id*="modal"]',
|
| 90 |
'[id*="overlay"]', '[id*="cookie"]', '[id*="skip"]', '[id*="navbar"]', '[id*="menu"]',
|
| 91 |
+
'.hidden', '.visually-hidden',
|
| 92 |
+
'.no-print', '.print-hide',
|
| 93 |
+
'.wp-block-navigation', '.wp-block-group.is-style-stripes',
|
| 94 |
+
'[class*="column"]', '[class*="grid"]'
|
| 95 |
+
]
|
| 96 |
|
| 97 |
for selector in unwanted_elements_in_content:
|
| 98 |
+
if re.match(r'^[a-zA-Z0-9]+$', selector):
|
| 99 |
+
for element in content_for_conversion.find_all(selector):
|
| 100 |
element.decompose()
|
| 101 |
+
else:
|
| 102 |
+
for element in content_for_conversion.select(selector):
|
| 103 |
element.decompose()
|
| 104 |
+
|
| 105 |
markdown_output = convert_to_markdown(str(content_for_conversion))
|
| 106 |
|
| 107 |
# Post-processing: Clean up resulting Markdown
|
| 108 |
markdown_output = re.sub(r'\n\s*\n\s*\n+', '\n\n', markdown_output)
|
| 109 |
markdown_output = re.sub(r'^\s*[\*\-]\s*$', '', markdown_output, flags=re.MULTILINE)
|
| 110 |
+
markdown_output = re.sub(r'\*{3,}', '', markdown_output)
|
| 111 |
markdown_output = markdown_output.strip()
|
| 112 |
|
| 113 |
return markdown_output
|
|
|
|
| 133 |
print(f"✅ Parsed {len(nodes)} nodes from Markdown.") # Debug print
|
| 134 |
|
| 135 |
structured_chunks = []
|
| 136 |
+
current_id = 0
|
| 137 |
|
| 138 |
for node in nodes:
|
| 139 |
pure_text_content = node.get_content(metadata_mode=MetadataMode.NONE).strip()
|
|
|
|
| 140 |
heading_title = ""
|
| 141 |
content_text = pure_text_content
|
| 142 |
|
| 143 |
heading_match = re.match(r"^(#+)\s*(.*)", pure_text_content)
|
|
|
|
| 144 |
if heading_match:
|
| 145 |
heading_title = heading_match.group(2).strip()
|
| 146 |
content_text = pure_text_content[len(heading_match.group(0)):].strip()
|
| 147 |
+
if not heading_title:
|
| 148 |
+
heading_title = "[Untitled Section]"
|
| 149 |
else:
|
| 150 |
first_line = content_text.split('\n')[0].strip()
|
| 151 |
heading_title = first_line[:70].strip() + "..." if len(first_line) > 70 else first_line
|
|
|
|
| 161 |
"original_node": node # Keep reference to the original LlamaIndex node
|
| 162 |
})
|
| 163 |
current_id += 1
|
| 164 |
+
|
| 165 |
return structured_chunks
|
| 166 |
|
| 167 |
class ChunkManager:
|
|
|
|
| 194 |
(Private helper method, SRP for stats calculation)
|
| 195 |
"""
|
| 196 |
stats = {}
|
| 197 |
+
cleaned_text = re.sub(r'#+\s*', '', text)
|
| 198 |
+
cleaned_text = re.sub(r'[\*\-]\s*', '', cleaned_text)
|
| 199 |
+
cleaned_text = re.sub(r'\n\s*\n+', ' ', cleaned_text).strip()
|
| 200 |
|
| 201 |
stats['word_count'] = textstat.lexicon_count(cleaned_text, removepunct=True)
|
| 202 |
stats['char_count'] = len(cleaned_text)
|
| 203 |
stats['sentence_count'] = textstat.sentence_count(cleaned_text)
|
| 204 |
+
|
| 205 |
if stats['sentence_count'] > 0:
|
| 206 |
stats['avg_sentence_length'] = stats['word_count'] / stats['sentence_count']
|
| 207 |
else:
|
|
|
|
| 213 |
stats['flesch_reading_ease'] = textstat.flesch_reading_ease(cleaned_text)
|
| 214 |
except Exception:
|
| 215 |
stats['flesch_reading_ease'] = 0
|
| 216 |
+
|
| 217 |
try:
|
| 218 |
stats['flesch_kincaid_grade'] = textstat.flesch_kincaid_grade(cleaned_text)
|
| 219 |
except Exception:
|
| 220 |
stats['flesch_kincaid_grade'] = 0
|
| 221 |
+
|
| 222 |
try:
|
| 223 |
stats['gunning_fog_score'] = textstat.gunning_fog(cleaned_text)
|
| 224 |
except Exception:
|
| 225 |
stats['gunning_fog_score'] = 0
|
|
|
|
| 226 |
return stats
|
| 227 |
|
| 228 |
def format_chunk_stats(self, stats: dict) -> str:
|
|
|
|
| 257 |
total_chars = 0
|
| 258 |
total_sentences = 0
|
| 259 |
total_paragraphs = 0
|
| 260 |
+
|
| 261 |
all_content_text = ""
|
| 262 |
for chunk in self._chunks:
|
| 263 |
content_text_for_stats = chunk['content']
|
|
|
|
| 275 |
doc_stats_str += f"- **Total Characters:** {total_chars}\n"
|
| 276 |
doc_stats_str += f"- **Total Sentences:** {total_sentences}\n"
|
| 277 |
doc_stats_str += f"- **Total Paragraphs:** {total_paragraphs}\n"
|
| 278 |
+
|
| 279 |
if len(self._chunks) > 0:
|
| 280 |
doc_stats_str += f"- **Average Words per Chunk:** {total_words / len(self._chunks):.2f}\n"
|
| 281 |
+
|
| 282 |
if all_content_text.strip():
|
| 283 |
overall_stats = self._calculate_chunk_stats(all_content_text)
|
| 284 |
doc_stats_str += f"- **Overall Flesch Reading Ease:** {overall_stats['flesch_reading_ease']:.2f}\n"
|
|
|
|
| 287 |
doc_stats_str += f"- **Overall Average Sentence Length:** {overall_stats['avg_sentence_length']:.2f} words\n"
|
| 288 |
else:
|
| 289 |
doc_stats_str += "- No content available for overall readability metrics.\n"
|
|
|
|
| 290 |
return doc_stats_str
|
| 291 |
|
| 292 |
def get_chunk_by_id(self, chunk_id: int) -> dict | None:
|
|
|
|
| 330 |
self._chunks = [chunk for chunk in self._chunks if chunk["id"] != chunk_id]
|
| 331 |
if len(self._chunks) == initial_chunk_count:
|
| 332 |
return False # Chunk not found
|
|
|
|
| 333 |
# Re-index IDs to be sequential again
|
| 334 |
for i, chunk in enumerate(self._chunks):
|
| 335 |
chunk['id'] = i
|
|
|
|
| 336 |
return True
|
| 337 |
+
|
| 338 |
def get_final_markdown(self) -> str:
|
| 339 |
"""Compiles all current chunks into a single Markdown string."""
|
| 340 |
final_md = ""
|
| 341 |
if not self._chunks:
|
| 342 |
return "No content to compile. Please process a URL first."
|
|
|
|
| 343 |
for chunk in self._chunks:
|
| 344 |
# Use H1 heading if title is meaningful
|
| 345 |
if not chunk["title"].startswith("[") and chunk["title"]:
|
| 346 |
final_md += f"# {chunk['title']}\n\n"
|
| 347 |
final_md += f"{chunk['content']}\n\n"
|
|
|
|
| 348 |
return final_md.strip()
|
| 349 |
|
| 350 |
def set_targets(self, flesch_min: float, grade_max: float, min_words: int, max_words: int):
|
|
|
|
| 355 |
self.target_max_chunk_words = max_words
|
| 356 |
# Recalculate stats for all chunks to reflect new targets in color coding (if displayed)
|
| 357 |
for chunk in self._chunks:
|
| 358 |
+
chunk['stats'] = self._calculate_chunk_stats(chunk['content'])
|
| 359 |
|
| 360 |
# --- Streamlit UI Definition ---
|
| 361 |
st.set_page_config(layout="wide", page_title="Chunk-Powered Webpage Editor")
|
|
|
|
| 374 |
if 'final_markdown' not in st.session_state:
|
| 375 |
st.session_state.final_markdown = "Click 'Compile All Chunks' to see the final document with your edits."
|
| 376 |
|
|
|
|
| 377 |
# Instantiate the managers
|
| 378 |
content_processor = st.session_state.content_processor
|
| 379 |
chunk_manager = st.session_state.chunk_manager
|
| 380 |
|
| 381 |
st.markdown("# <center>✨ Chunk-Powered Webpage Editor ✨</center>", unsafe_allow_html=True)
|
| 382 |
+
st.markdown("""Enter a URL, fetch its content, and break it into editable 'chunks'. Review statistics, set targets, edit chunks, and compile your final Markdown.<br><div style="font-size: 0.9em; margin-bottom: 12px;">
|
| 383 |
+
Inspired by <a href="https://www.linkedin.com/pulse/understanding-chunking-google-ai-mode-practical-content-volpini-zseaf/" target="_blank">Andrea Volpini</a></div><div style="display: flex; justify-content: flex-start; align-items: center; gap: 16px;">
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 384 |
<span>Runs best on Desktop. App created by <a href="https://www.linkedin.com/in/emilijagjorgjevska/" target="_blank">Emilija Gjorgjevska</a></span>
|
| 385 |
<a href="https://buymeacoffee.com/emiliagjorgjevska" target="_blank">
|
| 386 |
<img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 30px;">
|
| 387 |
+
</a></div><br>""", unsafe_allow_html=True)
|
| 388 |
+
|
|
|
|
|
|
|
| 389 |
# --- URL Input and Processing ---
|
| 390 |
col1, col2 = st.columns([4, 1])
|
| 391 |
with col1:
|
| 392 |
url_input = st.text_input(
|
| 393 |
+
label="Enter Webpage URL",
|
| 394 |
placeholder="e.g., https://www.llamaindex.ai/blog/what-is-llamaindex",
|
| 395 |
key="url_input"
|
| 396 |
)
|
|
|
|
| 408 |
else:
|
| 409 |
with st.spinner("Processing URL..."):
|
| 410 |
markdown_content = content_processor.fetch_and_convert_to_markdown(url_input)
|
| 411 |
+
|
| 412 |
if "Error" in markdown_content:
|
| 413 |
chunk_manager.set_chunks([])
|
| 414 |
st.session_state.status_message = markdown_content
|
|
|
|
| 416 |
chunks = content_processor.parse_markdown_into_chunks(markdown_content)
|
| 417 |
chunk_manager.set_chunks(chunks)
|
| 418 |
st.session_state.status_message = "URL processed successfully!" if chunks else "URL processed, but no content chunks could be extracted."
|
| 419 |
+
|
| 420 |
if chunks:
|
| 421 |
st.session_state.chunk_selector = chunk_manager.get_chunk_titles_for_dropdown()[0]
|
| 422 |
else:
|
| 423 |
st.session_state.chunk_selector = None
|
| 424 |
|
|
|
|
| 425 |
# --- Tabs for Editor and Overview ---
|
| 426 |
tab1, tab2 = st.tabs(["Editor", "Document Overview & Targets"])
|
| 427 |
|
| 428 |
with tab1:
|
| 429 |
st.markdown("## Edit Chunks Individually")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 430 |
|
| 431 |
+
chunk_selector_options = chunk_manager.get_chunk_titles_for_dropdown()
|
| 432 |
+
if chunk_selector_options:
|
| 433 |
+
try:
|
| 434 |
+
# Find the index of the currently selected item to handle updates
|
| 435 |
+
current_selection_index = chunk_selector_options.index(st.session_state.chunk_selector)
|
| 436 |
+
except (ValueError, TypeError):
|
| 437 |
+
current_selection_index = 0
|
| 438 |
+
|
| 439 |
+
selected_chunk_title = st.selectbox(
|
| 440 |
+
label="Select Chunk to Edit",
|
| 441 |
+
options=chunk_selector_options,
|
| 442 |
+
index=current_selection_index,
|
| 443 |
+
key="chunk_selector"
|
| 444 |
+
)
|
| 445 |
+
else:
|
| 446 |
+
selected_chunk_title = st.selectbox(
|
| 447 |
+
label="Select Chunk to Edit",
|
| 448 |
+
options=["No chunks available"],
|
| 449 |
+
disabled=True
|
| 450 |
+
)
|
| 451 |
|
| 452 |
# Get the currently selected chunk
|
| 453 |
selected_chunk = None
|
|
|
|
| 461 |
value=selected_chunk["title"],
|
| 462 |
disabled=True
|
| 463 |
)
|
| 464 |
+
|
| 465 |
chunk_content_editor = st.text_area(
|
| 466 |
label="Chunk Content",
|
| 467 |
value=selected_chunk["content"],
|
| 468 |
height=250,
|
| 469 |
key=f"editor_{selected_chunk['id']}" # Unique key to prevent state loss
|
| 470 |
)
|
| 471 |
+
|
| 472 |
st.markdown(
|
| 473 |
chunk_manager.format_chunk_stats(selected_chunk['stats']),
|
| 474 |
unsafe_allow_html=True
|
|
|
|
| 491 |
else:
|
| 492 |
st.session_state.chunk_selector = None
|
| 493 |
|
|
|
|
| 494 |
else:
|
| 495 |
st.text_input("Chunk Title (Auto-detected)", "Title of the selected chunk", disabled=True)
|
| 496 |
st.text_area("Chunk Content", "Content of the selected chunk will appear here for editing.", height=250, disabled=True)
|
| 497 |
st.markdown("Chunk statistics will appear here.")
|
| 498 |
+
|
| 499 |
st.markdown("---")
|
| 500 |
st.markdown("## Final Compiled Markdown")
|
|
|
|
| 501 |
if st.button("Compile All Chunks", use_container_width=True):
|
| 502 |
st.session_state.final_markdown = chunk_manager.get_final_markdown()
|
| 503 |
|
|
|
|
| 508 |
key="final_markdown_output",
|
| 509 |
disabled=False
|
| 510 |
)
|
| 511 |
+
|
| 512 |
with tab2:
|
| 513 |
st.markdown("## Document Summary Statistics")
|
| 514 |
st.markdown(chunk_manager.get_document_summary_stats(), unsafe_allow_html=True)
|
|
|
|
| 515 |
st.markdown("---")
|
| 516 |
st.markdown("## Content Targets")
|
| 517 |
st.markdown("Adjust these targets to guide your writing and see visual feedback in the chunk selector (green=good, red=needs attention).")
|
|
|
|
| 524 |
with col2:
|
| 525 |
target_grade_max_input = st.number_input("Max Flesch-Kincaid Grade", value=float(chunk_manager.target_grade_max))
|
| 526 |
target_max_chunk_words_input = st.number_input("Max Chunk Words", value=chunk_manager.target_max_chunk_words)
|
| 527 |
+
|
| 528 |
submitted = st.form_submit_button("Set New Targets", use_container_width=True)
|
| 529 |
if submitted:
|
| 530 |
chunk_manager.set_targets(
|
| 531 |
+
target_flesch_min_input,
|
| 532 |
+
target_grade_max_input,
|
| 533 |
+
int(target_min_chunk_words_input),
|
| 534 |
int(target_max_chunk_words_input)
|
| 535 |
)
|
| 536 |
st.session_state.status_message = "Target settings updated."
|