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# =================== Lord Of Large Language Models Configuration file ===========================
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version : 30
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binding_name : null
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model_name : null
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# Host information
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host : localhost
port : 9600
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# Genreration parameters
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discussion_prompt_separator : "!@>"
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seed : -1
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n_predict : 1024
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ctx_size : 4084
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min_n_predict : 512
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temperature : 0.9
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top_k : 50
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top_p : 0.95
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repeat_last_n : 40
repeat_penalty : 1.2
n_threads : 8
#Personality parameters
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personalities : [ "generic/lollms" ]
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active_personality_id : 0
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override_personality_model_parameters : false #if true the personality parameters are overriden by those of the configuration (may affect personality behaviour)
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extensions : [ ]
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user_name : user
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user_description : ""
use_user_name_in_discussions : false
user_avatar : default_user.svg
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use_user_informations_in_discussion : false
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# UI parameters
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db_path : database.db
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# Automatic updates
debug : False
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auto_update : true
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auto_save : true
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auto_title : false
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# Enables gpu usage
enable_gpu : true
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# Automatically open the browser
auto_show_browser : true
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# Audio
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audio_in_language : 'en-US'
audio_out_voice : null
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auto_speak : false
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audio_pitch : 1
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audio_auto_send_input : true
audio_silenceTimer : 5000
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# Data vectorization
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use_discussions_history : false # Activate vectorizing previous conversations
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summerize_discussion : false # activate discussion summary (better but adds computation time)
max_summary_size : 512 # in tokens
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data_vectorization_visualize_on_vectorization : false
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use_files : true # Activate using files
data_vectorization_activate : true # To activate/deactivate data vectorization
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data_vectorization_method : "tfidf_vectorizer" #"model_embedding" or "tfidf_vectorizer"
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data_visualization_method : "PCA" #"PCA" or "TSNE"
data_vectorization_save_db : False # For each new session, new files
data_vectorization_chunk_size : 512 # chunk size
data_vectorization_overlap_size : 128 # overlap between chunks size
data_vectorization_nb_chunks : 2 # number of chunks to use
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data_vectorization_build_keys_words : false # If true, when querrying the database, we use keywords generated from the user prompt instead of the prompt itself.
