feat: unify pipeline session creation between analyze and run commands

[shrutu0929]

solve #179
This task involved unifying the session creation and management logic between the core library's RefactronPipeline and the CLI's analyze and run commands. By refactoring the orchestration layer, I eliminated duplicate code paths that were previously handling analysis results and session state independently, which often led to inconsistent timing metrics and data drift. I implemented robust JSON-based persistence in the PipelineSession model, allowing sessions to be saved to and loaded from a centralized storage directory for better observability. With these changes, every analysis run now automatically initializes a structured session that captures phase-specific timings, tracks queued fixes, and persists metadata, ensuring a consistent and reliable state across all Refactron orchestration workflows.

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Configuration used: defaults

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Run ID: 0c211835-5f04-4b2d-88e8-0864c75bc6b5

📥 Commits

Reviewing files that changed from the base of the PR and between a9659f5 and 361bcd3.

📒 Files selected for processing (8)

• .refactron.yaml
• refactron/cli/analysis.py
• refactron/cli/main.py
• refactron/cli/run.py
• refactron/core/pipeline.py
• refactron/core/pipeline_session.py
• tests/test_pipeline.py
• tests/test_pipeline_session.py

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