…nagement

- Introduce RetrievalBudgetController to track token consumption across all
  pipeline stages (Plan, Search, Evaluate)
- Add BudgetStatus enum with Healthy, Constrained, and Exhausted states
- Implement budget-aware strategy selection in Plan stage
- Apply dynamic beam width adjustment based on budget status in Search stage
- Enable graceful degradation when budget is exhausted
- Track and report budget utilization throughout the pipeline
- Add comprehensive tests for budget controller functionality

Add optional path_constraint field to SubQuery to store structural
path constraints extracted from queries (e.g. "3.2", "Chapter 5").

Add resolved_path_hints field to PipelineContext to store node IDs
extracted from structural queries.

Implement Chinese number parsing utility function to convert
Chinese numerals to integers (e.g. "三" → 3, "二十一" → 21).

Add extract_structure_hints method to recognize and map various
structural patterns including:
- Chinese chapter/section patterns: "第X章", "第X节", "第一章"
- English section numbers: "Section 3.2", "section 4.1.2"
- Chapter references: "Chapter 5", "chapter 10"
- Bare section numbers: "3.2.1", "2.1"
- Table/Figure references: "表3", "Table 5", "图2", "Figure 4"

Integrate structure hints into search stage by injecting them as
high-priority search cues with confidence score of 1.0.

Update all relevant initialization code to include the new fields
in tests and implementation.

- introduce ReasoningIndex and related types (TopicEntry, SummaryShortcut,
  SectionSummary, HotNodeEntry, ReasoningIndexConfig) for pre-computed
  topic-to-path mappings
- create ReasoningIndexStage that builds the reasoning index after
  enrich stage and before optimize stage
- add reasoning_index field to PipelineOptions and IndexContext to
  configure and store the reasoning index
- implement hot node tracking functionality in HotNodeTracker for
  identifying frequently retrieved nodes
- integrate reasoning index into persist stage to save it with documents
- update metrics to track reasoning index build time and statistics
- add reasoning cache integration in retrieval pipeline context

- Introduce DocumentGraph struct with nodes, edges, and keyword indexing
- Implement graph builder for computing relationships based on shared keywords
- Add graph-aware retrieval strategy with boost capabilities
- Support serialization and storage integration in workspace
- Include comprehensive test coverage for graph operations

…vent support

This commit introduces comprehensive streaming retrieval capabilities to the
vectorless engine. Users can now receive incremental results through a
channel-based event system that provides real-time feedback during the
retrieval process.

Key changes include:

- Added `retrieve_streaming()` method to `PipelineRetriever` that returns
  a channel for receiving `RetrieveEvent`s as the pipeline progresses
- Implemented `RetrieveEvent` enum with variants for different pipeline
  milestones including Started, StageCompleted, NodeVisited, ContentFound,
  Backtracking, SufficiencyCheck, Completed, and Error
- Created new streaming module with proper channel handling and event
  emission throughout the retrieval pipeline
- Added streaming example in `examples/rust/streaming.rs` demonstrating
  how to process events as they arrive
- Updated `RetrievalOrchestrator` to support both regular and streaming
  execution paths without affecting existing functionality
- Enhanced documentation with usage examples and comprehensive event
  descriptions

The streaming API maintains backward compatibility - existing `query()`
method remains unchanged while `query_stream()` provides the new
incremental functionality. This enables use cases like interactive Q&A
with real-time feedback, progress monitoring, and responsive UI updates.

Removed the main README.md and design documents for client-module
and content-aggregation as they are no longer relevant to the
current codebase structure.

BREAKING CHANGE: Documentation files removed as part of cleanup
process.

…ontent

- Replace old logo with new lovable-vectorless.png and update styling
- Change title to "Reasoning-native Document Intelligence Engine"
- Update crates.io badge to show version instead of downloads
- Remove detailed architecture diagram and how-it-works sections
- Simplify quick start with streamlined Python and Rust examples
- Consolidate API usage patterns into concise code snippets
- Remove configuration details and focus on essential setup
- Streamline feature descriptions and remove redundant sections
- Remove architecture diagram file as it's no longer referenced