Removed custom_output_names from the separate file call.

[Kulin-Soni]

Removed custom_output_names from _separate_file call inside the _process_with_chunking method. This prevents the processed chunks from getting the same custom name, and have the chunk_N naming.

This prevents overwriting previous chunks.

This is a fix to #259

Summary by CodeRabbit

Release Notes

• Bug Fixes
  • Modified output file naming behavior during chunked audio file processing to ensure consistent handling across the separation pipeline.

[coderabbitai]

No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: Organization UI

Review profile: CHILL

Plan: Pro

Run ID: f57fc33d-6550-4fbc-938c-8190c65963c1

📥 Commits

Reviewing files that changed from the base of the PR and between 12f8fc6 and 2b0895f.

📒 Files selected for processing (1)

• audio_separator/separator/separator.py

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Walkthrough

A parameter removal from a function call in the chunked audio processing method. The custom_output_names parameter is omitted when calling _separate_file during chunk processing, eliminating custom naming for intermediate chunk outputs.

Changes

Cohort / File(s)	Summary
Parameter Removal audio_separator/separator/separator.py	Removed custom_output_names parameter from _separate_file() call in _process_with_chunking() method, affecting custom output naming during chunked audio separation.

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~3 minutes

Poem

🐰 A parameter hops away,
Custom names no longer stay,
Chunks process clean and plain,
Simplicity—the rabbit's gain! 🎵

🚥 Pre-merge checks | ✅ 3

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title accurately describes the main change: removing the custom_output_names parameter from a _separate_file method call in the chunking process.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.

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[beveradb]

Can you make sure all the tests pass too please? 🙏