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Update app.py
Browse files
app.py
CHANGED
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@@ -10,6 +10,16 @@ from langchain.tools.base import StructuredTool
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from langchain.agents import initialize_agent
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from qa_txt import llm
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import gradio as gr
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def faq(query: str) -> str:
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reponse = conversation_chain({"question": query, "chat_history": []})
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@@ -29,7 +39,7 @@ qa_faq = StructuredTool.from_function(
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)
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def request_data(query: str) -> str:
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request = chain.
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mot_cle = nettoyer_string(request)
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mots = mot_cle.split()
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ui = mots[0]
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@@ -58,17 +68,18 @@ tools_add = [
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fetch_data,
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]
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agent =
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agent
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)
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def data_gov_ma(message, history):
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try:
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response =
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return response
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except ValueError as e:
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return "Je suis désolé, je n'ai pas compris votre question. Pourriez-vous la reformuler s'il vous plaît ?"
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from langchain.agents import initialize_agent
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from qa_txt import llm
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import gradio as gr
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from langchain.agents import (
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create_react_agent,
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AgentExecutor,
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tool,
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)
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from langchain import hub
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prompt = hub.pull("hwchase17/react")
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def faq(query: str) -> str:
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reponse = conversation_chain({"question": query, "chat_history": []})
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)
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def request_data(query: str) -> str:
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request = chain.invoke({"input": query})['text']
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mot_cle = nettoyer_string(request)
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mots = mot_cle.split()
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ui = mots[0]
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fetch_data,
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]
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agent = create_react_agent(llm=llm, tools=tools_add, prompt=prompt)
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agent_executor = AgentExecutor(
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agent=agent,
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tools=tools_add,
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verbose=True,
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)
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def data_gov_ma(message, history):
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try:
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response = agent_executor.invoke({"input": message})
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return response['output']
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except ValueError as e:
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return "Je suis désolé, je n'ai pas compris votre question. Pourriez-vous la reformuler s'il vous plaît ?"
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