Merge branch 'main' into main

.github/FUNDING.yml

@@ -0,0 +1 @@
+ko_fi: oobabooga

README.md

@@ -27,7 +27,7 @@ Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github.
 * [FlexGen offload](https://github.com/oobabooga/text-generation-webui/wiki/FlexGen).
 * [DeepSpeed ZeRO-3 offload](https://github.com/oobabooga/text-generation-webui/wiki/DeepSpeed).
 * Get responses via API, [with](https://github.com/oobabooga/text-generation-webui/blob/main/api-example-streaming.py) or [without](https://github.com/oobabooga/text-generation-webui/blob/main/api-example.py) streaming.
-* [Supports the LLaMA model](https://github.com/oobabooga/text-generation-webui/wiki/LLaMA-model).
+* [Supports the LLaMA model, including 4-bit mode](https://github.com/oobabooga/text-generation-webui/wiki/LLaMA-model).
 * [Supports the RWKV model](https://github.com/oobabooga/text-generation-webui/wiki/RWKV-model).
 * Supports softprompts.
 * [Supports extensions](https://github.com/oobabooga/text-generation-webui/wiki/Extensions).
@@ -60,11 +60,13 @@ pip3 install torch torchvision torchaudio --extra-index-url https://download.pyt
 conda install pytorch torchvision torchaudio git -c pytorch
 ```
 
+See also: [Installation instructions for human beings](https://github.com/oobabooga/text-generation-webui/wiki/Installation-instructions-for-human-beings).
+
 ## Installation option 2: one-click installers
 
-[oobabooga-windows.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga-windows.zip)
+[oobabooga-windows.zip](https://github.com/oobabooga/one-click-installers/archive/refs/heads/oobabooga-windows.zip)
 
-[oobabooga-linux.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga-linux.zip)
+[oobabooga-linux.zip](https://github.com/oobabooga/one-click-installers/archive/refs/heads/oobabooga-linux.zip)
 
 Just download the zip above, extract it, and double click on "install". The web UI and all its dependencies will be installed in the same folder.
 
@@ -139,7 +141,7 @@ Optionally, you can use the following command-line flags:
 | `--cpu`       | Use the CPU to generate text.|
 | `--load-in-8bit`  | Load the model with 8-bit precision.|
 | `--load-in-4bit`  | Load the model with 4-bit precision. Currently only works with LLaMA.|
-| `--gptq-bits`  |  Load a pre-quantized model with specified precision. 2, 3, 4 and 8bit are supported. Currently only works with LLaMA. |
+| `--gptq-bits GPTQ_BITS`  |  Load a pre-quantized model with specified precision. 2, 3, 4 and 8 (bit) are supported. Currently only works with LLaMA. |
 | `--bf16`  | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. |
 | `--auto-devices` | Automatically split the model across the available GPU(s) and CPU.|
 | `--disk` | If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk. |
@@ -155,12 +157,13 @@ Optionally, you can use the following command-line flags:
 | `--local_rank LOCAL_RANK`    | DeepSpeed: Optional argument for distributed setups. |
 |  `--rwkv-strategy RWKV_STRATEGY`         |    RWKV: The strategy to use while loading the model. Examples: "cpu fp32", "cuda fp16", "cuda fp16i8". |
 |  `--rwkv-cuda-on`                        |   RWKV: Compile the CUDA kernel for better performance. |
-| `--no-stream`   | Don't stream the text output in real time. This improves the text generation performance.|
+| `--no-stream`   | Don't stream the text output in real time. |
 | `--settings SETTINGS_FILE` | Load the default interface settings from this json file. See `settings-template.json` for an example. If you create a file called `settings.json`, this file will be loaded by default without the need to use the `--settings` flag.|
 |  `--extensions EXTENSIONS [EXTENSIONS ...]` |  The list of extensions to load. If you want to load more than one extension, write the names separated by spaces. |
 | `--listen`   | Make the web UI reachable from your local network.|
 |  `--listen-port LISTEN_PORT` | The listening port that the server will use. |
 | `--share`   | Create a public URL. This is useful for running the web UI on Google Colab or similar. |
+| `--auto-launch` | Open the web UI in the default browser upon launch. |
 | `--verbose`   | Print the prompts to the terminal. |
 
 Out of memory errors? [Check this guide](https://github.com/oobabooga/text-generation-webui/wiki/Low-VRAM-guide).
@@ -179,14 +182,10 @@ Check the [wiki](https://github.com/oobabooga/text-generation-webui/wiki/System-
 
 Pull requests, suggestions, and issue reports are welcome.
 
-Before reporting a bug, make sure that you have created a conda environment and installed the dependencies exactly as in the *Installation* section above.
-
-These issues are known:
-
-* 8-bit doesn't work properly on Windows or older GPUs.
-* DeepSpeed doesn't work properly on Windows.
+Before reporting a bug, make sure that you have:
 
-For these two, please try commenting on an existing issue instead of creating a new one.
+1. Created a conda environment and installed the dependencies exactly as in the *Installation* section above.
+2. [Searched](https://github.com/oobabooga/text-generation-webui/issues) to see if an issue already exists for the issue you encountered.
 
 ## Credits
 

extensions/silero_tts/script.py

@@ -1,8 +1,12 @@
+import time
 from pathlib import Path
 
 import gradio as gr
 import torch
 
+import modules.chat as chat
+import modules.shared as shared
+
 torch._C._jit_set_profiling_mode(False)
 
 params = {
@@ -12,10 +16,28 @@ params = {
     'model_id': 'v3_en',
     'sample_rate': 48000,
     'device': 'cpu',
+    'show_text': False,
+    'autoplay': True,
+    'voice_pitch': 'medium',
+    'voice_speed': 'medium',
 }
+
 current_params = params.copy()
 voices_by_gender = ['en_99', 'en_45', 'en_18', 'en_117', 'en_49', 'en_51', 'en_68', 'en_0', 'en_26', 'en_56', 'en_74', 'en_5', 'en_38', 'en_53', 'en_21', 'en_37', 'en_107', 'en_10', 'en_82', 'en_16', 'en_41', 'en_12', 'en_67', 'en_61', 'en_14', 'en_11', 'en_39', 'en_52', 'en_24', 'en_97', 'en_28', 'en_72', 'en_94', 'en_36', 'en_4', 'en_43', 'en_88', 'en_25', 'en_65', 'en_6', 'en_44', 'en_75', 'en_91', 'en_60', 'en_109', 'en_85', 'en_101', 'en_108', 'en_50', 'en_96', 'en_64', 'en_92', 'en_76', 'en_33', 'en_116', 'en_48', 'en_98', 'en_86', 'en_62', 'en_54', 'en_95', 'en_55', 'en_111', 'en_3', 'en_83', 'en_8', 'en_47', 'en_59', 'en_1', 'en_2', 'en_7', 'en_9', 'en_13', 'en_15', 'en_17', 'en_19', 'en_20', 'en_22', 'en_23', 'en_27', 'en_29', 'en_30', 'en_31', 'en_32', 'en_34', 'en_35', 'en_40', 'en_42', 'en_46', 'en_57', 'en_58', 'en_63', 'en_66', 'en_69', 'en_70', 'en_71', 'en_73', 'en_77', 'en_78', 'en_79', 'en_80', 'en_81', 'en_84', 'en_87', 'en_89', 'en_90', 'en_93', 'en_100', 'en_102', 'en_103', 'en_104', 'en_105', 'en_106', 'en_110', 'en_112', 'en_113', 'en_114', 'en_115']
-wav_idx = 0
+voice_pitches = ['x-low', 'low', 'medium', 'high', 'x-high']
+voice_speeds = ['x-slow', 'slow', 'medium', 'fast', 'x-fast']
+
+# Used for making text xml compatible, needed for voice pitch and speed control
+table = str.maketrans({
+    "<": "&lt;",
+    ">": "&gt;",
+    "&": "&amp;",
+    "'": "&apos;",
+    '"': "&quot;",
+})
+
+def xmlesc(txt):
+    return txt.translate(table)
 
 def load_model():
     model, example_text = torch.hub.load(repo_or_dir='snakers4/silero-models', model='silero_tts', language=params['language'], speaker=params['model_id'])
@@ -33,12 +55,32 @@ def remove_surrounded_chars(string):
             new_string += char
     return new_string
 
+def remove_tts_from_history(name1, name2):
+    for i, entry in enumerate(shared.history['internal']):
+        shared.history['visible'][i] = [shared.history['visible'][i][0], entry[1]]
+    return chat.generate_chat_output(shared.history['visible'], name1, name2, shared.character)
+
+def toggle_text_in_history(name1, name2):
+    for i, entry in enumerate(shared.history['visible']):
+        visible_reply = entry[1]
+        if visible_reply.startswith('<audio'):
+            if params['show_text']:
+                reply = shared.history['internal'][i][1]
+                shared.history['visible'][i] = [shared.history['visible'][i][0], f"{visible_reply.split('</audio>')[0]}</audio>\n\n{reply}"]
+            else:
+                shared.history['visible'][i] = [shared.history['visible'][i][0], f"{visible_reply.split('</audio>')[0]}</audio>"]
+    return chat.generate_chat_output(shared.history['visible'], name1, name2, shared.character)
+
 def input_modifier(string):
     """
     This function is applied to your text inputs before
     they are fed into the model.
     """
 
+    # Remove autoplay from the last reply
+    if (shared.args.chat or shared.args.cai_chat) and len(shared.history['internal']) > 0:
+        shared.history['visible'][-1] = [shared.history['visible'][-1][0], shared.history['visible'][-1][1].replace('controls autoplay>','controls>')]
+
     return string
 
 def output_modifier(string):
@@ -46,7 +88,7 @@ def output_modifier(string):
     This function is applied to the model outputs.
     """
 
-    global wav_idx, model, current_params
+    global model, current_params
 
     for i in params:
         if params[i] != current_params[i]:
@@ -57,6 +99,7 @@ def output_modifier(string):
     if params['activate'] == False:
         return string
 
+    original_string = string
     string = remove_surrounded_chars(string)
     string = string.replace('"', '')
     string = string.replace('“', '')
@@ -64,13 +107,17 @@ def output_modifier(string):
     string = string.strip()
 
     if string == '':
-        string = 'empty reply, try regenerating'
-
-    output_file = Path(f'extensions/silero_tts/outputs/{wav_idx:06d}.wav')
-    model.save_wav(text=string, speaker=params['speaker'], sample_rate=int(params['sample_rate']), audio_path=str(output_file))
-
-    string = f'<audio src="file/{output_file.as_posix()}" controls></audio>'
-    wav_idx += 1
+        string = '*Empty reply, try regenerating*'
+    else:
+        output_file = Path(f'extensions/silero_tts/outputs/{shared.character}_{int(time.time())}.wav')
+        prosody = '<prosody rate="{}" pitch="{}">'.format(params['voice_speed'], params['voice_pitch'])
+        silero_input = f'<speak>{prosody}{xmlesc(string)}</prosody></speak>'
+        model.save_wav(ssml_text=silero_input, speaker=params['speaker'], sample_rate=int(params['sample_rate']), audio_path=str(output_file))
+
+        autoplay = 'autoplay' if params['autoplay'] else ''
+        string = f'<audio src="file/{output_file.as_posix()}" controls {autoplay}></audio>'
+        if params['show_text']:
+            string += f'\n\n{original_string}'
 
     return string
 
@@ -85,9 +132,36 @@ def bot_prefix_modifier(string):
 
 def ui():
     # Gradio elements
-    activate = gr.Checkbox(value=params['activate'], label='Activate TTS')
-    voice = gr.Dropdown(value=params['speaker'], choices=voices_by_gender, label='TTS voice')
+    with gr.Accordion("Silero TTS"):
+        with gr.Row():
+            activate = gr.Checkbox(value=params['activate'], label='Activate TTS')
+            autoplay = gr.Checkbox(value=params['autoplay'], label='Play TTS automatically')
+        show_text = gr.Checkbox(value=params['show_text'], label='Show message text under audio player')
+        voice = gr.Dropdown(value=params['speaker'], choices=voices_by_gender, label='TTS voice')
+        with gr.Row():
+            v_pitch = gr.Dropdown(value=params['voice_pitch'], choices=voice_pitches, label='Voice pitch')
+            v_speed = gr.Dropdown(value=params['voice_speed'], choices=voice_speeds, label='Voice speed')
+        with gr.Row():
+            convert = gr.Button('Permanently replace audios with the message texts')
+            convert_cancel = gr.Button('Cancel', visible=False)
+            convert_confirm = gr.Button('Confirm (cannot be undone)', variant="stop", visible=False)
+
+    # Convert history with confirmation
+    convert_arr = [convert_confirm, convert, convert_cancel]
+    convert.click(lambda :[gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)], None, convert_arr)
+    convert_confirm.click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, convert_arr)
+    convert_confirm.click(remove_tts_from_history, [shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'])
+    convert_confirm.click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
+    convert_cancel.click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, convert_arr)
+
+    # Toggle message text in history
+    show_text.change(lambda x: params.update({"show_text": x}), show_text, None)
+    show_text.change(toggle_text_in_history, [shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'])
+    show_text.change(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
 
     # Event functions to update the parameters in the backend
     activate.change(lambda x: params.update({"activate": x}), activate, None)
+    autoplay.change(lambda x: params.update({"autoplay": x}), autoplay, None)
     voice.change(lambda x: params.update({"speaker": x}), voice, None)
+    v_pitch.change(lambda x: params.update({"voice_pitch": x}), v_pitch, None)
+    v_speed.change(lambda x: params.update({"voice_speed": x}), v_speed, None)

modules/RWKV.py

@@ -25,10 +25,10 @@ class RWKVModel:
         tokenizer_path = Path(f"{path.parent}/20B_tokenizer.json")
 
         if shared.args.rwkv_strategy is None:
-            model = RWKV(model=os.path.abspath(path), strategy=f'{device} {dtype}')
+            model = RWKV(model=str(path), strategy=f'{device} {dtype}')
         else:
-            model = RWKV(model=os.path.abspath(path), strategy=shared.args.rwkv_strategy)
-        pipeline = PIPELINE(model, os.path.abspath(tokenizer_path))
+            model = RWKV(model=str(path), strategy=shared.args.rwkv_strategy)
+        pipeline = PIPELINE(model, str(tokenizer_path))
 
         result = self()
         result.pipeline = pipeline
@@ -61,7 +61,7 @@ class RWKVTokenizer:
     @classmethod
     def from_pretrained(self, path):
         tokenizer_path = path / "20B_tokenizer.json"
-        tokenizer = Tokenizer.from_file(os.path.abspath(tokenizer_path))
+        tokenizer = Tokenizer.from_file(str(tokenizer_path))
 
         result = self()
         result.tokenizer = tokenizer

modules/chat.py

@@ -22,6 +22,12 @@ def clean_chat_message(text):
     text = text.strip()
     return text
 
+def generate_chat_output(history, name1, name2, character):
+    if shared.args.cai_chat:
+        return generate_chat_html(history, name1, name2, character)
+    else:
+        return history
+
 def generate_chat_prompt(user_input, max_new_tokens, name1, name2, context, chat_prompt_size, impersonate=False):
     user_input = clean_chat_message(user_input)
     rows = [f"{context.strip()}\n"]
@@ -53,7 +59,6 @@ def generate_chat_prompt(user_input, max_new_tokens, name1, name2, context, chat
 
 def extract_message_from_reply(question, reply, name1, name2, check, impersonate=False):
     next_character_found = False
-    substring_found = False
 
     asker = name1 if not impersonate else name2
     replier = name2 if not impersonate else name1
@@ -79,15 +84,15 @@ def extract_message_from_reply(question, reply, name1, name2, check, impersonate
             next_character_found = True
         reply = clean_chat_message(reply)
 
-        # Detect if something like "\nYo" is generated just before
-        # "\nYou:" is completed
-        tmp = f"\n{asker}:"
-        for j in range(1, len(tmp)):
-            if reply[-j:] == tmp[:j]:
+        # If something like "\nYo" is generated just before "\nYou:"
+        # is completed, trim it
+        next_turn = f"\n{asker}:"
+        for j in range(len(next_turn)-1, 0, -1):
+            if reply[-j:] == next_turn[:j]:
                 reply = reply[:-j]
-                substring_found = True
+                break
 
-    return reply, next_character_found, substring_found
+    return reply, next_character_found
 
 def stop_everything_event():
     shared.stop_everything = True
@@ -122,7 +127,6 @@ def chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical
         prompt = custom_generate_chat_prompt(text, max_new_tokens, name1, name2, context, chat_prompt_size)
 
     if not regenerate:
-        # Display user input and "*is typing...*" imediately
         yield shared.history['visible']+[[visible_text, '*Is typing...*']]
 
     # Generate
@@ -131,7 +135,7 @@ def chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical
         for reply in generate_reply(f"{prompt}{' ' if len(reply) > 0 else ''}{reply}", max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, eos_token=eos_token, stopping_string=f"\n{name1}:"):
 
             # Extracting the reply
-            reply, next_character_found, substring_found = extract_message_from_reply(prompt, reply, name1, name2, check)
+            reply, next_character_found = extract_message_from_reply(prompt, reply, name1, name2, check)
             visible_reply = re.sub("(<USER>|<user>|{{user}})", name1_original, reply)
             visible_reply = apply_extensions(visible_reply, "output")
             if shared.args.chat:
@@ -148,7 +152,7 @@ def chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical
 
             shared.history['internal'][-1] = [text, reply]
             shared.history['visible'][-1] = [visible_text, visible_reply]
-            if not substring_found and not shared.args.no_stream:
+            if not shared.args.no_stream:
                 yield shared.history['visible']
             if next_character_found:
                 break
@@ -163,15 +167,12 @@ def impersonate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typ
 
     prompt = generate_chat_prompt(text, max_new_tokens, name1, name2, context, chat_prompt_size, impersonate=True)
 
-    # Display "*is typing...*" imediately
-    yield '*Is typing...*'
-
     reply = ''
+    yield '*Is typing...*'
     for i in range(chat_generation_attempts):
         for reply in generate_reply(prompt+reply, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, eos_token=eos_token, stopping_string=f"\n{name2}:"):
-            reply, next_character_found, substring_found = extract_message_from_reply(prompt, reply, name1, name2, check, impersonate=True)
-            if not substring_found:
-                yield reply
+            reply, next_character_found = extract_message_from_reply(prompt, reply, name1, name2, check, impersonate=True)
+            yield reply
             if next_character_found:
                 break
         yield reply
@@ -182,21 +183,18 @@ def cai_chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typ
 
 def regenerate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size, chat_generation_attempts=1):
     if (shared.character != 'None' and len(shared.history['visible']) == 1) or len(shared.history['internal']) == 0:
-        if shared.args.cai_chat:
-            yield generate_chat_html(shared.history['visible'], name1, name2, shared.character)
-        else:
-            yield shared.history['visible']
+        yield generate_chat_output(shared.history['visible'], name1, name2, shared.character)
     else:
         last_visible = shared.history['visible'].pop()
         last_internal = shared.history['internal'].pop()
 
+        yield generate_chat_output(shared.history['visible']+[[last_visible[0], '*Is typing...*']], name1, name2, shared.character)
         for _history in chatbot_wrapper(last_internal[0], max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size, chat_generation_attempts, regenerate=True):
             if shared.args.cai_chat:
                 shared.history['visible'][-1] = [last_visible[0], _history[-1][1]]
-                yield generate_chat_html(shared.history['visible'], name1, name2, shared.character)
             else:
                 shared.history['visible'][-1] = (last_visible[0], _history[-1][1])
-                yield shared.history['visible']
+            yield generate_chat_output(shared.history['visible'], name1, name2, shared.character)
 
 def remove_last_message(name1, name2):
     if len(shared.history['visible']) > 0 and not shared.history['internal'][-1][0] == '<|BEGIN-VISIBLE-CHAT|>':
@@ -204,6 +202,7 @@ def remove_last_message(name1, name2):
         shared.history['internal'].pop()
     else:
         last = ['', '']
+
     if shared.args.cai_chat:
         return generate_chat_html(shared.history['visible'], name1, name2, shared.character), last[0]
     else:
@@ -223,10 +222,7 @@ def replace_last_reply(text, name1, name2):
             shared.history['visible'][-1] = (shared.history['visible'][-1][0], text)
         shared.history['internal'][-1][1] = apply_extensions(text, "input")
 
-    if shared.args.cai_chat:
-        return generate_chat_html(shared.history['visible'], name1, name2, shared.character)
-    else:
-        return shared.history['visible']
+    return generate_chat_output(shared.history['visible'], name1, name2, shared.character)
 
 def clear_html():
     return generate_chat_html([], "", "", shared.character)
@@ -246,10 +242,8 @@ def clear_chat_log(name1, name2):
     else:
         shared.history['internal'] = []
         shared.history['visible'] = []
-    if shared.args.cai_chat:
-        return generate_chat_html(shared.history['visible'], name1, name2, shared.character)
-    else:
-        return shared.history['visible']
+
+    return generate_chat_output(shared.history['visible'], name1, name2, shared.character)
 
 def redraw_html(name1, name2):
     return generate_chat_html(shared.history['visible'], name1, name2, shared.character)

modules/quantized_LLaMA.py

@@ -1,4 +1,3 @@
-import os
 import sys
 from pathlib import Path
 
@@ -7,7 +6,7 @@ import torch
 
 import modules.shared as shared
 
-sys.path.insert(0, os.path.abspath(Path("repositories/GPTQ-for-LLaMa")))
+sys.path.insert(0, str(Path("repositories/GPTQ-for-LLaMa")))
 from llama import load_quant
 
 
@@ -41,9 +40,9 @@ def load_quantized_LLaMA(model_name):
         print(f"Could not find {pt_model}, exiting...")
         exit()
 
-    model = load_quant(path_to_model, os.path.abspath(pt_path), bits)
+    model = load_quant(str(path_to_model), str(pt_path), bits)
 
-    # Multi-GPU setup
+    # Multiple GPUs or GPU+CPU
     if shared.args.gpu_memory:
         max_memory = {}
         for i in range(len(shared.args.gpu_memory)):

modules/shared.py

@@ -85,12 +85,12 @@ parser.add_argument('--nvme-offload-dir', type=str, help='DeepSpeed: Directory t
 parser.add_argument('--local_rank', type=int, default=0, help='DeepSpeed: Optional argument for distributed setups.')
 parser.add_argument('--rwkv-strategy', type=str, default=None, help='RWKV: The strategy to use while loading the model. Examples: "cpu fp32", "cuda fp16", "cuda fp16i8".')
 parser.add_argument('--rwkv-cuda-on', action='store_true', help='RWKV: Compile the CUDA kernel for better performance.')
-parser.add_argument('--no-stream', action='store_true', help='Don\'t stream the text output in real time. This improves the text generation performance.')
+parser.add_argument('--no-stream', action='store_true', help='Don\'t stream the text output in real time.')
 parser.add_argument('--settings', type=str, help='Load the default interface settings from this json file. See settings-template.json for an example. If you create a file called settings.json, this file will be loaded by default without the need to use the --settings flag.')
 parser.add_argument('--extensions', type=str, nargs="+", help='The list of extensions to load. If you want to load more than one extension, write the names separated by spaces.')
 parser.add_argument('--listen', action='store_true', help='Make the web UI reachable from your local network.')
 parser.add_argument('--listen-port', type=int, help='The listening port that the server will use.')
 parser.add_argument('--share', action='store_true', help='Create a public URL. This is useful for running the web UI on Google Colab or similar.')
+parser.add_argument('--auto-launch', action='store_true', default=False, help='Open the web UI in the default browser upon launch.')
 parser.add_argument('--verbose', action='store_true', help='Print the prompts to the terminal.')
-parser.add_argument('--auto-launch', action='store_true', default=False, help='Open the web UI in the default browser upon launch')
 args = parser.parse_args()

modules/text_generation.py

@@ -37,9 +37,13 @@ def encode(prompt, tokens_to_generate=0, add_special_tokens=True):
             return input_ids.cuda()
 
 def decode(output_ids):
-    reply = shared.tokenizer.decode(output_ids, skip_special_tokens=True)
-    reply = reply.replace(r'<|endoftext|>', '')
-    return reply
+    # Open Assistant relies on special tokens like <|endoftext|>
+    if re.match('oasst-*', shared.model_name.lower()):
+        return shared.tokenizer.decode(output_ids, skip_special_tokens=False)
+    else:
+        reply = shared.tokenizer.decode(output_ids, skip_special_tokens=True)
+        reply = reply.replace(r'<|endoftext|>', '')
+        return reply
 
 def generate_softprompt_input_tensors(input_ids):
     inputs_embeds = shared.model.transformer.wte(input_ids)
@@ -119,7 +123,9 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
     original_input_ids = input_ids
     output = input_ids[0]
     cuda = "" if (shared.args.cpu or shared.args.deepspeed or shared.args.flexgen) else ".cuda()"
-    n = shared.tokenizer.eos_token_id if eos_token is None else int(encode(eos_token)[0][-1])
+    eos_token_ids = [shared.tokenizer.eos_token_id] if shared.tokenizer.eos_token_id is not None else []
+    if eos_token is not None:
+        eos_token_ids.append(int(encode(eos_token)[0][-1]))
     stopping_criteria_list = transformers.StoppingCriteriaList()
     if stopping_string is not None:
         # Copied from https://github.com/PygmalionAI/gradio-ui/blob/master/src/model.py
@@ -129,7 +135,7 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
     if not shared.args.flexgen:
         generate_params = [
             f"max_new_tokens=max_new_tokens",
-            f"eos_token_id={n}",
+            f"eos_token_id={eos_token_ids}",
             f"stopping_criteria=stopping_criteria_list",
             f"do_sample={do_sample}",
             f"temperature={temperature}",
@@ -149,7 +155,7 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
             f"max_new_tokens={max_new_tokens if shared.args.no_stream else 8}",
             f"do_sample={do_sample}",
             f"temperature={temperature}",
-            f"stop={n}",
+            f"stop={eos_token_ids[-1]}",
         ]
     if shared.args.deepspeed:
         generate_params.append("synced_gpus=True")
@@ -196,10 +202,12 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
 
                     if not (shared.args.chat or shared.args.cai_chat):
                         reply = original_question + apply_extensions(reply[len(question):], "output")
-                    yield formatted_outputs(reply, shared.model_name)
 
-                    if output[-1] == n:
+                    if output[-1] in eos_token_ids:
                         break
+                    yield formatted_outputs(reply, shared.model_name)
+
+                yield formatted_outputs(reply, shared.model_name)
 
         # Stream the output naively for FlexGen since it doesn't support 'stopping_criteria'
         else:
@@ -213,15 +221,17 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
 
                 if not (shared.args.chat or shared.args.cai_chat):
                     reply = original_question + apply_extensions(reply[len(question):], "output")
-                yield formatted_outputs(reply, shared.model_name)
 
-                if np.count_nonzero(input_ids[0] == n) < np.count_nonzero(output == n):
+                if np.count_nonzero(np.isin(input_ids[0], eos_token_ids)) < np.count_nonzero(np.isin(output, eos_token_ids)):
                     break
+                yield formatted_outputs(reply, shared.model_name)
 
                 input_ids = np.reshape(output, (1, output.shape[0]))
                 if shared.soft_prompt:
                     inputs_embeds, filler_input_ids = generate_softprompt_input_tensors(input_ids)
 
+            yield formatted_outputs(reply, shared.model_name)
+
     finally:
         t1 = time.time()
         print(f"Output generated in {(t1-t0):.2f} seconds ({(len(output)-len(original_input_ids[0]))/(t1-t0):.2f} tokens/s, {len(output)-len(original_input_ids[0])} tokens)")

requirements.txt

@@ -1,12 +1,12 @@
-accelerate==0.16.0
+accelerate==0.17.0
 bitsandbytes==0.37.0
 flexgen==0.1.7
 gradio==3.18.0
 numpy
 requests
-rwkv==0.1.0
-safetensors==0.2.8
+rwkv==0.3.1
+safetensors==0.3.0
 sentencepiece
 tqdm
 markdown
-git+https://github.com/zphang/transformers@llama_push
+git+https://github.com/zphang/transformers.git@68d640f7c368bcaaaecfc678f11908ebbd3d6176

server.py

@@ -269,10 +269,10 @@ if shared.args.chat or shared.args.cai_chat:
 
         function_call = 'chat.cai_chatbot_wrapper' if shared.args.cai_chat else 'chat.chatbot_wrapper'
 
-        gen_events.append(shared.gradio['Generate'].click(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=False, api_name='textgen'))
-        gen_events.append(shared.gradio['textbox'].submit(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=False))
-        gen_events.append(shared.gradio['Regenerate'].click(chat.regenerate_wrapper, shared.input_params, shared.gradio['display'], show_progress=False))
-        gen_events.append(shared.gradio['Impersonate'].click(chat.impersonate_wrapper, shared.input_params, shared.gradio['textbox'], show_progress=False))
+        gen_events.append(shared.gradio['Generate'].click(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream, api_name='textgen'))
+        gen_events.append(shared.gradio['textbox'].submit(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
+        gen_events.append(shared.gradio['Regenerate'].click(chat.regenerate_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
+        gen_events.append(shared.gradio['Impersonate'].click(chat.impersonate_wrapper, shared.input_params, shared.gradio['textbox'], show_progress=shared.args.no_stream))
         shared.gradio['Stop'].click(chat.stop_everything_event, [], [], cancels=gen_events)
 
         shared.gradio['Copy last reply'].click(chat.send_last_reply_to_input, [], shared.gradio['textbox'], show_progress=shared.args.no_stream)