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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
class Controller:
def __init__(self):
self.agent_config = AgentConfig()
image = []
def handle_submission(user_message, selected_tools, url_endpoint, document, image, context):
log_response("User input \n {}".format(user_message))
log_response("selected_tools \n {}".format(selected_tools))
log_response("url_endpoint \n {}".format(url_endpoint))
log_response("document \n {}".format(document))
log_response("image \n {}".format(image))
log_response("context \n {}".format(context))
agent = CustomHfAgent(
url_endpoint=url_endpoint,
token=os.environ['HF_token'],
additional_tools=selected_tools,
input_params={"max_new_tokens": 192},
)
response = agent.chat(user_message,document=document,image=image, context = context)
log_response("Agent Response\n {}".format(response))
return response
def cut_text_after_keyword(text, keyword):
index = text.find(keyword)
if index != -1:
return text[:index].strip()
return text
def handle_submission_chat(user_message, response):
# os.environ['HUGGINGFACEHUB_API_TOKEN'] = os.environ['HF_token']
agent_chat_bot = ConversationChainSingleton().get_conversation_chain()
if response is not None:
text = agent_chat_bot.predict(input=user_message + response)
else:
text = agent_chat_bot.predict(input=user_message)
result = cut_text_after_keyword(text, "Human:")
print(result)
return result |