fix
Browse files- controller.py +5 -10
- model/conversation_chain_singleton.py +1 -2
- model/custom_agent_config.py +2 -2
controller.py
CHANGED
@@ -1,7 +1,7 @@
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import os
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from app_agent_config import AgentConfig
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from utils.logger import log_response
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from model.custom_agent import CustomHfAgent
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from model.conversation_chain_singleton import ConversationChainSingleton
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def cut_text_after_keyword(text, keyword):
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@@ -17,19 +17,17 @@ class Controller:
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#self.app_config = AppConfig()
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image = []
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-
def handle_submission(self, user_message ):
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-
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log_response("User input \n {}".format(user_message))
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log_response("selected_tools \n {}".format(self.agent_config.tool_checkboxes))
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log_response("url_endpoint \n {}".format(self.agent_config.url_endpoint))
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log_response("document \n {}".format(self.agent_config.document))
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log_response("image \n {}".format(self.agent_config.image))
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-
log_response("context \n {}".format(self.agent_config.context))
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-
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agent = CustomHfAgent(
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url_endpoint=self.agent_config.url_endpoint,
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token=os.environ['HF_token'],
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-
additional_tools=self.agent_config.
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input_params={"max_new_tokens": 192},
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)
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@@ -41,15 +39,12 @@ class Controller:
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def handle_submission_chat(self, user_message, angent_respone):
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# os.environ['HUGGINGFACEHUB_API_TOKEN'] = os.environ['HF_token']
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-
agent_chat_bot = ConversationChainSingleton().get_conversation_chain()
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-
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if angent_respone is not None:
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text = agent_chat_bot.predict(input=user_message + angent_respone)
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else:
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text = agent_chat_bot.predict(input=user_message)
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result = cut_text_after_keyword(text, "Human:")
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-
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print(result)
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-
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return result
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import os
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from app_agent_config import AgentConfig
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from utils.logger import log_response
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+
from model.custom_agent import CustomHfAgent
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from model.conversation_chain_singleton import ConversationChainSingleton
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def cut_text_after_keyword(text, keyword):
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#self.app_config = AppConfig()
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image = []
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+
def handle_submission(self, user_message ):
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log_response("User input \n {}".format(user_message))
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log_response("selected_tools \n {}".format(self.agent_config.tool_checkboxes))
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log_response("url_endpoint \n {}".format(self.agent_config.url_endpoint))
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log_response("document \n {}".format(self.agent_config.document))
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log_response("image \n {}".format(self.agent_config.image))
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+
log_response("context \n {}".format(self.agent_config.context))
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agent = CustomHfAgent(
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url_endpoint=self.agent_config.url_endpoint,
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token=os.environ['HF_token'],
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+
additional_tools=self.agent_config.tool_checkboxes,
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input_params={"max_new_tokens": 192},
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)
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def handle_submission_chat(self, user_message, angent_respone):
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# os.environ['HUGGINGFACEHUB_API_TOKEN'] = os.environ['HF_token']
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+
agent_chat_bot = ConversationChainSingleton().get_conversation_chain()
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if angent_respone is not None:
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text = agent_chat_bot.predict(input=user_message + angent_respone)
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else:
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text = agent_chat_bot.predict(input=user_message)
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result = cut_text_after_keyword(text, "Human:")
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print(result)
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return result
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model/conversation_chain_singleton.py
CHANGED
@@ -1,6 +1,5 @@
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-
from langchain.vectorstores import FAISS
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from langchain.memory import ConversationBufferMemory
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-
from langchain.chains import
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from langchain.llms import HuggingFaceHub
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class ConversationChainSingleton:
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from langchain.memory import ConversationBufferMemory
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from langchain.chains import ConversationChain
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from langchain.llms import HuggingFaceHub
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class ConversationChainSingleton:
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model/custom_agent_config.py
CHANGED
@@ -1,4 +1,4 @@
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class CustomHfAgentConfig():
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-
def __init__():
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-
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class CustomHfAgentConfig():
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def __init__(self):
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print("")
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