Build cues out of word times where a model marks no segments

Not every model behind /audio/transcriptions marks segments the way
whisper does. microsoft/mai-transcribe-2 answers a fourteen minute video
with three of them, one per paragraph, and to_srt turns each into a cue
that stays up for minutes. The model is worth keeping for what it hears,
so the times are taken from somewhere else instead: the same request now
asks for word timestamps too, and where the segments come back too long
to be cues, the cues are cut out of the words.

A cue ends where a sentence does, and failing that where it has grown
too long to read or to leave up. A full stop too early in a cue is not
the end of a sentence but a list marker or a shortened word, and one
that ends up short anyway is held on screen until the next needs the
space. Whisper still answers with its own segments and nothing on that
path changes; the local server is not asked for words it was never
asked for, and a hosted model that refuses the field falls back to the
request it used to answer.

A cue is short enough now that two can begin in the same second, so
to_srt hands out every timing a second holds rather than the first.

tests/test_api.py

@@ -322,7 +322,12 @@ class TranscribeSegments(DikteTest):
         fields = multipart_fields(calls[0])
         self.assertEqual(fields["model"], "whisper-1")
         self.assertEqual(fields["response_format"], "verbose_json")
-        self.assertEqual(fields["timestamp_granularities[]"], "segment")
+        # Both are asked for: whisper answers with segments, and a model that
+        # does not mark them still answers with word times.
+        body = calls[0].data.decode("utf-8", "replace")
+        for level in ("segment", "word"):
+            self.assertIn(
+                f'name="timestamp_granularities[]"\r\n\r\n{level}\r\n', body)
 
     def test_openrouter_uses_the_namespaced_id(self):
         with fake_urlopen(self.reply([{"start": 0, "end": 1, "text": "hi"}])) as calls:
@@ -363,6 +368,74 @@ class TranscribeSegments(DikteTest):
             self.assertEqual(api.transcribe_segments(OPENAI, self.wav),
                              [(5.0, 5.0, "hi")])
 
+    def test_a_long_sentence_is_broken_where_it_gets_too_long_to_read(self):
+        words = [{"word": "word", "start": i * 0.2, "end": i * 0.2 + 0.2}
+                 for i in range(60)]
+        cues = api.cues_from_words(words)
+        self.assertGreater(len(cues), 1)
+        for start, end, text in cues:
+            self.assertLessEqual(len(text), api.MAX_CUE_CHARS)
+            self.assertLessEqual(end - start, api.MAX_CUE_SECONDS + 0.2)
+
+    def test_a_pause_between_short_sentences_does_not_join_them(self):
+        cues = api.cues_from_words([
+            {"word": "Yes.", "start": 0.0, "end": 0.3},
+            {"word": "No.", "start": 9.0, "end": 9.3},
+        ])
+        self.assertEqual([(start, text) for start, _, text in cues],
+                         [(0.0, "Yes."), (9.0, "No.")])
+
+    def test_a_cue_too_short_to_read_is_held_until_the_next_one(self):
+        cues = api.cues_from_words([
+            {"word": "Yes.", "start": 0.0, "end": 0.3},
+            {"word": "No.", "start": 9.0, "end": 9.3},
+        ])
+        # The first has the room for it, the last has nothing after it to wait for.
+        self.assertEqual(cues[0][1], api.MIN_CUE_SECONDS)
+        self.assertEqual(cues[1][1], 9.0 + api.MIN_CUE_SECONDS)
+
+    def test_a_list_marker_does_not_end_a_cue_on_its_own(self):
+        cues = api.cues_from_words([
+            {"word": "1.", "start": 0.0, "end": 0.2},
+            {"word": "Antivirus.", "start": 0.4, "end": 1.6},
+        ])
+        self.assertEqual([text for _, _, text in cues], ["1. Antivirus."])
+
+    def test_a_sentence_ending_inside_a_quote_still_ends_the_cue(self):
+        cues = api.cues_from_words([
+            {"word": '"Stop', "start": 0.0, "end": 1.0},
+            {"word": 'there."', "start": 1.1, "end": 2.0},
+            {"word": "Then", "start": 2.2, "end": 2.6},
+        ])
+        self.assertEqual([text for _, _, text in cues],
+                         ['"Stop there."', "Then"])
+
+    def test_word_times_take_over_from_segments_too_long_to_read(self):
+        # What a model that does not mark segments answers with: one entry for
+        # the whole file, and the real timing in the words beside it.
+        reply = {
+            "text": "One. Two.",
+            "segments": [{"start": 0, "end": 60, "text": "One. Two."}],
+            "words": [
+                {"word": "One.", "start": 0.1, "end": 1.5},
+                {"word": "Two.", "start": 1.7, "end": 3.0},
+            ],
+        }
+        with fake_urlopen(reply):
+            self.assertEqual(api.transcribe_segments(OPENAI, self.wav),
+                             [(0.1, 1.5, "One."), (1.7, 3.0, "Two.")])
+
+    def test_whisper_segments_are_left_alone_when_words_come_too(self):
+        reply = {
+            "text": "hi there",
+            "segments": [{"start": 0, "end": 2, "text": "hi there"}],
+            "words": [{"word": "hi", "start": 0.0, "end": 0.5},
+                      {"word": "there", "start": 0.5, "end": 2.0}],
+        }
+        with fake_urlopen(reply):
+            self.assertEqual(api.transcribe_segments(OPENAI, self.wav),
+                             [(0.0, 2.0, "hi there")])
+
     def test_a_model_that_returned_no_segments_still_gives_its_text(self):
         with fake_urlopen(self.reply([], text="the whole thing")):
             self.assertEqual(api.transcribe_segments(OPENAI, self.wav),