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allow transcribe to be used with the LLM instead if no whisper model exists

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Concedo 2026-01-04 11:06:05 +08:00
parent 04f5445bef
commit 01c70a7d3d
1 changed files with 24 additions and 2 deletions
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26
koboldcpp.py
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@ -67,7 +67,7 @@ dry_seq_break_max = 128
extra_images_max = 4 # for kontext/qwen img
# global vars
KcppVersion = "1.106"
KcppVersion = "1.105.2"
showdebug = True
kcpp_instance = None #global running instance
global_memory = {"tunnel_url": "", "restart_target":"", "input_to_exit":False, "load_complete":False, "restart_override_config_target":""}
@ -2803,6 +2803,7 @@ number ::= ("-"? ([0-9] | [1-9] [0-9]{0,15})) ("." [0-9]+)? ([eE] [-+]? [1-9] [0
ws ::= | " " | "\n" [ \t]{0,20}
"""
used_tool_json = None
#api format 1=basic,2=kai,3=oai,4=oai-chat,5=interrogate,6=ollama,7=ollamachat
#alias all nonstandard alternative names for rep pen.
rp1 = float(genparams.get('repeat_penalty', 1.0))
@ -4750,7 +4751,28 @@ Change Mode<br>
return
elif is_transcribe:
try:
gendat = whisper_generate(genparams)
global fullwhispermodelpath, has_audio_support
gendat = None
if genparams.get("audio_data","") and fullwhispermodelpath=="" and has_audio_support: #if we have no whisper model but an audio-capable projector, use that instead
adapter_obj = {} if chatcompl_adapter is None else chatcompl_adapter
user_message_start = adapter_obj.get("user_start", "### Instruction:")
assistant_message_start = adapter_obj.get("assistant_start", "### Response:")
assistant_message_gen = adapter_obj.get("assistant_gen", assistant_message_start)
prompt = f"{user_message_start} Transcribe all speech in the audio.\n{assistant_message_gen}"
rawaudio = genparams.get("audio_data","").replace("data:audio/wav;base64,","")
temp_poll = {
"prompt": prompt,
"max_length":300,
"temperature":0.1,
"top_k":1,
"rep_pen":1,
"ban_eos_token":False,
"audio": [rawaudio]
}
temp_poll_result = generate(genparams=temp_poll)
gendat = temp_poll_result['text']
else:
gendat = whisper_generate(genparams)
genresp = (json.dumps({"text":gendat}).encode())
self.send_response(200)
self.send_header('content-length', str(len(genresp)))