mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-23 08:28:21 +01:00
commit
af876095e2
@ -67,8 +67,56 @@ This extension uses the following parameters (from `settings.json`):
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## Usage through API
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### Chat completions endpoint
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#### With an image URL
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```shell
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curl http://127.0.0.1:5000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"messages": [
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{
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"role": "user",
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"image_url": "https://avatars.githubusercontent.com/u/112222186?v=4"
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},
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{
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"role": "user",
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"content": "What is unusual about this image?"
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}
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]
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}'
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```
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#### With a Base64 image
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```python
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import base64
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import json
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import requests
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img = open('image.jpg', 'rb')
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img_bytes = img.read()
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img_base64 = base64.b64encode(img_bytes).decode('utf-8')
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data = { "messages": [
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{
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"role": "user",
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"image_url": f"data:image/jpeg;base64,{img_base64}"
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},
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{
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"role": "user",
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"content": "what is unusual about this image?"
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}
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]
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}
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response = requests.post('http://127.0.0.1:5000/v1/chat/completions', json=data)
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print(response.text)
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```
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You can run the multimodal inference through API, by inputting the images to prompt. Images are embedded like so: `f'<img src="data:image/jpeg;base64,{img_str}">'`, where `img_str` is base-64 jpeg data. Note that you will need to launch `server.py` with the arguments `--api --extensions multimodal`.
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### Completions endpoint
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Python example:
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```Python
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@ -1,10 +1,15 @@
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import base64
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import copy
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import re
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import time
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from collections import deque
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from io import BytesIO
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import requests
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import tiktoken
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import torch
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import torch.nn.functional as F
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from PIL import Image
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from transformers import LogitsProcessor, LogitsProcessorList
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from extensions.openai.errors import InvalidRequestError
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@ -140,7 +145,25 @@ def convert_history(history):
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system_message = ""
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for entry in history:
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if "image_url" in entry:
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image_url = entry['image_url']
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if "base64" in image_url:
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image_url = re.sub('^data:image/.+;base64,', '', image_url)
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img = Image.open(BytesIO(base64.b64decode(image_url)))
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else:
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try:
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my_res = requests.get(image_url)
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img = Image.open(BytesIO(my_res.content))
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except Exception:
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raise 'Image cannot be loaded from the URL!'
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buffered = BytesIO()
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img.save(buffered, format="JPEG")
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img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
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content = f'<img src="data:image/jpeg;base64,{img_str}">'
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else:
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content = entry["content"]
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role = entry["role"]
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if role == "user":
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@ -182,7 +205,8 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False) -
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raise InvalidRequestError(message="messages: missing role", param='messages')
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elif m['role'] == 'function':
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raise InvalidRequestError(message="role: function is not supported.", param='messages')
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if 'content' not in m:
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if 'content' not in m and "image_url" not in m:
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raise InvalidRequestError(message="messages: missing content", param='messages')
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# Chat Completions
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25
instruction-templates/Synthia-CoT.yaml
Normal file
25
instruction-templates/Synthia-CoT.yaml
Normal file
@ -0,0 +1,25 @@
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instruction_template: |-
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{%- set found_item = false -%}
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{%- for message in messages -%}
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{%- if message['role'] == 'system' -%}
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{%- set found_item = true -%}
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{%- endif -%}
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{%- endfor -%}
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{%- if not found_item -%}
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{{-'SYSTEM: ' + 'Elaborate on the topic using a Tree of Thoughts and backtrack when necessary to construct a clear, cohesive Chain of Thought reasoning. Always answer without hesitation.' + '\n' -}}
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{%- endif %}
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{%- for message in messages %}
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{%- if message['role'] == 'system' -%}
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{{-'SYSTEM: ' + message['content'] + '\n' -}}
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{%- else -%}
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{%- if message['role'] == 'user' -%}
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{{-'USER: ' + message['content'] + '\n'-}}
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{%- else -%}
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{{-'ASSISTANT: ' + message['content'] + '</s>\n' -}}
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{%- endif -%}
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{%- endif -%}
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{%- endfor -%}
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{%- if add_generation_prompt -%}
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{{-'ASSISTANT:'-}}
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{%- endif -%}
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25
instruction-templates/Synthia.yaml
Normal file
25
instruction-templates/Synthia.yaml
Normal file
@ -0,0 +1,25 @@
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instruction_template: |-
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{%- set found_item = false -%}
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{%- for message in messages -%}
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{%- if message['role'] == 'system' -%}
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{%- set found_item = true -%}
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{%- endif -%}
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{%- endfor -%}
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{%- if not found_item -%}
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{{-'SYSTEM: ' + 'Answer the question thoughtfully and intelligently. Always answer without hesitation.' + '\n' -}}
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{%- endif %}
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{%- for message in messages %}
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{%- if message['role'] == 'system' -%}
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{{-'SYSTEM: ' + message['content'] + '\n' -}}
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{%- else -%}
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{%- if message['role'] == 'user' -%}
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{{-'USER: ' + message['content'] + '\n'-}}
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{%- else -%}
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{{-'ASSISTANT: ' + message['content'] + '</s>\n' -}}
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{%- endif -%}
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{%- endif -%}
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{%- endfor -%}
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{%- if add_generation_prompt -%}
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{{-'ASSISTANT:'-}}
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{%- endif -%}
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@ -188,3 +188,5 @@
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instruction_template: 'ChatML'
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(dolphin).*:
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instruction_template: 'ChatML'
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.*synthia:
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instruction_template: 'Synthia'
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@ -482,6 +482,7 @@ def clear_torch_cache():
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def unload_model():
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shared.model = shared.tokenizer = None
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shared.model_name = 'None'
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shared.lora_names = []
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shared.model_dirty_from_training = False
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clear_torch_cache()
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@ -45,6 +45,7 @@ settings = {
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'truncation_length_min': 0,
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'truncation_length_max': 200000,
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'max_tokens_second': 0,
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'max_updates_second': 0,
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'custom_stopping_strings': '',
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'custom_token_bans': '',
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'auto_max_new_tokens': False,
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@ -77,6 +77,10 @@ def _generate_reply(question, state, stopping_strings=None, is_chat=False, escap
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state = copy.deepcopy(state)
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state['stream'] = True
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min_update_interval = 0
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if state.get('max_updates_second', 0) > 0:
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min_update_interval = 1 / state['max_updates_second']
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# Generate
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for reply in generate_func(question, original_question, seed, state, stopping_strings, is_chat=is_chat):
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reply, stop_found = apply_stopping_strings(reply, all_stop_strings)
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@ -94,10 +98,9 @@ def _generate_reply(question, state, stopping_strings=None, is_chat=False, escap
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last_update = time.time()
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yield reply
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# Limit updates to 24 or 5 per second to avoid lag in the Gradio UI
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# Limit updates to avoid lag in the Gradio UI
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# API updates are not limited
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else:
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min_update_interval = 0 if not for_ui else 0.2 if (shared.args.listen or shared.args.share) else 0.0417
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if cur_time - last_update > min_update_interval:
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last_update = cur_time
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yield reply
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@ -265,7 +268,14 @@ def apply_stopping_strings(reply, all_stop_strings):
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def get_reply_from_output_ids(output_ids, state, starting_from=0):
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reply = decode(output_ids[starting_from:], state['skip_special_tokens'])
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if (hasattr(shared.tokenizer, 'convert_ids_to_tokens') and len(output_ids) > starting_from and shared.tokenizer.convert_ids_to_tokens(int(output_ids[starting_from])).startswith('▁')) and not reply.startswith(' '):
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# Handle tokenizers that do not add the leading space for the first token
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if (hasattr(shared.tokenizer, 'convert_ids_to_tokens') and len(output_ids) > starting_from) and not reply.startswith(' '):
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first_token = shared.tokenizer.convert_ids_to_tokens(int(output_ids[starting_from]))
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if isinstance(first_token, (bytes,)):
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first_token = first_token.decode('utf8')
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if first_token.startswith('▁'):
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reply = ' ' + reply
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return reply
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@ -110,6 +110,7 @@ def list_interface_input_elements():
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'max_new_tokens',
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'auto_max_new_tokens',
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'max_tokens_second',
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'max_updates_second',
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'seed',
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'temperature',
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'temperature_last',
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@ -66,7 +66,9 @@ def create_ui(default_preset):
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with gr.Row():
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with gr.Column():
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shared.gradio['truncation_length'] = gr.Slider(value=get_truncation_length(), minimum=shared.settings['truncation_length_min'], maximum=shared.settings['truncation_length_max'], step=256, label='Truncate the prompt up to this length', info='The leftmost tokens are removed if the prompt exceeds this length. Most models require this to be at most 2048.')
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shared.gradio['max_tokens_second'] = gr.Slider(value=shared.settings['max_tokens_second'], minimum=0, maximum=20, step=1, label='Maximum number of tokens/second', info='To make text readable in real time.')
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shared.gradio['max_tokens_second'] = gr.Slider(value=shared.settings['max_tokens_second'], minimum=0, maximum=20, step=1, label='Maximum tokens/second', info='To make text readable in real time.')
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shared.gradio['max_updates_second'] = gr.Slider(value=shared.settings['max_updates_second'], minimum=0, maximum=24, step=1, label='Maximum UI updates/second', info='Set this if you experience lag in the UI during streaming.')
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shared.gradio['custom_stopping_strings'] = gr.Textbox(lines=1, value=shared.settings["custom_stopping_strings"] or None, label='Custom stopping strings', info='In addition to the defaults. Written between "" and separated by commas.', placeholder='"\\n", "\\nYou:"')
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shared.gradio['custom_token_bans'] = gr.Textbox(value=shared.settings['custom_token_bans'] or None, label='Custom token bans', info='Specific token IDs to ban from generating, comma-separated. The IDs can be found in the Default or Notebook tab.')
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@ -5,6 +5,7 @@ einops
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exllamav2==0.0.11; platform_system != "Darwin" and platform_machine != "x86_64"
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gradio==3.50.*
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hqq==0.1.1.post1
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lm_eval==0.3.0
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markdown
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numpy==1.24.*
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optimum==1.16.*
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@ -98,4 +99,4 @@ https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_
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https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_llama-0.1.1+cu121-cp39-cp39-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.9"
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https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_llama-0.1.1+cu121-cp38-cp38-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.8"
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https://github.com/jllllll/ctransformers-cuBLAS-wheels/releases/download/AVX2/ctransformers-0.2.27+cu121-py3-none-any.whl
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autoawq==0.1.7; platform_system == "Linux" or platform_system == "Windows"
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autoawq==0.1.8; platform_system == "Linux" or platform_system == "Windows"
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@ -5,6 +5,7 @@ einops
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exllamav2==0.0.11; platform_system == "Windows" or python_version < "3.10" or python_version > "3.11" or platform_machine != "x86_64"
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gradio==3.50.*
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hqq==0.1.1.post1
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lm_eval==0.3.0
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markdown
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numpy==1.24.*
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optimum==1.16.*
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@ -5,6 +5,7 @@ einops
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exllamav2==0.0.11; platform_system == "Windows" or python_version < "3.10" or python_version > "3.11" or platform_machine != "x86_64"
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gradio==3.50.*
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hqq==0.1.1.post1
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lm_eval==0.3.0
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markdown
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numpy==1.24.*
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optimum==1.16.*
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@ -5,6 +5,7 @@ einops
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exllamav2==0.0.11
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gradio==3.50.*
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hqq==0.1.1.post1
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lm_eval==0.3.0
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markdown
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numpy==1.24.*
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optimum==1.16.*
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@ -5,6 +5,7 @@ einops
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exllamav2==0.0.11
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gradio==3.50.*
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hqq==0.1.1.post1
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lm_eval==0.3.0
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markdown
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numpy==1.24.*
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optimum==1.16.*
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@ -5,6 +5,7 @@ einops
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exllamav2==0.0.11
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gradio==3.50.*
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hqq==0.1.1.post1
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lm_eval==0.3.0
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markdown
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numpy==1.24.*
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optimum==1.16.*
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@ -5,6 +5,7 @@ einops
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exllamav2==0.0.11
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gradio==3.50.*
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hqq==0.1.1.post1
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lm_eval==0.3.0
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markdown
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numpy==1.24.*
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optimum==1.16.*
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@ -5,6 +5,7 @@ einops
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exllamav2==0.0.11; platform_system != "Darwin" and platform_machine != "x86_64"
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gradio==3.50.*
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hqq==0.1.1.post1
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lm_eval==0.3.0
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markdown
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numpy==1.24.*
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optimum==1.16.*
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@ -98,4 +99,4 @@ https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_
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https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_llama-0.1.1+cu121-cp39-cp39-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.9"
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https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_llama-0.1.1+cu121-cp38-cp38-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.8"
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https://github.com/jllllll/ctransformers-cuBLAS-wheels/releases/download/AVX/ctransformers-0.2.27+cu121-py3-none-any.whl
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autoawq==0.1.7; platform_system == "Linux" or platform_system == "Windows"
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autoawq==0.1.8; platform_system == "Linux" or platform_system == "Windows"
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|
@ -5,6 +5,7 @@ einops
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exllamav2==0.0.11
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gradio==3.50.*
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hqq==0.1.1.post1
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lm_eval==0.3.0
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markdown
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numpy==1.24.*
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optimum==1.16.*
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|
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Block a user