Create app.py

app.py

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+import streamlit as st
+from llama_index.core import Settings
+from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, StorageContext
+from llama_index.embeddings.gemini import GeminiEmbedding
+from llama_index.llms.gemini import Gemini
+from llama_index.core import Document
+import google.generativeai as genai
+#import streamlit_analytics2 as streamlit_analytics
+
+# Set up Google API key
+import os
+
+# Configure Google Gemini
+
+# Load and index the legal document data
+def load_data(uploaded_files):
+    documents = [Document(text=t) for t in uploaded_files]
+    #documents = SimpleDirectoryReader(input_files=[uploaded_files]).load_data()
+    Settings.embed_model = GeminiEmbedding(api_key=os.getenv("GOOGLE_API_KEY"), model_name="models/embedding-001")
+    Settings.llm = Gemini(api_key=os.getenv("GOOGLE_API_KEY"), temperature=0.8, model_name="models/gemini-pro")
+    llm = Gemini(api_key=os.getenv("GOOGLE_API_KEY"), temperature=0.8, model_name="models/gemini-pro")
+    index = VectorStoreIndex.from_documents(documents)
+    return index
+
+# Generate legal document summary
+def generate_summary(index, document_text):
+    query_engine = index.as_query_engine()
+    response = query_engine.query(f"""
+    You are a skilled legal analyst. Your task is to provide a comprehensive summary of the given legal document.
+    Analyze the following legal document and summarize it:
+    {document_text}
+    
+    Please cover the following aspects:
+    1. Document type and purpose
+    2. Key parties involved
+    3. Main clauses and provisions
+    4. Important dates and deadlines
+    5. Potential legal implications
+    6. Any notable or unusual elements
+    
+    Provide a clear, concise, and professional summary that would be useful for legal professionals or clients.
+    """)
+    return response.response
+
+# Streamlit app
+def main():
+    st.title("Legal Document Summarizer")
+    st.write("Upload a legal document, and let our AI summarize it!")
+
+    # File uploader
+    uploaded_file = st.file_uploader("Choose a legal document file", type=["txt", "pdf"])
+
+    if uploaded_file is not None:
+        # Read file contents
+        if uploaded_file.type == "application/pdf":
+            # You'll need to install PyPDF2 for this
+            import PyPDF2
+            pdf_reader = PyPDF2.PdfReader(uploaded_file)
+            document_text = ""
+            l = []
+            for page in pdf_reader.pages:
+                document_text += page.extract_text()
+                l.append(page.extract_text())
+        else:
+            document_text = uploaded_file.getvalue().decode("utf-8")
+
+        st.write("Analyzing legal document...")
+
+        # Load data and generate summary
+        index = load_data(l)
+        summary = generate_summary(index, document_text)
+
+        st.write("## Legal Document Summary")
+        st.write(summary)
+
+if __name__ == "__main__":
+    main()