## Version 0.17.4

This release includes several enhancements and bug fixes improving the functionality and user experience across various modules, particularly focusing on span logging, bot behavior, and agent design.

### New Features

- Introduced a span-based logging feature for LLM traces, enhancing traceability and debugging capabilities for bots. (1fd64e9) (Eric Ma)
- Added a new cell in the experiment_design_agent notebook to demonstrate a perfect prompt using markdown, enhancing user guidance and example clarity. (10a1540) (Eric Ma)
- Revamped the experiment design agent to function as an inquisitive consultation assistant, improving interaction quality and decision-making support. (be7b8f2) (Eric Ma)
- Implemented a two-step receipt processing method using OCR and structuring bots in the PyData Boston 2025 tutorial, optimizing data extraction and processing. (4fd99f9) (Eric Ma)
- Added the inspect_globals tool to Llamabot for better context awareness by listing available objects in globals. (51f6246) (Eric Ma)

### Bug Fixes

- Ensured bots always create a new trace_id for each call to prevent inheriting trace_ids from the context, addressing a critical bug in trace management. (92de1b8) (Eric Ma)
- Improved span visualization styling and layout to prevent overflow and enhance visual balance between panels. (d0c15e2) (Eric Ma)
- Fixed incorrect usage of the get_spans function in the span_logging_example notebook by changing attribute dictionary to keyword arguments. (d69a842) (Eric Ma)
- Addressed flaky tests related to AgentBot's max_iterations and improved test fixtures for better reliability and performance. (0d60c54) (Eric Ma)
- Corrected the parameter mismatch in test_agentbot by updating the mock function to use 'response' instead of 'message'. (2ff52c0) (Eric Ma)

### Deprecations

- Removed the View Span Tree section from the span logging example notebook as part of documentation updates to reflect current features. (1730d04) (Eric Ma)
