diff --git a/cookbook/use_cases/finance/03_Earnings_Call_Analysis.ipynb b/cookbook/use_cases/finance/03_Earnings_Call_Analysis.ipynb index fe8d2335..3e8b2574 100644 --- a/cookbook/use_cases/finance/03_Earnings_Call_Analysis.ipynb +++ b/cookbook/use_cases/finance/03_Earnings_Call_Analysis.ipynb @@ -87,44 +87,73 @@ "execution_count": 3, "metadata": {}, "outputs": [ + { + "data": { + "text/html": [ + "

🧠 Semantica - 📊 Current Progress

StatusActionModuleSubmoduleProgressETARateTime
❌Semantica is parsing🔍 parseDoclingParser---0.01s
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "name": "stdout", "output_type": "stream", "text": [ - "✓ Document parsed: Q1 2024 Earnings Call\n", - " Text length: 409 characters\n" + "🧠 Semantica is parsing: Docling: mda_space_q3_2025_press_release.pdf 🔄🔍 (0.0s) " + ] + }, + { + "ename": "ImportError", + "evalue": "[WinError 1114] A dynamic link library (DLL) initialization routine failed. Error loading \"c:\\Users\\Mohd Kaif\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\lib\\c10.dll\" or one of its dependencies.", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[3], line 22\u001b[0m\n\u001b[0;32m 19\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m transcript_pdf\u001b[38;5;241m.\u001b[39mexists():\n\u001b[0;32m 20\u001b[0m transcript_pdf\u001b[38;5;241m.\u001b[39mwrite_bytes(requests\u001b[38;5;241m.\u001b[39mget(transcript_url)\u001b[38;5;241m.\u001b[39mcontent)\n\u001b[1;32m---> 22\u001b[0m press_release \u001b[38;5;241m=\u001b[39m \u001b[43mparser\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparse\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpress_release_pdf\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 23\u001b[0m transcript \u001b[38;5;241m=\u001b[39m parser\u001b[38;5;241m.\u001b[39mparse(transcript_pdf)\n\u001b[0;32m 25\u001b[0m parsed_doc \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 26\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfull_text\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m# Press Release\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mpress_release[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfull_text\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m# Transcript\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mtranscript[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfull_text\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 27\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtables\u001b[39m\u001b[38;5;124m\"\u001b[39m: press_release[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtables\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m+\u001b[39m transcript[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtables\u001b[39m\u001b[38;5;124m'\u001b[39m],\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 33\u001b[0m }\n\u001b[0;32m 34\u001b[0m }\n", + "File \u001b[1;32m~\\semantica\\semantica\\parse\\docling_parser.py:137\u001b[0m, in \u001b[0;36mDoclingParser.parse\u001b[1;34m(self, file_path, **options)\u001b[0m\n\u001b[0;32m 135\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m DOCLING_AVAILABLE:\n\u001b[0;32m 136\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m DOCLING_IMPORT_ERROR:\n\u001b[1;32m--> 137\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(DOCLING_IMPORT_ERROR)\n\u001b[0;32m 138\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 139\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDocling is not installed\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[1;31mImportError\u001b[0m: [WinError 1114] A dynamic link library (DLL) initialization routine failed. Error loading \"c:\\Users\\Mohd Kaif\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\lib\\c10.dll\" or one of its dependencies." ] } ], "source": [ + "import requests\n", + "from pathlib import Path\n", "from semantica.parse import DoclingParser\n", "\n", - "parser = DoclingParser(\n", - " export_format=\"markdown\",\n", - " enable_ocr=False,\n", - " table_extraction_mode=\"auto\"\n", - ")\n", + "parser = DoclingParser()\n", + "\n", + "press_release_url = \"https://filecache.investorroom.com/mr5ircnw_mda/677/MDA_Space_Ltd_Q3_2025_Press_Release_Nov_14_2025_FINAL.pdf\"\n", + "transcript_url = \"https://filecache.investorroom.com/mr5ircnw_mda/681/MDA%20Space%20Ltd.%20Q3%202025%20Earnings%20Conference%20Call%20Transcript%20%28November%2014%202025%29.pdf\"\n", + "\n", + "download_dir = Path(\"downloads\")\n", + "download_dir.mkdir(exist_ok=True)\n", + "\n", + "press_release_pdf = download_dir / \"mda_space_q3_2025_press_release.pdf\"\n", + "transcript_pdf = download_dir / \"mda_space_q3_2025_transcript.pdf\"\n", + "\n", + "if not press_release_pdf.exists():\n", + " press_release_pdf.write_bytes(requests.get(press_release_url).content)\n", + "\n", + "if not transcript_pdf.exists():\n", + " transcript_pdf.write_bytes(requests.get(transcript_url).content)\n", + "\n", + "press_release = parser.parse(press_release_pdf)\n", + "transcript = parser.parse(transcript_pdf)\n", "\n", - "# Example parsed document (replace with actual PDF parsing)\n", "parsed_doc = {\n", - " \"full_text\": \"\"\"Q1 2024 Earnings Call Transcript\n", - "\n", - "Company: TechCorp Inc.\n", - "Date: January 25, 2024\n", - "\n", - "Prepared Remarks:\n", - "Our revenue for Q1 2024 was $2.5 billion, representing 15% year-over-year growth. \n", - "EPS was $1.25 per share. We expect Q2 revenue to be between $2.6 and $2.8 billion.\n", - "\n", - "Q&A Session:\n", - "Analyst: What's your guidance for the full year?\n", - "CEO: We're maintaining our full-year guidance of $10.5 to $11 billion in revenue.\"\"\",\n", - " \"tables\": [],\n", - " \"metadata\": {\"title\": \"Q1 2024 Earnings Call\"}\n", - "}\n", - "\n", - "print(f\"✓ Document parsed: {parsed_doc['metadata'].get('title', 'Unknown')}\")\n", - "print(f\" Text length: {len(parsed_doc['full_text'])} characters\")\n" + " \"full_text\": f\"# Press Release\\n\\n{press_release['full_text']}\\n\\n# Transcript\\n\\n{transcript['full_text']}\",\n", + " \"tables\": press_release['tables'] + transcript['tables'],\n", + " \"metadata\": {\n", + " \"title\": \"MDA Space Ltd. Q3 2025 Earnings Analysis\",\n", + " \"company\": \"MDA Space Ltd.\",\n", + " \"quarter\": \"Q3 2025\",\n", + " \"date\": \"November 14, 2025\"\n", + " }\n", + "}\n" ] }, { @@ -138,26 +167,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [ - { - "data": { - "text/html": [ - "

🧠 Semantica - 📊 Current Progress

StatusActionModuleSubmoduleProgressETARateTime
✅Semantica is normalizing🔧 normalizeTextNormalizer100.0%--0.01s
✅Semantica is extracting🎯 semantic_extractNERExtractor100.0%--0.01s
✅Semantica is extracting🎯 semantic_extractRelationExtractor100.0%--0.00s
✅Semantica is extracting🎯 semantic_extractTripletExtractor100.0% (1/1)-65.4/s0.02s
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, { "name": "stdout", "output_type": "stream", "text": [ - "🧠 Normalizing text 🔄🔧 (0.0s) ✓ Text normalized: 409 characters\n" + "🧠 Semantica is parsing: Docling: mda_space_q3_2025_press_release.pdf 🔄🔍 (0.0s) | 🧠 Normalizing text 🔄🔧 (0.0s) ✓ Text normalized: 0 characters\n" ] } ], @@ -186,16 +203,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Method llm failed: groq provider not available\n" - ] - }, { "name": "stdout", "output_type": "stream", @@ -236,23 +246,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "🧠 Normalizing text 🔄🔧 (0.0s) | 🧠 Semantica is extracting: Extracting named entities from text 🔄🎯 (0.0s) " - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Method llm failed: groq provider not available\n" - ] - }, { "name": "stdout", "output_type": "stream", @@ -289,7 +285,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -334,14 +330,14 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "🧠 Semantica is extracting: Extracting named entities from text 🔄🎯 (0.0s) | 🧠 Semantica is extracting: Extracting triplets using llm... (1/1, remaining: 0 methods) |███████████████| 100.0% [1/1] 🔄🎯 (88.5/s)" + "🧠 Normalizing text 🔄🔧 (0.0s) | 🧠 Semantica is extracting: Extracting triplets using llm... (1/1, remaining: 0 methods) |███████████████| 100.0% [1/1] 🔄🎯 (61.7/s)" ] }, { diff --git a/semantica/parse/docling_parser.py b/semantica/parse/docling_parser.py index 97e0a3e3..386cadc8 100644 --- a/semantica/parse/docling_parser.py +++ b/semantica/parse/docling_parser.py @@ -32,6 +32,7 @@ Author: Semantica Contributors License: MIT """ +import time from dataclasses import dataclass, field from pathlib import Path from typing import Any, Dict, List, Optional, Union @@ -137,6 +138,14 @@ class DoclingParser: else: raise ImportError("Docling is not installed") + # Stage 1: Initialization (0-10%) + self.progress_tracker.update_progress( + tracking_id, + processed=1, + total=10, + message="Initializing Docling converter..." + ) + # Lazy initialization of converter if self._converter is None: self._converter = DocumentConverter( @@ -148,18 +157,44 @@ class DoclingParser: # Determine export format export_format = options.get("export_format", self.export_format) - self.progress_tracker.update_tracking( - tracking_id, message=f"Converting document with Docling..." + # Stage 2: Document conversion (10-70%) - This is the longest step + # Note: This is a blocking operation, but we'll update progress after it completes + self.progress_tracker.update_progress( + tracking_id, + processed=2, + total=10, + message=f"Converting document with Docling (this may take a while for large PDFs)..." ) - # Convert document using Docling + # Convert document using Docling (blocking operation) + # Store start time for ETA calculation + conversion_start = time.time() result = self._converter.convert(str(file_path)) + conversion_elapsed = time.time() - conversion_start + + # Stage 3: Document conversion complete (70%) + # Update progress immediately after conversion completes with timing info + self.progress_tracker.update_progress( + tracking_id, + processed=7, + total=10, + message=f"Document conversion complete ({conversion_elapsed:.1f}s), extracting content..." + ) # Extract content based on export format extract_text = options.get("extract_text", True) extract_tables = options.get("extract_tables", True) extract_images = options.get("extract_images", False) + # Stage 4: Text extraction (70-80%) + if extract_text: + self.progress_tracker.update_progress( + tracking_id, + processed=8, + total=10, + message=f"Extracting text content ({export_format} format)..." + ) + # Get document content if export_format == "markdown": full_text = result.document.export_to_markdown() @@ -172,20 +207,44 @@ class DoclingParser: else: full_text = result.document.export_to_markdown() - # Extract metadata + # Stage 5: Metadata extraction (80-85%) + self.progress_tracker.update_progress( + tracking_id, + processed=8, + total=10, + message="Extracting document metadata..." + ) metadata = self._extract_metadata(result, file_path) - # Extract tables + # Stage 6: Table extraction (85-95%) tables = [] if extract_tables: + self.progress_tracker.update_progress( + tracking_id, + processed=9, + total=10, + message="Extracting tables from document..." + ) tables = self._extract_tables(result, export_format) - # Extract pages (for PDF-like structure) + # Stage 7: Page extraction (95-98%) + self.progress_tracker.update_progress( + tracking_id, + processed=9, + total=10, + message="Extracting page structure..." + ) pages = self._extract_pages(result, options) - # Extract images if requested + # Stage 8: Image extraction (98-100%) images = [] if extract_images: + self.progress_tracker.update_progress( + tracking_id, + processed=9, + total=10, + message="Extracting images from document..." + ) images = self._extract_images(result) self.progress_tracker.stop_tracking(