rename, more stats
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a9b7a7a2c7
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@ -18,7 +18,7 @@ def prepare_json(json_data: dict):
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return {
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'inputs': json_data.get('prompt', ''),
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'parameters': {
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'max_new_tokens': opts.token_limit - token_count,
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'max_new_tokens': opts.context_size - token_count,
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'repetition_penalty': json_data.get('repetition_penalty', None),
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'seed': seed,
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'stop': json_data.get('stopping_strings', []),
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@ -4,7 +4,7 @@ running_model = 'none'
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concurrent_gens = 3
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mode = 'oobabooga'
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backend_url = None
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token_limit = 5555
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context_size = 5555
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database_path = './proxy-server.db'
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auth_required = False
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log_prompts = False
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@ -64,7 +64,7 @@ def generate():
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backend_response = safe_list_get(response_json_body.get('results', []), 0, {}).get('text')
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if not backend_response:
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if opts.mode == 'oobabooga':
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backend_response = format_sillytavern_err(f'Backend returned an empty string. This can happen when your parameters are incorrect. Make sure your context size is no greater than {opts.token_limit}.', 'error')
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backend_response = format_sillytavern_err(f'Backend returned an empty string. This can happen when your parameters are incorrect. Make sure your context size is no greater than {opts.context_size}.', 'error')
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response_json_body['results'][0]['text'] = backend_response
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else:
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raise Exception
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@ -17,21 +17,30 @@ from ...llm.info import get_running_model
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@cache.cached(timeout=60, query_string=True)
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@cache_control(60)
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def get_stats():
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model_list = get_running_model()
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model_list = get_running_model() # will return False when the fetch fails
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if isinstance(model_list, bool):
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# get_running_model() will return False when the fetch fails
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online = False
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else:
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online = True
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return jsonify({
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'proompters_now': opts.concurrent_gens - concurrent_semaphore._value,
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'proompters_1_min': proompters_1_min,
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'total_proompts': stats.proompts.value,
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'uptime': int((datetime.now() - stats.start_time).total_seconds()),
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'stats': {
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'proompters_now': opts.concurrent_gens - concurrent_semaphore._value,
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'proompters_1_min': proompters_1_min,
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'total_proompts': stats.proompts.value,
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'uptime': int((datetime.now() - stats.start_time).total_seconds()),
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},
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'online': online,
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'mode': opts.mode,
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'model': get_running_model(),
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'client': f'https://{request.headers.get("Host")}/{opts.frontend_api_client.strip("/")}',
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'timestamp': int(time.time())
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'endpoints': {
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'blocking': f'https://{request.headers.get("Host")}/{opts.frontend_api_client.strip("/")}',
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},
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'timestamp': int(time.time()),
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'openaiKeys': '∞',
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'anthropicKeys': '∞',
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'config': {
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'gatekeeper': 'none' if opts.auth_required is False else 'token',
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'context_size': opts.context_size,
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}
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}), 200
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@ -46,7 +46,7 @@ opts.auth_required = config['auth_required']
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opts.log_prompts = config['log_prompts']
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opts.concurrent_gens = config['concurrent_gens']
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opts.frontend_api_client = config['frontend_api_client']
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opts.token_limit = config['token_limit']
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opts.context_size = config['token_limit']
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app = Flask(__name__)
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cache.init_app(app)
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