Anti-hallucination: filename hint to LLM + beam search + silence threshold

When Whisper hallucinates (generates fake lyrics not matching the audio),
LLM can now use the original filename as a hint to recognize the song
and override the false transcript with the actual lyrics.

Pipeline:
1. Pass filename (e.g. 'Ben Zucker - Bonnie und Clyde') as hint
2. Whisper transcribes (may hallucinate)
3. Claude/Gemini reads filename + transcript:
   - Recognizes song from filename hint
   - Compares Whisper output to known lyrics
   - Replaces hallucinated text with real lyrics (preserves timestamps)
   - If can't fix, removes segment (better silent than wrong)

Also added Whisper anti-hallucination params:
- beam_size=5 (more careful decoding vs greedy)
- hallucination_silence_threshold=2.0 (skip text in long silences)

app/main.py

@@ -242,6 +242,11 @@ def process_job(job_id):
                 cmd += ["--llm-provider", job["llm_provider"]]
             if job.get("llm_model"):
                 cmd += ["--llm-model", job["llm_model"]]
+            # Filename hint = original filename (Claude lahko prepozna pesem)
+            if job.get("filename"):
+                # Brez extension
+                fn_hint = Path(job["filename"]).stem
+                cmd += ["--filename-hint", fn_hint]
             # lang: če None ali 'auto', pusti analyze.py auto-detect
             if job.get("lang") and job["lang"] not in ("auto", ""):
                 cmd += ["--lang", job["lang"]]