Spaces:
Running
Running
File size: 5,287 Bytes
0157229 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 |
from backend import get_handler
import uuid
import os
import json
import time
from datetime import datetime
from app_utils import *
class State:
"""
Manages the state of a chatbot including its model configuration, chat history, and test data.
Attributes:
current_model (str): The currently active model identifier
current_temperature (float): The temperature setting for model inference
current_category (str): The current category of conversation
test_entry (dict): Contains test configuration and data
inference_data (dict): Stores inference results and messages
handler: The model handler instance
history (list): List of conversation messages
name (str): Identifier for this bot instance, defaults to "bot"
database: Database connection for storing chat history
example_settings (dict): Predefined example configurations (see app_utils.py)
"""
def __init__(self, init_model, init_temperature, database, example_settings, name="bot"):
self.current_model = init_model
self.current_temperature = init_temperature
self.current_category = None
self.test_entry = initialize_empty_test_entry()
self.inference_data = {"message": []}
self.handler = get_handler(self.current_model, self.current_temperature)
self.history = self.get_initial_state()
self.name = name
self.database = database
self.example_settings = example_settings
def initialize(self, category):
self.category = category
self.update_category_and_load_config(category)
def get_initial_state(self):
return list(INITIAL_CHAT_HISTORY)
def restart_chat(self, model, temperature):
self.test_entry["id"] = str(uuid.uuid4())
self.handler = get_handler(model, temperature)
self.history = self.get_initial_state()
return self.history
def update_handler(self, model, temperature):
self.current_model = model
self.current_temperature = temperature
self.handler = get_handler(model, temperature)
print(f"Update handler for {self.name}: ", model, temperature)
self.history = self.restart_chat(model, temperature)
return model, self.history
def save(self):
if len(self.history) > 2:
document = {"time": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
"model": self.current_model,
"category": self.current_category,
"temperature": self.current_temperature,
"history": self.history}
self.database.insert_one(document)
def restart_chat_and_save(self):
self.save()
return self.restart_chat(self.current_model, self.current_temperature)
def update_category_and_load_config(self, category):
self.current_category = category
self.test_entry["initial_config"] = {category: {}}
self.test_entry["involved_classes"] = [category]
config_path = os.path.join("config", f"{MAPPINGS[category]}.json")
self.load_config(config_path)
return category
def load_config(self, config_path):
if os.path.exists(config_path):
with open(config_path, 'r') as config_file:
data = json.load(config_file)
self.test_entry["function"] = data.copy()
def load_example_and_update(self, example):
self.save()
model, temp, category, message = self.load_example(example)
self.update_category_and_load_config(category)
return model, temp, category, message
def load_example(self, example):
return self.example_settings[example]
def response(self):
for item in self.handler.inference(self.test_entry):
if item[0] == "regular":
responses_results = equalize_and_zip(item[1], item[2])
for (model_res, exec_res) in responses_results:
if model_res is not None:
response = model_res
self.history.append({"role": "assistant", "content": "<b>Model Response🤖: </b><br>"})
for character in response:
self.history[-1]["content"] += character
time.sleep(0.01)
yield self.history
if exec_res is not None:
response = exec_res
self.history[-1]["content"] += "<br><br><b>Model Execution💻: </b><br>"
yield self.history
for character in response:
self.history[-1]["content"] += character
time.sleep(0.01)
yield self.history
elif item[0] == 'summary':
response = item[1]
if response is not None:
self.history.append({"role": "assistant", "content": "<b>Summary✅: </b><br>"})
for character in response:
self.history[-1]["content"] += character
time.sleep(0.01)
yield self.history
elif item[0] == "final":
self.inference_data = item[2]
time.sleep(0.05) |