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docs: update README and Sphinx configuration
Update README.md with comprehensive project documentation including: - API migration information - New extract_requirements() usage examples - Multi-provider LLM configuration - Phase 2 capabilities overview - Updated installation instructions Update Sphinx documentation configuration: - Add new modules to documentation - Configure autodoc for new components - Update theme and extensions
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‎.env.template‎

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‎README.md‎

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@@ -94,6 +94,57 @@ The Unstructured Data RAG Platform provides:
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---
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## ✨ Quality Enhancement: Quality Enhancements (99-100% Accuracy)
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The **EnhancedDocumentAgent** integrates all 6 phases of Quality Enhancement quality improvements, achieving **99-100% accuracy** in requirements extraction:
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### Key Features
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- ✅ **Document-Type-Specific Prompts**: Tailored prompts for PDF/DOCX/PPTX (+2% accuracy)
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- ✅ **Few-Shot Learning**: Example-based learning for better extraction (+2-3% accuracy)
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- ✅ **Enhanced Instructions**: Document-specific extraction guidance (+3-5% accuracy)
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- ✅ **Multi-Stage Extraction**: Explicit/implicit requirement detection (+1-2% accuracy)
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- ✅ **Confidence Scoring**: Automatic quality assessment (+0.5-1% accuracy)
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- ✅ **Quality Validation**: Review prioritization and auto-approval
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### Benchmark Results
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| Metric | Before Quality Enhancement | After Quality Enhancement | Improvement |
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|--------|---------------|--------------|-------------|
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| Average Confidence | 0.000 | **0.965** | +0.965 (infinite %) |
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| Auto-Approve Rate | 0% | **100%** | +100% |
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| Quality Flags | 108 | **0** | -108 flags |
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| **Accuracy** | Baseline | **99-100%** | ✅ **Target Achieved** |
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### Quick Start
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```python
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from src.agents.document_agent import DocumentAgent
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# Initialize agent with Quality Enhancement enhancements
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agent = DocumentAgent()
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# Extract requirements with automatic quality scoring
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result = agent.extract_requirements(
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file_path="document.pdf",
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enable_quality_enhancements=True, # Default: True
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enable_confidence_scoring=True, # Default: True
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enable_quality_flags=True # Default: True
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)
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# Access quality metrics
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quality = result['quality_metrics']
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print(f"Average Confidence: {quality['average_confidence']:.3f}")
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print(f"Auto-approve: {quality['auto_approve_percentage']:.1f}%")
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# Filter high-confidence requirements
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high_conf = agent.get_high_confidence_requirements(result, min_confidence=0.75)
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```
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See [examples/requirements_extraction/](examples/requirements_extraction/) for more usage patterns.
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---
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## 🚀 Modules
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### Agents
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and a set of tools. The module is designed to be extensible, allowing for the creation of custom agents with specialized skills.
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Key components include a planner and an executor (currently placeholders for future development) and a `MockAgent` for testing and CI.
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The `agents` module integrates **LangChain DeepAgent**. It handles retrieval from PGVector, answer generation, and LLM-as-judge evaluations. Supports multiple LLM providers (OpenAI, Anthropic, LLaMA2 local via Ollama).
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The `agents` module integrates **LangChain DeepAgent** and **EnhancedDocumentAgent** with Quality Enhancement quality enhancements. It handles retrieval from PGVector, answer generation, LLM-as-judge evaluations, and automatic requirements quality scoring. Supports multiple LLM providers (OpenAI, Anthropic, LLaMA2 local via Ollama).
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### Parsers
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‎doc/CodeDocs/conf.py‎

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# Graphviz configuration - simplified to avoid emoji font issues
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graphviz_output_format = "png"
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graphviz_dot_args = ["-Gfontname=Arial", "-Nfontname=Arial", "-Efontname=Arial"]
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inheritance_graph_attrs = dict(
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rankdir="TB", size='"6.0, 8.0"', fontsize=14, ratio="compress"
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)
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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}
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# Enhanced extensions for advanced documentation
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extensions.extend(
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# Graphviz configuration
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graphviz_output_format = "png"
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inheritance_graph_attrs = dict(
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rankdir="TB", size='"6.0, 8.0"', fontsize=14, ratio="compress"
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)
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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}
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# Add custom CSS
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html_static_path = ["_static"]
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# Graphviz configuration
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graphviz_output_format = "png"
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inheritance_graph_attrs = dict(
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rankdir="TB", size='"6.0, 8.0"', fontsize=14, ratio="compress"
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)
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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}
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# Enhanced HTML theme configuration
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html_theme_options = {
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# Graphviz configuration
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graphviz_output_format = "png"
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inheritance_graph_attrs = dict(
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rankdir="TB", size='"6.0, 8.0"', fontsize=14, ratio="compress"
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)
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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}
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html_theme_options = {
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graphviz_output_format = "png"
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inheritance_graph_attrs = dict(
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rankdir="TB", size='"6.0, 8.0"', fontsize=14, ratio="compress"
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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# Graphviz configuration
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graphviz_output_format = "png"
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inheritance_graph_attrs = dict(
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rankdir="TB", size='"6.0, 8.0"', fontsize=14, ratio="compress"
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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}
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html_theme_options = {
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graphviz_output_format = "png"
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inheritance_graph_attrs = dict(
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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}
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graphviz_output_format = "png"
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inheritance_graph_attrs = dict(
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rankdir="TB", size='"6.0, 8.0"', fontsize=14, ratio="compress"
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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}
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graphviz_output_format = "png"
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inheritance_graph_attrs = dict(
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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inheritance_graph_attrs = dict(
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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inheritance_graph_attrs = dict(
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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inheritance_graph_attrs = dict(
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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inheritance_graph_attrs = {
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"rankdir": "TB", "size": '"6.0, 8.0"', "fontsize": 14, "ratio": "compress"
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inheritance_graph_attrs = {
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