Context prompt (#128)

Co-authored-by: Jong Wook Kim <[email protected]>

whisper/transcribe.py

@@ -137,6 +137,11 @@ def decode_with_fallback(segment: torch.Tensor) -> List[DecodingResult]:
     all_segments = []
     prompt_reset_since = 0
 
+    initial_prompt = decode_options.pop("initial_prompt", None) or []
+    if initial_prompt:
+        initial_prompt = tokenizer.encode(" " + initial_prompt.strip())
+        all_tokens.extend(initial_prompt)
+
     def add_segment(
         *, start: float, end: float, text_tokens: torch.Tensor, result: DecodingResult
     ):
@@ -237,7 +242,7 @@ def add_segment(
             pbar.update(min(num_frames, seek) - previous_seek_value)
             previous_seek_value = seek
 
-    return dict(text=tokenizer.decode(all_tokens), segments=all_segments, language=language)
+    return dict(text=tokenizer.decode(all_tokens[len(initial_prompt):]), segments=all_segments, language=language)
 
 
 def cli():
@@ -260,6 +265,7 @@ def cli():
     parser.add_argument("--length_penalty", type=float, default=None, help="optional token length penalty coefficient (alpha) as in https://arxiv.org/abs/1609.08144, uses simple lengt normalization by default")
 
     parser.add_argument("--suppress_tokens", type=str, default="-1", help="comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations")
+    parser.add_argument("--initial_prompt", type=str, default=None, help="optional text to provide as a prompt for the first window.")
     parser.add_argument("--condition_on_previous_text", type=str2bool, default=True, help="if True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop")
     parser.add_argument("--fp16", type=str2bool, default=True, help="whether to perform inference in fp16; True by default")