Upload Legal ChatBot.py

Legal ChatBot.py

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+import os
+import streamlit as st
+from langchain_openai import OpenAIEmbeddings
+from langchain_openai.chat_models import ChatOpenAI
+from langchain_community.vectorstores import Chroma
+from langchain.chains import RetrievalQA
+from langchain.prompts import PromptTemplate
+from langchain.memory import ConversationBufferMemory
+from langchain.agents import initialize_agent, Tool, AgentExecutor
+from langchain.text_splitter import CharacterTextSplitter
+import openai
+
+# Set OpenAI API Key
+openai_api_key = os.environ.get("OPENAI_API_KEY")
+openai.api_key = openai_api_key
+
+# Document file paths
+file1 = "./data/DIVISION OF ASSETS AFTER DIVORCE.txt"
+file2 = "./data/INHERITANCE.txt"
+
+def openai_setting():
+    embedding = OpenAIEmbeddings()
+    model_name = "gpt-3.5-turbo"
+    llm = ChatOpenAI(model_name=model_name, temperature=0)
+    return embedding, llm
+
+def law_content_splitter(path, splitter="CIVIL CODE"):
+    with open(path) as f:
+        law_content = f.read()
+    law_content_by_article = law_content.split(splitter)[1:]
+    text_splitter = CharacterTextSplitter()
+    return text_splitter.create_documents(law_content_by_article)
+
+def is_greeting(input_str):
+    greetings = [
+        "hello", "hi", "hey", "greetings", "good morning", "good afternoon", 
+        "good evening", "hi there", "hello there", "hey there", 
+        "whats up", "ciao", "salve", "buongiorno", 
+        "buona sera", "buonasera", "buon pomeriggio", "buonpomeriggio", 
+        "come stai", "comestai", "come va", "comeva", "come sta", "comesta"
+    ]
+    return any(greet in input_str.lower() for greet in greetings)
+
+def chatbot1(question):
+    try:
+        return agent.run(question)
+    except:
+        return "I'm sorry, I'm having trouble understanding your question."
+
+def chatbot(input_str):
+    if is_greeting(input_str):
+        return "Hello! Ask me your question about Italian Divorce or Inheritance Law?"
+    else:
+        return chatbot1(input_str)
+
+
+### If you wanna disable Greeting in the chatbot, use this code:
+# def chatbot(input_str):
+#     # Directly process every input as a question
+#     response = chatbot1(input_str)
+#     if response == "N/A":
+#         return "I'm sorry, I'm having trouble understanding your question. Could you please rephrase it or provide more context"
+#     else:
+#         return response
+
+
+
+# Splitting the content of law documents
+divorce_splitted = law_content_splitter(file1)
+inheritance_splitted = law_content_splitter(file2)
+
+# Initializing embedding and language model
+embedding, llm = openai_setting()
+
+# Define the prompts
+divorce_prompt = """As a specialized bot in divorce law, you should offer accurate insights on Italian divorce regulations.
+You should always cite the article numbers you reference. 
+Ensure you provide detailed and exact data. 
+If a query doesn't pertain to the legal documents, you should remind the user that it falls outside your expertise.
+You should be adept at discussing the various Italian divorce categories, including fault-based divorce, mutual-consent divorce, and divorce due to infidelity.
+You should guide users through the prerequisites and procedures of each divorce type, detailing the essential paperwork, expected duration, and potential legal repercussions. 
+You should capably address queries regarding asset allocation, child custody, spousal support, and other financial concerns related to divorce, all while staying true to Italian legislation.
+{context}
+
+Question: {question}"""
+DIVORCE_BOT_PROMPT = PromptTemplate(template=divorce_prompt, input_variables=["context", "question"])
+
+# define inheritance prompt
+inheritance_prompt = """As a specialist in Italian inheritance law, you should deliver detailed and accurate insights about inheritance regulations in Italy.
+You should always cite the article numbers you reference. 
+When responding to user queries, you should always base your answers on the provided context.
+Always cite the specific article numbers you mention and refrain from speculating.
+Maintain precision in all your responses.
+If a user's question doesn't align with the legal documents, you should point out that it's beyond your domain of expertise.
+You should elucidate Italian inheritance law comprehensively, touching on topics such as testamentary inheritance, intestate inheritance, and other pertinent subjects.
+Make sure to elaborate on the obligations and rights of inheritors, the methodology of estate distribution, asset assessment, and settling debts, all while adhering to Italian law specifics.
+You should adeptly tackle questions about various will forms like holographic or notarial wills, ensuring you clarify their legitimacy within Italian jurisdiction. 
+Offer advice on creating a will, naming heirs, and managing potential conflicts.
+You should provide detailed information on tax nuances associated with inheritance in Italy, inclusive of exemptions, tax rates, and mandatory disclosures.
+
+{context}
+
+Question: {question}"""
+INHERITANCE_BOT_PROMPT = PromptTemplate(template=inheritance_prompt, input_variables=["context", "question"])
+
+# Setup for Chroma databases and RetrievalQA
+chroma_directory = "./docs/chroma"
+
+inheritance_db = Chroma.from_documents(
+    documents=inheritance_splitted,
+    embedding=embedding,
+    persist_directory=chroma_directory,
+)
+inheritance = RetrievalQA.from_chain_type(
+    llm=llm,
+    chain_type="stuff",
+    retriever=inheritance_db.as_retriever(),
+    chain_type_kwargs={"prompt": INHERITANCE_BOT_PROMPT},
+)
+
+divorce_db = Chroma.from_documents(
+    documents=divorce_splitted, embedding=embedding, persist_directory=chroma_directory
+)
+divorce = RetrievalQA.from_chain_type(
+    llm=llm,
+    chain_type="stuff",
+    retriever=divorce_db.as_retriever(),
+    chain_type_kwargs={"prompt": DIVORCE_BOT_PROMPT},
+)
+
+# Define the tools for the chatbot
+tools = [
+    Tool(
+        name="Divorce Italian law QA System",
+        func=divorce.run,
+        description="useful for when you need to answer questions about divorce laws in Italy.Give also the number of article you use for it.",
+    ),
+    Tool(
+        name="Inheritance Italian law QA System",
+        func=inheritance.run,
+        description="useful for when you need to answer questions about inheritance laws in Italy.Give also the number of article you use for it.",
+    ),
+]
+
+# Initialize conversation memory and ReAct agent
+memory = ConversationBufferMemory(memory_key="chat_history", input_key="input", output_key="output")
+react = initialize_agent(tools, llm, agent="zero-shot-react-description")
+agent = AgentExecutor.from_agent_and_tools(tools=tools, agent=react.agent, memory=memory, verbose=False)
+
+# Streamlit UI Setup
+def setup_ui():
+    st.set_page_config(page_title="Italian Law Chatbot", page_icon="⚖️")
+    st.title("Italian Law Chatbot 🏛️")
+    st.info(
+        "Check out the full tutorial to build this app in our [📝 blog post](https://sattari.org/projects/) — "
+        "[GitHub Repository](https://sattari.org)",
+        icon="ℹ️",
+    )
+    st.success(
+        "Check out [Prompt Examples List](https://sattari.org/projects/) to learn how to interact with this ChatBot 🤗 ",
+        icon="✅",
+    )
+    if "messages" not in st.session_state:
+        st.session_state.messages = [
+            {
+                "role": "assistant",
+                "content": "Hello! I'm here to help you with Italian Divorce or Inheritance Law.",
+            }
+        ]
+
+    # Display previous messages and handle new user input
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+    if user_input := st.chat_input("Ask a question about Italian Divorce or Inheritance Law:"):
+        st.session_state.messages.append({"role": "user", "content": user_input})
+        with st.chat_message("user"):
+            st.markdown(user_input)
+
+        # Generate and display chatbot response
+        with st.chat_message("assistant"):
+            response_placeholder = st.empty()
+            response = chatbot(user_input)  # Your existing chatbot function
+            response_placeholder.markdown(response)
+
+        # Append the response to the conversation history
+        st.session_state.messages.append({"role": "assistant", "content": response})
+
+if __name__ == "__main__":
+    setup_ui()