Create app.py

app.py

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+import os
+import streamlit as st
+from dotenv import load_dotenv
+from langchain.schema import HumanMessage
+from langchain_groq import ChatGroq
+from langgraph.graph import StateGraph, START, END
+from pydantic import BaseModel
+from langsmith import traceable
+import traceback
+
+# ✅ Load API keys securely
+load_dotenv()
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+LANGSMITH_API_KEY = os.getenv("LANGSMITH_API_KEY")
+
+os.environ["GROQ_API_KEY"] = GROQ_API_KEY
+os.environ["LANGCHAIN_TRACING_V2"] = "true"
+os.environ["LANGCHAIN_API_KEY"] = LANGSMITH_API_KEY
+
+# ✅ Initialize LLM (Using Groq Llama3-8B)
+llm = ChatGroq(groq_api_key=GROQ_API_KEY, model_name="llama3-8b-8192")
+
+# ✅ Define the LegalState Model
+class LegalState(BaseModel):
+    original_text: str
+    tone: str
+    complexity: int = 1
+    rewritten_text: str = None
+    summary: str = None
+    key_clauses: str = None
+    risk_analysis: str = None
+    compliance_report: str = None
+    contract_suggestions: str = None
+    legal_arguments: str = None
+    formatted_text: str = None
+    comparison_result: str = None
+    final_report: str = None
+
+# ✅ Function to invoke LLM with error handling
+def generate_response(prompt):
+    try:
+        response = llm.invoke([HumanMessage(content=prompt)])
+        return response.content
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+# ✅ Define Worker Functions
+@traceable(name="Rewrite Legal Text")
+def rewrite_text(state: LegalState):
+    prompt = f"""Rewrite this legal text in '{state.tone}' tone with complexity level {state.complexity}:
+
+    {state.original_text}"""
+    return {"rewritten_text": generate_response(prompt)}
+
+@traceable(name="Summarize Legal Text")
+def summarize_text(state: LegalState):
+    return {"summary": generate_response(f"Summarize this legal text:\n\n{state.rewritten_text}")}
+
+@traceable(name="Extract Key Clauses")
+def extract_clauses(state: LegalState):
+    return {"key_clauses": generate_response(f"Extract key legal clauses:\n\n{state.rewritten_text}")}
+
+@traceable(name="Detect Risks in Document")
+def detect_risks(state: LegalState):
+    return {"risk_analysis": generate_response(f"Analyze for risks:\n\n{state.rewritten_text}")}
+
+@traceable(name="Check Compliance")
+def check_compliance(state: LegalState):
+    return {"compliance_report": generate_response(f"Check legal compliance:\n\n{state.rewritten_text}")}
+
+@traceable(name="Suggest Contract Improvements")
+def suggest_improvements(state: LegalState):
+    return {"contract_suggestions": generate_response(f"Suggest improvements:\n\n{state.rewritten_text}")}
+
+@traceable(name="Generate Legal Arguments")
+def generate_arguments(state: LegalState):
+    return {"legal_arguments": generate_response(f"Generate legal arguments:\n\n{state.rewritten_text}")}
+
+@traceable(name="Format Legal Document")
+def format_document(state: LegalState):
+    return {"formatted_text": generate_response(f"Format this legal document:\n\n{state.rewritten_text}")}
+
+@traceable(name="Compare Original vs Rewritten")
+def compare_texts(state: LegalState):
+    prompt = f"Compare original vs rewritten:\n\nOriginal: {state.original_text}\nRewritten: {state.rewritten_text}"
+    return {"comparison_result": generate_response(prompt)}
+
+# ✅ Build LangGraph Workflow
+builder = StateGraph(LegalState)
+builder.add_node("rewrite_text", rewrite_text)
+builder.add_node("summarize_text", summarize_text)
+builder.add_node("extract_clauses", extract_clauses)
+builder.add_node("detect_risks", detect_risks)
+builder.add_node("check_compliance", check_compliance)
+builder.add_node("suggest_improvements", suggest_improvements)
+builder.add_node("generate_arguments", generate_arguments)
+builder.add_node("format_document", format_document)
+builder.add_node("compare_texts", compare_texts)
+
+builder.add_edge(START, "rewrite_text")
+for node in ["summarize_text", "extract_clauses", "detect_risks", "check_compliance", "suggest_improvements", "generate_arguments", "format_document", "compare_texts"]:
+    builder.add_edge("rewrite_text", node)
+
+graph = builder.compile()
+
+# ✅ Streamlit UI
+def main():
+    st.title("📜 AI-Powered Legal Text Processor")
+    st.write("A smart legal document assistant powered by LLMs.")
+
+    original_text = st.text_area("Enter Legal Text:")
+    tone = st.radio("Select Tone:", ["Formal", "Empathetic", "Neutral", "Strength-Based"])
+    
+    if st.button("Process Text"):
+        input_data = {"original_text": original_text, "tone": tone, "complexity": 1}
+        result = graph.invoke(input_data)
+        
+        st.subheader("🔹 Rewritten Text")
+        st.markdown(f"**{result['rewritten_text']}**")
+
+        st.subheader("📌 Summary")
+        st.write(result['summary'])
+        
+        st.subheader("📜 Key Clauses")
+        st.write(result['key_clauses'])
+        
+        st.subheader("⚠️ Risk Analysis")
+        st.write(result['risk_analysis'])
+        
+        st.subheader("✅ Compliance Report")
+        st.write(result['compliance_report'])
+        
+        st.subheader("💡 Contract Suggestions")
+        st.write(result['contract_suggestions'])
+        
+        st.subheader("⚖️ Legal Arguments")
+        st.write(result['legal_arguments'])
+        
+        st.subheader("📝 Formatted Legal Document")
+        st.write(result['formatted_text'])
+        
+        st.subheader("🔍 Comparison Result")
+        st.write(result['comparison_result'])
+
+if __name__ == "__main__":
+    main()