mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-12-24 13:28:59 +01:00
Remove old API, launch OpenAI API with --api
This commit is contained in:
oobabooga
parent
6a7cd01ebf
commit
4aabff3728
@ -75,7 +75,7 @@
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" with open('temp_requirements.txt', 'w') as file:\n",
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" file.write('\\n'.join(textgen_requirements))\n",
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"\n",
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" !pip install -r extensions/api/requirements.txt --upgrade\n",
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" !pip install -r extensions/openai/requirements.txt --upgrade\n",
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" !pip install -r temp_requirements.txt --upgrade\n",
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"\n",
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" print(\"\\033[1;32;1m\\n --> If you see a warning about \\\"previously imported packages\\\", just ignore it.\\033[0;37;0m\")\n",
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@ -10,7 +10,7 @@ pip install -r extensions/openai/requirements.txt
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### Starting the API
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Add `--extensions openai` to your command-line flags.
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Add `--api` to your command-line flags.
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* To create a public Cloudflare URL, add the `--public-api` flag.
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* To listen on your local network, add the `--listen` flag.
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@ -18,31 +18,6 @@ Add `--extensions openai` to your command-line flags.
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* To use SSL, add `--ssl-keyfile key.pem --ssl-certfile cert.pem`. Note that it doesn't work with `--public-api`.
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* To use an API key for authentication, add `--api-key yourkey`.
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#### Environment variables
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The following environment variables can be used (they take precendence over everything else):
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| Variable Name | Description | Example Value |
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|------------------------|------------------------------------|----------------------------|
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| `OPENEDAI_PORT` | Port number | 5000 |
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| `OPENEDAI_CERT_PATH` | SSL certificate file path | cert.pem |
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| `OPENEDAI_KEY_PATH` | SSL key file path | key.pem |
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| `OPENEDAI_DEBUG` | Enable debugging (set to 1) | 1 |
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| `SD_WEBUI_URL` | WebUI URL (used by endpoint) | http://127.0.0.1:7861 |
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| `OPENEDAI_EMBEDDING_MODEL` | Embedding model (if applicable) | all-mpnet-base-v2 |
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| `OPENEDAI_EMBEDDING_DEVICE` | Embedding device (if applicable) | cuda |
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#### Persistent settings with `settings.yaml`
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You can also set the following variables in your `settings.yaml` file:
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```
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openai-embedding_device: cuda
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openai-embedding_model: all-mpnet-base-v2
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openai-sd_webui_url: http://127.0.0.1:7861
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openai-debug: 1
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```
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### Examples
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For the documentation with all the parameters and their types, consult `http://127.0.0.1:5000/docs` or the [typing.py](https://github.com/oobabooga/text-generation-webui/blob/main/extensions/openai/typing.py) file.
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@ -220,6 +195,31 @@ for event in client.events():
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print()
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```
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### Environment variables
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The following environment variables can be used (they take precendence over everything else):
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| Variable Name | Description | Example Value |
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|------------------------|------------------------------------|----------------------------|
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| `OPENEDAI_PORT` | Port number | 5000 |
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| `OPENEDAI_CERT_PATH` | SSL certificate file path | cert.pem |
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| `OPENEDAI_KEY_PATH` | SSL key file path | key.pem |
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| `OPENEDAI_DEBUG` | Enable debugging (set to 1) | 1 |
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| `SD_WEBUI_URL` | WebUI URL (used by endpoint) | http://127.0.0.1:7861 |
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| `OPENEDAI_EMBEDDING_MODEL` | Embedding model (if applicable) | all-mpnet-base-v2 |
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| `OPENEDAI_EMBEDDING_DEVICE` | Embedding device (if applicable) | cuda |
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#### Persistent settings with `settings.yaml`
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You can also set the following variables in your `settings.yaml` file:
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```
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openai-embedding_device: cuda
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openai-embedding_model: all-mpnet-base-v2
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openai-sd_webui_url: http://127.0.0.1:7861
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openai-debug: 1
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```
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### Third-party application setup
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You can usually force an application that uses the OpenAI API to connect to the local API by using the following environment variables:
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@ -1,232 +0,0 @@
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import json
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import ssl
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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from threading import Thread
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from extensions.api.util import build_parameters, try_start_cloudflared
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from modules import shared
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from modules.chat import generate_chat_reply
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from modules.LoRA import add_lora_to_model
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from modules.models import load_model, unload_model
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from modules.models_settings import get_model_metadata, update_model_parameters
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from modules.text_generation import (
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encode,
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generate_reply,
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stop_everything_event
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)
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from modules.utils import get_available_models
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from modules.logging_colors import logger
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def get_model_info():
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return {
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'model_name': shared.model_name,
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'lora_names': shared.lora_names,
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# dump
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'shared.settings': shared.settings,
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'shared.args': vars(shared.args),
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}
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class Handler(BaseHTTPRequestHandler):
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def do_GET(self):
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if self.path == '/api/v1/model':
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self.send_response(200)
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self.end_headers()
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response = json.dumps({
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'result': shared.model_name
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})
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self.wfile.write(response.encode('utf-8'))
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else:
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self.send_error(404)
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def do_POST(self):
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content_length = int(self.headers['Content-Length'])
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body = json.loads(self.rfile.read(content_length).decode('utf-8'))
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if self.path == '/api/v1/generate':
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self.send_response(200)
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self.send_header('Content-Type', 'application/json')
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self.end_headers()
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prompt = body['prompt']
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generate_params = build_parameters(body)
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stopping_strings = generate_params.pop('stopping_strings')
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generate_params['stream'] = False
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generator = generate_reply(
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prompt, generate_params, stopping_strings=stopping_strings, is_chat=False)
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answer = ''
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for a in generator:
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answer = a
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response = json.dumps({
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'results': [{
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'text': answer
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}]
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})
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self.wfile.write(response.encode('utf-8'))
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elif self.path == '/api/v1/chat':
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self.send_response(200)
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self.send_header('Content-Type', 'application/json')
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self.end_headers()
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user_input = body['user_input']
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regenerate = body.get('regenerate', False)
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_continue = body.get('_continue', False)
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generate_params = build_parameters(body, chat=True)
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generate_params['stream'] = False
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generator = generate_chat_reply(
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user_input, generate_params, regenerate=regenerate, _continue=_continue, loading_message=False)
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answer = generate_params['history']
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for a in generator:
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answer = a
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response = json.dumps({
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'results': [{
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'history': answer
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}]
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})
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self.wfile.write(response.encode('utf-8'))
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elif self.path == '/api/v1/stop-stream':
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self.send_response(200)
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self.send_header('Content-Type', 'application/json')
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self.end_headers()
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stop_everything_event()
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response = json.dumps({
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'results': 'success'
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})
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self.wfile.write(response.encode('utf-8'))
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elif self.path == '/api/v1/model':
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self.send_response(200)
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self.send_header('Content-Type', 'application/json')
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self.end_headers()
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# by default return the same as the GET interface
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result = shared.model_name
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# Actions: info, load, list, unload
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action = body.get('action', '')
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if action == 'load':
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model_name = body['model_name']
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args = body.get('args', {})
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print('args', args)
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for k in args:
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setattr(shared.args, k, args[k])
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shared.model_name = model_name
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unload_model()
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model_settings = get_model_metadata(shared.model_name)
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shared.settings.update({k: v for k, v in model_settings.items() if k in shared.settings})
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update_model_parameters(model_settings, initial=True)
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if shared.settings['mode'] != 'instruct':
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shared.settings['instruction_template'] = None
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try:
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shared.model, shared.tokenizer = load_model(shared.model_name)
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if shared.args.lora:
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add_lora_to_model(shared.args.lora) # list
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except Exception as e:
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response = json.dumps({'error': {'message': repr(e)}})
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self.wfile.write(response.encode('utf-8'))
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raise e
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shared.args.model = shared.model_name
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result = get_model_info()
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elif action == 'unload':
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unload_model()
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shared.model_name = None
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shared.args.model = None
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result = get_model_info()
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elif action == 'list':
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result = get_available_models()
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elif action == 'info':
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result = get_model_info()
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response = json.dumps({
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'result': result,
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})
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self.wfile.write(response.encode('utf-8'))
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elif self.path == '/api/v1/token-count':
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self.send_response(200)
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self.send_header('Content-Type', 'application/json')
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self.end_headers()
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tokens = encode(body['prompt'])[0]
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response = json.dumps({
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'results': [{
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'tokens': len(tokens)
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}]
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})
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self.wfile.write(response.encode('utf-8'))
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else:
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self.send_error(404)
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def do_OPTIONS(self):
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self.send_response(200)
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self.end_headers()
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def end_headers(self):
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self.send_header('Access-Control-Allow-Origin', '*')
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self.send_header('Access-Control-Allow-Methods', '*')
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self.send_header('Access-Control-Allow-Headers', '*')
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self.send_header('Cache-Control', 'no-store, no-cache, must-revalidate')
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super().end_headers()
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def _run_server(port: int, share: bool = False, tunnel_id=str):
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address = '0.0.0.0' if shared.args.listen else '127.0.0.1'
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server = ThreadingHTTPServer((address, port), Handler)
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ssl_certfile = shared.args.ssl_certfile
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ssl_keyfile = shared.args.ssl_keyfile
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ssl_verify = True if (ssl_keyfile and ssl_certfile) else False
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if ssl_verify:
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context = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER)
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context.load_cert_chain(ssl_certfile, ssl_keyfile)
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server.socket = context.wrap_socket(server.socket, server_side=True)
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def on_start(public_url: str):
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logger.info(f'Blocking API URL: \n\n{public_url}/api\n')
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if share:
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try:
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try_start_cloudflared(port, tunnel_id, max_attempts=3, on_start=on_start)
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except Exception:
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pass
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else:
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if ssl_verify:
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logger.info(f'Blocking API URL: \n\nhttps://{address}:{port}/api\n')
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else:
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logger.info(f'Blocking API URL: \n\nhttp://{address}:{port}/api\n')
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server.serve_forever()
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def start_server(port: int, share: bool = False, tunnel_id=str):
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Thread(target=_run_server, args=[port, share, tunnel_id], daemon=True).start()
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@ -1,2 +0,0 @@
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flask_cloudflared==0.0.14
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websockets==11.0.2
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@ -1,15 +0,0 @@
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import time
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import extensions.api.blocking_api as blocking_api
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import extensions.api.streaming_api as streaming_api
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from modules import shared
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from modules.logging_colors import logger
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def setup():
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logger.warning("\nThe current API is deprecated and will be replaced with the OpenAI compatible API on November 13th.\nTo test the new API, use \"--extensions openai\" instead of \"--api\".\nFor documentation on the new API, consult:\nhttps://github.com/oobabooga/text-generation-webui/wiki/12-%E2%80%90-OpenAI-API")
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blocking_api.start_server(shared.args.api_blocking_port, share=shared.args.public_api, tunnel_id=shared.args.public_api_id)
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if shared.args.public_api:
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time.sleep(5)
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streaming_api.start_server(shared.args.api_streaming_port, share=shared.args.public_api, tunnel_id=shared.args.public_api_id)
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@ -1,142 +0,0 @@
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import asyncio
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import json
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import ssl
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from threading import Thread
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from websockets.server import serve
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from extensions.api.util import (
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build_parameters,
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try_start_cloudflared,
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with_api_lock
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)
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from modules import shared
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from modules.chat import generate_chat_reply
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from modules.text_generation import generate_reply
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from modules.logging_colors import logger
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PATH = '/api/v1/stream'
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@with_api_lock
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async def _handle_stream_message(websocket, message):
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message = json.loads(message)
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prompt = message['prompt']
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generate_params = build_parameters(message)
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stopping_strings = generate_params.pop('stopping_strings')
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generate_params['stream'] = True
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generator = generate_reply(
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prompt, generate_params, stopping_strings=stopping_strings, is_chat=False)
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# As we stream, only send the new bytes.
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skip_index = 0
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message_num = 0
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for a in generator:
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to_send = a[skip_index:]
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if to_send is None or chr(0xfffd) in to_send: # partial unicode character, don't send it yet.
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continue
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await websocket.send(json.dumps({
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'event': 'text_stream',
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'message_num': message_num,
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'text': to_send
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}))
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await asyncio.sleep(0)
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skip_index += len(to_send)
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message_num += 1
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await websocket.send(json.dumps({
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'event': 'stream_end',
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'message_num': message_num
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}))
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@with_api_lock
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async def _handle_chat_stream_message(websocket, message):
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body = json.loads(message)
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user_input = body['user_input']
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generate_params = build_parameters(body, chat=True)
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generate_params['stream'] = True
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regenerate = body.get('regenerate', False)
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_continue = body.get('_continue', False)
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generator = generate_chat_reply(
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user_input, generate_params, regenerate=regenerate, _continue=_continue, loading_message=False)
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message_num = 0
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for a in generator:
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await websocket.send(json.dumps({
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'event': 'text_stream',
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'message_num': message_num,
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'history': a
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}))
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await asyncio.sleep(0)
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message_num += 1
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await websocket.send(json.dumps({
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'event': 'stream_end',
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'message_num': message_num
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}))
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async def _handle_connection(websocket, path):
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if path == '/api/v1/stream':
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async for message in websocket:
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await _handle_stream_message(websocket, message)
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elif path == '/api/v1/chat-stream':
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async for message in websocket:
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await _handle_chat_stream_message(websocket, message)
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else:
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print(f'Streaming api: unknown path: {path}')
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return
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async def _run(host: str, port: int):
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ssl_certfile = shared.args.ssl_certfile
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ssl_keyfile = shared.args.ssl_keyfile
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ssl_verify = True if (ssl_keyfile and ssl_certfile) else False
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if ssl_verify:
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context = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER)
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context.load_cert_chain(ssl_certfile, ssl_keyfile)
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else:
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context = None
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async with serve(_handle_connection, host, port, ping_interval=None, ssl=context):
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await asyncio.Future() # Run the server forever
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def _run_server(port: int, share: bool = False, tunnel_id=str):
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address = '0.0.0.0' if shared.args.listen else '127.0.0.1'
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ssl_certfile = shared.args.ssl_certfile
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ssl_keyfile = shared.args.ssl_keyfile
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ssl_verify = True if (ssl_keyfile and ssl_certfile) else False
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def on_start(public_url: str):
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public_url = public_url.replace('https://', 'wss://')
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logger.info(f'Streaming API URL: \n\n{public_url}{PATH}\n')
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if share:
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try:
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try_start_cloudflared(port, tunnel_id, max_attempts=3, on_start=on_start)
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except Exception as e:
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print(e)
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else:
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if ssl_verify:
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logger.info(f'Streaming API URL: \n\nwss://{address}:{port}{PATH}\n')
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else:
|
||||
logger.info(f'Streaming API URL: \n\nws://{address}:{port}{PATH}\n')
|
||||
|
||||
asyncio.run(_run(host=address, port=port))
|
||||
|
||||
|
||||
def start_server(port: int, share: bool = False, tunnel_id=str):
|
||||
Thread(target=_run_server, args=[port, share, tunnel_id], daemon=True).start()
|
||||
@ -1,156 +0,0 @@
|
||||
import asyncio
|
||||
import functools
|
||||
import threading
|
||||
import time
|
||||
import traceback
|
||||
from threading import Thread
|
||||
from typing import Callable, Optional
|
||||
|
||||
from modules import shared
|
||||
from modules.chat import load_character_memoized
|
||||
from modules.presets import load_preset_memoized
|
||||
|
||||
# We use a thread local to store the asyncio lock, so that each thread
|
||||
# has its own lock. This isn't strictly necessary, but it makes it
|
||||
# such that if we can support multiple worker threads in the future,
|
||||
# thus handling multiple requests in parallel.
|
||||
api_tls = threading.local()
|
||||
|
||||
|
||||
def build_parameters(body, chat=False):
|
||||
|
||||
generate_params = {
|
||||
'max_new_tokens': int(body.get('max_new_tokens', body.get('max_length', 200))),
|
||||
'auto_max_new_tokens': bool(body.get('auto_max_new_tokens', False)),
|
||||
'max_tokens_second': int(body.get('max_tokens_second', 0)),
|
||||
'do_sample': bool(body.get('do_sample', True)),
|
||||
'temperature': float(body.get('temperature', 0.5)),
|
||||
'temperature_last': bool(body.get('temperature_last', False)),
|
||||
'top_p': float(body.get('top_p', 1)),
|
||||
'min_p': float(body.get('min_p', 0)),
|
||||
'typical_p': float(body.get('typical_p', body.get('typical', 1))),
|
||||
'epsilon_cutoff': float(body.get('epsilon_cutoff', 0)),
|
||||
'eta_cutoff': float(body.get('eta_cutoff', 0)),
|
||||
'tfs': float(body.get('tfs', 1)),
|
||||
'top_a': float(body.get('top_a', 0)),
|
||||
'repetition_penalty': float(body.get('repetition_penalty', body.get('rep_pen', 1.1))),
|
||||
'presence_penalty': float(body.get('presence_penalty', body.get('presence_pen', 0))),
|
||||
'frequency_penalty': float(body.get('frequency_penalty', body.get('frequency_pen', 0))),
|
||||
'repetition_penalty_range': int(body.get('repetition_penalty_range', 0)),
|
||||
'encoder_repetition_penalty': float(body.get('encoder_repetition_penalty', 1.0)),
|
||||
'top_k': int(body.get('top_k', 0)),
|
||||
'min_length': int(body.get('min_length', 0)),
|
||||
'no_repeat_ngram_size': int(body.get('no_repeat_ngram_size', 0)),
|
||||
'num_beams': int(body.get('num_beams', 1)),
|
||||
'penalty_alpha': float(body.get('penalty_alpha', 0)),
|
||||
'length_penalty': float(body.get('length_penalty', 1)),
|
||||
'early_stopping': bool(body.get('early_stopping', False)),
|
||||
'mirostat_mode': int(body.get('mirostat_mode', 0)),
|
||||
'mirostat_tau': float(body.get('mirostat_tau', 5)),
|
||||
'mirostat_eta': float(body.get('mirostat_eta', 0.1)),
|
||||
'grammar_string': str(body.get('grammar_string', '')),
|
||||
'guidance_scale': float(body.get('guidance_scale', 1)),
|
||||
'negative_prompt': str(body.get('negative_prompt', '')),
|
||||
'seed': int(body.get('seed', -1)),
|
||||
'add_bos_token': bool(body.get('add_bos_token', True)),
|
||||
'truncation_length': int(body.get('truncation_length', body.get('max_context_length', 2048))),
|
||||
'custom_token_bans': str(body.get('custom_token_bans', '')),
|
||||
'ban_eos_token': bool(body.get('ban_eos_token', False)),
|
||||
'skip_special_tokens': bool(body.get('skip_special_tokens', True)),
|
||||
'custom_stopping_strings': '', # leave this blank
|
||||
'stopping_strings': body.get('stopping_strings', []),
|
||||
}
|
||||
|
||||
preset_name = body.get('preset', 'None')
|
||||
if preset_name not in ['None', None, '']:
|
||||
preset = load_preset_memoized(preset_name)
|
||||
generate_params.update(preset)
|
||||
|
||||
if chat:
|
||||
character = body.get('character')
|
||||
instruction_template = body.get('instruction_template', shared.settings['instruction_template'])
|
||||
if str(instruction_template) == "None":
|
||||
instruction_template = "Vicuna-v1.1"
|
||||
if str(character) == "None":
|
||||
character = "Assistant"
|
||||
|
||||
name1, name2, _, greeting, context, _, _ = load_character_memoized(character, str(body.get('your_name', shared.settings['name1'])), '', instruct=False)
|
||||
name1_instruct, name2_instruct, _, _, context_instruct, turn_template, _ = load_character_memoized(instruction_template, '', '', instruct=True)
|
||||
generate_params.update({
|
||||
'mode': str(body.get('mode', 'chat')),
|
||||
'name1': str(body.get('name1', name1)),
|
||||
'name2': str(body.get('name2', name2)),
|
||||
'context': str(body.get('context', context)),
|
||||
'greeting': str(body.get('greeting', greeting)),
|
||||
'name1_instruct': str(body.get('name1_instruct', name1_instruct)),
|
||||
'name2_instruct': str(body.get('name2_instruct', name2_instruct)),
|
||||
'context_instruct': str(body.get('context_instruct', context_instruct)),
|
||||
'turn_template': str(body.get('turn_template', turn_template)),
|
||||
'chat-instruct_command': str(body.get('chat_instruct_command', body.get('chat-instruct_command', shared.settings['chat-instruct_command']))),
|
||||
'history': body.get('history', {'internal': [], 'visible': []})
|
||||
})
|
||||
|
||||
return generate_params
|
||||
|
||||
|
||||
def try_start_cloudflared(port: int, tunnel_id: str, max_attempts: int = 3, on_start: Optional[Callable[[str], None]] = None):
|
||||
Thread(target=_start_cloudflared, args=[
|
||||
port, tunnel_id, max_attempts, on_start], daemon=True).start()
|
||||
|
||||
|
||||
def _start_cloudflared(port: int, tunnel_id: str, max_attempts: int = 3, on_start: Optional[Callable[[str], None]] = None):
|
||||
try:
|
||||
from flask_cloudflared import _run_cloudflared
|
||||
except ImportError:
|
||||
print('You should install flask_cloudflared manually')
|
||||
raise Exception(
|
||||
'flask_cloudflared not installed. Make sure you installed the requirements.txt for this extension.')
|
||||
|
||||
for _ in range(max_attempts):
|
||||
try:
|
||||
if tunnel_id is not None:
|
||||
public_url = _run_cloudflared(port, port + 1, tunnel_id=tunnel_id)
|
||||
else:
|
||||
public_url = _run_cloudflared(port, port + 1)
|
||||
|
||||
if on_start:
|
||||
on_start(public_url)
|
||||
|
||||
return
|
||||
except Exception:
|
||||
traceback.print_exc()
|
||||
time.sleep(3)
|
||||
|
||||
raise Exception('Could not start cloudflared.')
|
||||
|
||||
|
||||
def _get_api_lock(tls) -> asyncio.Lock:
|
||||
"""
|
||||
The streaming and blocking API implementations each run on their own
|
||||
thread, and multiplex requests using asyncio. If multiple outstanding
|
||||
requests are received at once, we will try to acquire the shared lock
|
||||
shared.generation_lock multiple times in succession in the same thread,
|
||||
which will cause a deadlock.
|
||||
|
||||
To avoid this, we use this wrapper function to block on an asyncio
|
||||
lock, and then try and grab the shared lock only while holding
|
||||
the asyncio lock.
|
||||
"""
|
||||
if not hasattr(tls, "asyncio_lock"):
|
||||
tls.asyncio_lock = asyncio.Lock()
|
||||
|
||||
return tls.asyncio_lock
|
||||
|
||||
|
||||
def with_api_lock(func):
|
||||
"""
|
||||
This decorator should be added to all streaming API methods which
|
||||
require access to the shared.generation_lock. It ensures that the
|
||||
tls.asyncio_lock is acquired before the method is called, and
|
||||
released afterwards.
|
||||
"""
|
||||
@functools.wraps(func)
|
||||
async def api_wrapper(*args, **kwargs):
|
||||
async with _get_api_lock(api_tls):
|
||||
return await func(*args, **kwargs)
|
||||
return api_wrapper
|
||||
@ -295,14 +295,14 @@ def run_server():
|
||||
|
||||
if shared.args.public_api:
|
||||
def on_start(public_url: str):
|
||||
logger.info(f'OpenAI compatible API URL:\n\n{public_url}/v1\n')
|
||||
logger.info(f'OpenAI compatible API URL:\n\n{public_url}\n')
|
||||
|
||||
_start_cloudflared(port, shared.args.public_api_id, max_attempts=3, on_start=on_start)
|
||||
else:
|
||||
if ssl_keyfile and ssl_certfile:
|
||||
logger.info(f'OpenAI compatible API URL:\n\nhttps://{server_addr}:{port}/v1\n')
|
||||
logger.info(f'OpenAI compatible API URL:\n\nhttps://{server_addr}:{port}\n')
|
||||
else:
|
||||
logger.info(f'OpenAI compatible API URL:\n\nhttp://{server_addr}:{port}/v1\n')
|
||||
logger.info(f'OpenAI compatible API URL:\n\nhttp://{server_addr}:{port}\n')
|
||||
|
||||
if shared.args.api_key:
|
||||
logger.info(f'OpenAI API key:\n\n{shared.args.api_key}\n')
|
||||
|
||||
@ -258,9 +258,8 @@ if args.multimodal_pipeline is not None:
|
||||
add_extension('multimodal')
|
||||
|
||||
# Activate the API extension
|
||||
if args.api:
|
||||
# add_extension('openai', last=True)
|
||||
add_extension('api', last=True)
|
||||
if args.api or args.public_api:
|
||||
add_extension('openai', last=True)
|
||||
|
||||
# Load model-specific settings
|
||||
with Path(f'{args.model_dir}/config.yaml') as p:
|
||||
|
||||
@ -9,6 +9,7 @@ os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False'
|
||||
os.environ['BITSANDBYTES_NOWELCOME'] = '1'
|
||||
warnings.filterwarnings('ignore', category=UserWarning, message='TypedStorage is deprecated')
|
||||
warnings.filterwarnings('ignore', category=UserWarning, message='Using the update method is deprecated')
|
||||
warnings.filterwarnings('ignore', category=UserWarning, message='Field "model_name" has conflict')
|
||||
|
||||
with RequestBlocker():
|
||||
import gradio as gr
|
||||
|
||||
Loading…
Reference in New Issue
Block a user