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thanks github copilot for the comments i was too lazy to add

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expect 2025-06-22 19:07:41 +02:00
parent ec6751ee2e
commit a96616e4a2
6 changed files with 171 additions and 81 deletions
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11
modules/markovmemory.py
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@ -4,6 +4,8 @@ import markovify
import pickle
from modules.globalvars import *
from modules.translations import *
# Get file size and line count for a given file path
def get_file_info(file_path):
try:
file_size = os.path.getsize(file_path)
@ -13,16 +15,18 @@ def get_file_info(file_path):
except Exception as e:
return {"error": str(e)}
# Load memory data from file, or use default dataset if not loaded yet
def load_memory():
data = []
# load data from MEMORY_FILE
# Try to load data from MEMORY_FILE
try:
with open(MEMORY_FILE, "r") as f:
data = json.load(f)
except FileNotFoundError:
pass
# If MEMORY_LOADED_FILE does not exist, load default data and mark as loaded
if not os.path.exists(MEMORY_LOADED_FILE):
try:
with open(DEFAULT_DATASET_FILE, "r") as f:
@ -34,10 +38,12 @@ def load_memory():
f.write("Data loaded")
return data
# Save memory data to MEMORY_FILE
def save_memory(memory):
with open(MEMORY_FILE, "w") as f:
json.dump(memory, f, indent=4)
# Train a Markov model using memory and optional additional data
def train_markov_model(memory, additional_data=None):
if not memory:
return None
@ -47,13 +53,14 @@ def train_markov_model(memory, additional_data=None):
model = markovify.NewlineText(text, state_size=2)
return model
# Save the Markov model to a pickle file
def save_markov_model(model, filename='markov_model.pkl'):
with open(filename, 'wb') as f:
pickle.dump(model, f)
print(f"Markov model saved to {filename}.")
# Load the Markov model from a pickle file
def load_markov_model(filename='markov_model.pkl'):
try:
with open(filename, 'rb') as f:
model = pickle.load(f)