Fix main_v2 bridge and pipeline regressions

history.md

@@ -238,3 +238,20 @@ The project now features a high-performance, Apple Silicon-optimized pipeline th
     - **English Bridge Optimization:** Forced a two-pass transcription strategy (ASR first, then optional translation) to ensure word-level timestamps are captured for speaker mapping even when translating to English.
     - **Stability Fixes:** Added hallucination filtering for Whisper's repetitive loops, enforced line-buffering for terminal logging, and implemented a global `lzma` mock to ensure compatibility across restricted Python environments.
 - **Outcome:** A robust, production-ready pipeline that produces high-quality, speaker-attributed, and professionally formatted live transcripts.
+
+## Phase 28: `main_v2` Bridge Contract Fixes + Live Reliability Review
+- **Goal:** Repair stage-contract regressions in the new multi-process pipeline and preserve live throughput under failure.
+- **Review Findings:**
+    - The Whisper English bridge in `engine_transcribe.py` reused source-language prompt context for `task="translate"` instead of a dedicated English context, which could bias or degrade translated bridge text.
+    - `--filter-lang` was exposed in `main_v2.py` but not enforced in the new transcription engine, so wrong-language speech could still be bridged and propagated downstream.
+    - `engine_llm.py` told the paragraph refiner to output the source language even though downstream Marian models require English input, breaking `llm_paragraph` for non-English sources.
+    - `engine_translate.py` could translate one English variant while publishing a different `[EN]` line, making the visible source text diverge from what target-language MT actually used.
+    - `engine_distribute.py` retried ingest forever in the queue consumer, allowing a network outage to stall the whole live pipeline.
+    - `main_v2.py` exposed post-correction settings that the new pipeline did not fully honor, making CLI behavior drift from the documented workflow.
+- **Approach:**
+    - Restored a dedicated rolling English prompt context for the Whisper bridge pass and rebuilt bridge kwargs explicitly instead of copying source-ASR kwargs.
+    - Reinstated `--filter-lang` enforcement before bridge generation and reduced unnecessary ASR cost by only asking Whisper for word timestamps when diarization is enabled.
+    - Updated the LLM stage so paragraph refinement always preserves English bridge text, added deterministic post-correction plus optional LLM line cleanup, and provided a safe fallback paragraph when the LLM backend is unavailable.
+    - Aligned published English output with the exact text chosen for translation and added the missing Ollama-related config/plumbing to `main_v2`.
+    - Replaced infinite ingest retry loops with bounded retry logic so failed delivery degrades gracefully instead of freezing caption flow.
+- **Outcome:** The `main_v2` pipeline now keeps an English-first contract across transcription, refinement, and Marian translation while behaving more predictably under API outages and mixed-language input.