Commit b9d475d

@@ -17,12 +17,7 @@ from networking import hx_req
 from utils import seconds_to_time, strings_list, zhcn
 
 
-async def cloudflare_asr(
-    path: str | Path,
-    duration: float,
-    model: str | None = "",
-    prompt: str | None = "",
-) -> dict:
+async def cloudflare_asr(path: str | Path, duration: float, model: str | None = "") -> dict:
     """Cloudflare ASR.
 
     https://developers.cloudflare.com/workers-ai/models/whisper-large-v3-turbo/
@@ -40,17 +35,11 @@ async def cloudflare_asr(
     audio_path = await convert_single_channel(audio_path, ext="wav", codec="pcm_s16le")
     # max allowed file size is 25MB
     if duration < ASR.CLOUDFLARE_CHUNK_SECONDS:
-        return await cloudflare_single_file(audio_path, model=model, prompt=prompt)
-    return await cloudflare_file_chunks(audio_path, duration, model=model, prompt=prompt)
+        return await cloudflare_single_file(audio_path, model=model)
+    return await cloudflare_file_chunks(audio_path, duration, model=model)
 
 
-async def cloudflare_single_file(
-    path_or_bytes: Path | bytes,
-    model: str | None = "",
-    prompt: str | None = "",
-    *,
-    offset_seconds: int = 0,
-) -> dict:
+async def cloudflare_single_file(path_or_bytes: Path | bytes, model: str | None = "", *, offset_seconds: int = 0) -> dict:
     """Transcribe a single audio chunk with Groq API.
 
     Returns:
@@ -73,8 +62,6 @@ async def cloudflare_single_file(
             headers = {"Authorization": f"Bearer {cf_token}"}
             audio_base64 = base64.b64encode(audio_bytes).decode("utf-8")
             payload = {"audio": audio_base64, "task": "transcribe", "vad_filter": False}
-            if prompt:
-                payload["initial_prompt"] = prompt
             resp = await hx_req(
                 url,
                 "POST",
@@ -107,7 +94,6 @@ async def cloudflare_file_chunks(
     path: Path,
     duration: float,
     model: str | None = "",
-    prompt: str | None = "",
     chunk_seconds: float = 600,
     overlap_seconds: float = ASR.CLOUDFLARE_OVERLAP_SECONDS,
 ) -> dict:
@@ -152,7 +138,7 @@ async def cloudflare_file_chunks(
         bytes_list = await asyncio.gather(*tasks)  # convert chunks to bytes
         tasks = []
         for audio_bytes, offset_seconds in zip(bytes_list, offset_list, strict=True):
-            task = cloudflare_single_file(audio_bytes, model, prompt, offset_seconds=offset_seconds)
+            task = cloudflare_single_file(audio_bytes, model, offset_seconds=offset_seconds)
             tasks.append(run_with_semaphore(task))
         results = await asyncio.gather(*tasks)
         results = [r for r in results if r.get("segments")]

@@ -15,7 +15,7 @@ from networking import hx_req
 from utils import guess_mime, seconds_to_time, strings_list, zhcn
 
 
-async def groq_asr(path: str | Path, model: str = "", prompt: str = "", temperature: float = 0, language: str = "") -> dict:
+async def groq_asr(path: str | Path, model: str = "", temperature: float = 0, language: str = "") -> dict:
     """Groq ASR.
 
     https://console.groq.com/docs/api-reference#audio-transcription
@@ -30,15 +30,14 @@ async def groq_asr(path: str | Path, model: str = "", prompt: str = "", temperat
     audio_path = await convert_single_channel(audio_path, ext="wav", codec="pcm_s16le")
     # max allowed file size is 25MB
     if audio_path.stat().st_size < ASR.GROQ_MAX_BYTES:
-        return await groq_single_file(audio_path, model=model, prompt=prompt, temperature=temperature, language=language)
-    return await groq_file_chunks(audio_path, model=model, temperature=temperature, prompt=prompt, language=language)
+        return await groq_single_file(audio_path, model=model, temperature=temperature, language=language)
+    return await groq_file_chunks(audio_path, model=model, temperature=temperature, language=language)
 
 
 async def groq_single_file(
     path_or_bytes: Path | bytes,
     model: str = "",
     temperature: float = 0,
-    prompt: str = "",
     language: str = "",
     start_seconds: float = 0,
 ) -> dict:
@@ -60,8 +59,6 @@ async def groq_single_file(
     else:
         file_name = "chunk.wav"
         mime = "audio/wav"
-    if prompt:
-        data["prompt"] = prompt
     if language:
         data["language"] = language
     audio_bytes = await get_file_bytes(path_or_bytes)
@@ -253,7 +250,6 @@ async def groq_file_chunks(
     overlap_seconds: float = ASR.GROQ_OVERLAP_SECONDS,
     model: str = "",
     temperature: float = 0,
-    prompt: str = "",
     language: str = "",
 ) -> dict:
     """Transcribe audio in chunks with overlap.
@@ -300,7 +296,6 @@ async def groq_file_chunks(
                 start_seconds=offset,
                 model=model,
                 temperature=temperature,
-                prompt=prompt,
                 language=language,
             )
             for audio_bytes, offset in zip(bytes_list, offset_list, strict=True)

@@ -216,9 +216,9 @@ async def asr_file(
         elif engine == "gemini":
             res = await gemini_asr(path=path, prompt=prompt, delete_gemini_file=delete_gemini_file)
         elif engine == "cloudflare":
-            res = await cloudflare_asr(path, duration, model=kwargs.get("cf_asr_model"), prompt=prompt)
+            res = await cloudflare_asr(path, duration, model=kwargs.get("cf_asr_model"))
         elif engine == "groq":
-            res = await groq_asr(path=path, model=kwargs.get("groq_asr_model", ""), prompt=prompt)
+            res = await groq_asr(path=path, model=kwargs.get("groq_asr_model", ""))
         else:
             return {"error": "ASR method not supported"}
         if res.get("texts"):