File size: 2,003 Bytes
c7e94cf b8b0b89 7330cbd 003c5fb b2b25fd b8b0b89 b2b25fd b8b0b89 7330cbd b8b0b89 7330cbd b8b0b89 7330cbd b8b0b89 7330cbd b8b0b89 003c5fb 7330cbd 3e43065 7330cbd 3e43065 7330cbd 3e43065 7330cbd b8b0b89 55a5dbd 7330cbd b8b0b89 55a5dbd b8b0b89 6827c6b b8b0b89 |
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 |
import os
from app_agent_config import AgentConfig
from utils.logger import log_response
from model.custom_agent import CustomHfAgent
from model.conversation_chain_singleton import ConversationChainSingleton
def cut_text_after_keyword(text, keyword):
index = text.find(keyword)
if index != -1:
return text[:index].strip()
return text
class Controller:
def __init__(self):
self.agent_config = AgentConfig()
image = []
def handle_submission(self, user_message ):
log_response("User input \n {}".format(user_message))
log_response("selected_tools \n {}".format(self.agent_config.selected_tools))
log_response("url_endpoint \n {}".format(self.agent_config.url_endpoint))
log_response("document \n {}".format(self.agent_config.document))
log_response("image \n {}".format(self.agent_config.image))
log_response("context \n {}".format(self.agent_config.context))
agent = CustomHfAgent(
url_endpoint=self.agent_config.url_endpoint,
token=os.environ['HF_token'],
additional_tools=self.agent_config.elected_tools,
input_params={"max_new_tokens": 192},
)
angent_respone = agent.chat(user_message,document=self.agent_config.document,image=self.agent_config.image, context = self.agent_config.context)
log_response("Agent Response\n {}".format(angent_respone))
return angent_respone
def handle_submission_chat(self, user_message, angent_respone):
# os.environ['HUGGINGFACEHUB_API_TOKEN'] = os.environ['HF_token']
agent_chat_bot = ConversationChainSingleton().get_conversation_chain()
if angent_respone is not None:
text = agent_chat_bot.predict(input=user_message + angent_respone)
else:
text = agent_chat_bot.predict(input=user_message)
result = cut_text_after_keyword(text, "Human:")
print(result)
return result |