Merge pull request #5887 from oobabooga/dev

Merge dev branch

extensions/openai/completions.py

@@ -135,6 +135,7 @@ def convert_history(history):
     current_message = ""
     current_reply = ""
     user_input = ""
+    user_input_last = True
     system_message = ""
 
     # Multimodal: convert OpenAI format to multimodal extension format
@@ -188,13 +189,15 @@ def convert_history(history):
 
         if role == "user":
             user_input = content
+            user_input_last = True
             if current_message:
                 chat_dialogue.append([current_message, ''])
                 current_message = ""
 
             current_message = content
         elif role == "assistant":
             current_reply = content
+            user_input_last = False
             if current_message:
                 chat_dialogue.append([current_message, current_reply])
                 current_message = ""
@@ -204,13 +207,13 @@ def convert_history(history):
         elif role == "system":
             system_message = content
 
-    # if current_message:
-    #     chat_dialogue.append([current_message, ''])
+    if not user_input_last:
+        user_input = ""
 
     return user_input, system_message, {'internal': chat_dialogue, 'visible': copy.deepcopy(chat_dialogue)}
 
 
-def chat_completions_common(body: dict, is_legacy: bool = False, stream=False) -> dict:
+def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, prompt_only=False) -> dict:
     if body.get('functions', []):
         raise InvalidRequestError(message="functions is not supported.", param='functions')
 
@@ -310,14 +313,18 @@ def chat_streaming_chunk(content):
         #    chunk[resp_list][0]["logprobs"] = None
         return chunk
 
-    if stream:
-        yield chat_streaming_chunk('')
-
     # generate reply #######################################
-    prompt = generate_chat_prompt(user_input, generate_params)
+    prompt = generate_chat_prompt(user_input, generate_params, _continue=continue_)
+    if prompt_only:
+        yield {'prompt': prompt}
+        return
+
     token_count = len(encode(prompt)[0])
     debug_msg({'prompt': prompt, 'generate_params': generate_params})
 
+    if stream:
+        yield chat_streaming_chunk('')
+
     generator = generate_chat_reply(
         user_input, generate_params, regenerate=False, _continue=continue_, loading_message=False)
 

extensions/openai/models.py

@@ -9,7 +9,8 @@
 def get_current_model_info():
     return {
         'model_name': shared.model_name,
-        'lora_names': shared.lora_names
+        'lora_names': shared.lora_names,
+        'loader': shared.args.loader
     }
 
 

extensions/openai/script.py

@@ -3,6 +3,7 @@
 import logging
 import os
 import traceback
+from collections import deque
 from threading import Thread
 
 import speech_recognition as sr
@@ -31,6 +32,7 @@
 from .typing import (
     ChatCompletionRequest,
     ChatCompletionResponse,
+    ChatPromptResponse,
     CompletionRequest,
     CompletionResponse,
     DecodeRequest,
@@ -259,6 +261,15 @@ async def handle_logits(request_data: LogitsRequest):
     return JSONResponse(response)
 
 
+@app.post('/v1/internal/chat-prompt', response_model=ChatPromptResponse, dependencies=check_key)
+async def handle_chat_prompt(request: Request, request_data: ChatCompletionRequest):
+    path = request.url.path
+    is_legacy = "/generate" in path
+    generator = OAIcompletions.chat_completions_common(to_dict(request_data), is_legacy=is_legacy, prompt_only=True)
+    response = deque(generator, maxlen=1).pop()
+    return JSONResponse(response)
+
+
 @app.post("/v1/internal/stop-generation", dependencies=check_key)
 async def handle_stop_generation(request: Request):
     stop_everything_event()

extensions/openai/typing.py

@@ -124,6 +124,10 @@ class ChatCompletionResponse(BaseModel):
     usage: dict
 
 
+class ChatPromptResponse(BaseModel):
+    prompt: str
+
+
 class EmbeddingsRequest(BaseModel):
     input: str | List[str] | List[int] | List[List[int]]
     model: str | None = Field(default=None, description="Unused parameter. To change the model, set the OPENEDAI_EMBEDDING_MODEL and OPENEDAI_EMBEDDING_DEVICE environment variables before starting the server.")

extensions/whisper_stt/script.py

@@ -62,7 +62,7 @@ def ui():
                 whipser_model = gr.Dropdown(label='Whisper Model', value=params['whipser_model'], choices=["tiny.en", "base.en", "small.en", "medium.en", "tiny", "base", "small", "medium", "large"])
                 whipser_language = gr.Dropdown(label='Whisper Language', value=params['whipser_language'], choices=["chinese", "german", "spanish", "russian", "korean", "french", "japanese", "portuguese", "turkish", "polish", "catalan", "dutch", "arabic", "swedish", "italian", "indonesian", "hindi", "finnish", "vietnamese", "hebrew", "ukrainian", "greek", "malay", "czech", "romanian", "danish", "hungarian", "tamil", "norwegian", "thai", "urdu", "croatian", "bulgarian", "lithuanian", "latin", "maori", "malayalam", "welsh", "slovak", "telugu", "persian", "latvian", "bengali", "serbian", "azerbaijani", "slovenian", "kannada", "estonian", "macedonian", "breton", "basque", "icelandic", "armenian", "nepali", "mongolian", "bosnian", "kazakh", "albanian", "swahili", "galician", "marathi", "punjabi", "sinhala", "khmer", "shona", "yoruba", "somali", "afrikaans", "occitan", "georgian", "belarusian", "tajik", "sindhi", "gujarati", "amharic", "yiddish", "lao", "uzbek", "faroese", "haitian creole", "pashto", "turkmen", "nynorsk", "maltese", "sanskrit", "luxembourgish", "myanmar", "tibetan", "tagalog", "malagasy", "assamese", "tatar", "hawaiian", "lingala", "hausa", "bashkir", "javanese", "sundanese"])
 
-    audio.change(
+    audio.stop_recording(
         auto_transcribe, [audio, auto_submit, whipser_model, whipser_language], [shared.gradio['textbox'], audio]).then(
         None, auto_submit, None, js="(check) => {if (check) { document.getElementById('Generate').click() }}")
 

modules/models_settings.py

@@ -136,9 +136,6 @@ def get_model_metadata(model):
     if 'instruction_template' not in model_settings:
         model_settings['instruction_template'] = 'Alpaca'
 
-    if model_settings['instruction_template'] != 'Custom (obtained from model metadata)':
-        model_settings['instruction_template_str'] = chat.load_instruction_template(model_settings['instruction_template'])
-
     # Ignore rope_freq_base if set to the default value
     if 'rope_freq_base' in model_settings and model_settings['rope_freq_base'] == 10000:
         model_settings.pop('rope_freq_base')
@@ -150,6 +147,10 @@ def get_model_metadata(model):
             for k in settings[pat]:
                 model_settings[k] = settings[pat][k]
 
+    # Load instruction template if defined by name rather than by value
+    if model_settings['instruction_template'] != 'Custom (obtained from model metadata)':
+        model_settings['instruction_template_str'] = chat.load_instruction_template(model_settings['instruction_template'])
+
     return model_settings
 
 

requirements.txt

@@ -23,14 +23,14 @@ safetensors==0.4.*
 scipy
 sentencepiece
 tensorboard
-transformers==4.39.*
+transformers==4.40.*
 tqdm
 wandb
 
 # API
 SpeechRecognition==3.10.0
 flask_cloudflared==0.0.14
-sse-starlette==2.1.0
+sse-starlette==1.6.5
 tiktoken
 
 # llama-cpp-python (CPU only, AVX2)

requirements_amd.txt

@@ -21,14 +21,14 @@ safetensors==0.4.*
 scipy
 sentencepiece
 tensorboard
-transformers==4.39.*
+transformers==4.40.*
 tqdm
 wandb
 
 # API
 SpeechRecognition==3.10.0
 flask_cloudflared==0.0.14
-sse-starlette==2.1.0
+sse-starlette==1.6.5
 tiktoken
 
 # llama-cpp-python (CPU only, AVX2)

requirements_amd_noavx2.txt

@@ -21,14 +21,14 @@ safetensors==0.4.*
 scipy
 sentencepiece
 tensorboard
-transformers==4.39.*
+transformers==4.40.*
 tqdm
 wandb
 
 # API
 SpeechRecognition==3.10.0
 flask_cloudflared==0.0.14
-sse-starlette==2.1.0
+sse-starlette==1.6.5
 tiktoken
 
 # llama-cpp-python (CPU only, no AVX2)

requirements_apple_intel.txt

@@ -21,14 +21,14 @@ safetensors==0.4.*
 scipy
 sentencepiece
 tensorboard
-transformers==4.39.*
+transformers==4.40.*
 tqdm
 wandb
 
 # API
 SpeechRecognition==3.10.0
 flask_cloudflared==0.0.14
-sse-starlette==2.1.0
+sse-starlette==1.6.5
 tiktoken
 
 # Mac wheels

requirements_apple_silicon.txt

@@ -21,14 +21,14 @@ safetensors==0.4.*
 scipy
 sentencepiece
 tensorboard
-transformers==4.39.*
+transformers==4.40.*
 tqdm
 wandb
 
 # API
 SpeechRecognition==3.10.0
 flask_cloudflared==0.0.14
-sse-starlette==2.1.0
+sse-starlette==1.6.5
 tiktoken
 
 # Mac wheels

requirements_cpu_only.txt

@@ -21,14 +21,14 @@ safetensors==0.4.*
 scipy
 sentencepiece
 tensorboard
-transformers==4.39.*
+transformers==4.40.*
 tqdm
 wandb
 
 # API
 SpeechRecognition==3.10.0
 flask_cloudflared==0.0.14
-sse-starlette==2.1.0
+sse-starlette==1.6.5
 tiktoken
 
 # llama-cpp-python (CPU only, AVX2)

requirements_cpu_only_noavx2.txt

@@ -21,14 +21,14 @@ safetensors==0.4.*
 scipy
 sentencepiece
 tensorboard
-transformers==4.39.*
+transformers==4.40.*
 tqdm
 wandb
 
 # API
 SpeechRecognition==3.10.0
 flask_cloudflared==0.0.14
-sse-starlette==2.1.0
+sse-starlette==1.6.5
 tiktoken
 
 # llama-cpp-python (CPU only, no AVX2)

requirements_noavx2.txt

@@ -23,14 +23,14 @@ safetensors==0.4.*
 scipy
 sentencepiece
 tensorboard
-transformers==4.39.*
+transformers==4.40.*
 tqdm
 wandb
 
 # API
 SpeechRecognition==3.10.0
 flask_cloudflared==0.0.14
-sse-starlette==2.1.0
+sse-starlette==1.6.5
 tiktoken
 
 # llama-cpp-python (CPU only, no AVX2)

requirements_nowheels.txt

@@ -21,12 +21,12 @@ safetensors==0.4.*
 scipy
 sentencepiece
 tensorboard
-transformers==4.39.*
+transformers==4.40.*
 tqdm
 wandb
 
 # API
 SpeechRecognition==3.10.0
 flask_cloudflared==0.0.14
-sse-starlette==2.1.0
+sse-starlette==1.6.5
 tiktoken