contract verification

app.py

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+import streamlit as st
+import os
+import openai
+import json
+import pandas as pd
+from docx import Document
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from dotenv import load_dotenv
+
+# Load the OpenAI API key from environment variables
+load_dotenv()
+api_key = os.getenv("OPENAI_API_KEY")
+openai.api_key = api_key
+
+def extract_text_from_docx(docx_path):
+    doc = Document(docx_path)
+    return "\n".join([para.text for para in doc.paragraphs])
+
+def extract_terms_from_contract(contract_text):
+    prompt = (
+        "You are an AI tasked with analyzing a contract and extracting key terms and constraints. The contract contains "
+        "various sections and subsections with terms related to budget constraints, types of allowable work, timelines, "
+        "penalties, responsibilities, and other conditions for work execution. Your job is to extract these key terms and "
+        "structure them in a clear JSON format, reflecting the hierarchy of sections and subsections. "
+        "Ensure to capture all important constraints and conditions specified in the contract text. If a section or subsection "
+        "contains multiple terms, list them all.\n\n"
+        "Contract text:\n"
+        f"{contract_text}\n\n"
+        "Provide the extracted terms in JSON format."
+    )
+
+    response = openai.ChatCompletion.create(
+        model="gpt-4",
+        messages=[
+            {"role": "system", "content": "You are an AI specialized in extracting structured data from text documents."},
+            {"role": "user", "content": prompt},
+        ],
+        max_tokens=4096,
+        n=1,
+        stop=None,
+        temperature=0.1,
+    )
+    return response.choices[0].message["content"]
+
+def analyze_task_compliance(task_description, cost_estimate, contract_terms):
+    prompt = (
+        "You are an AI tasked with analyzing a task description and its associated cost estimate for compliance with contract conditions. "
+        "Below are the key terms and constraints extracted from the contract, followed by a task description and its cost estimate. "
+        "Your job is to analyze the task description and specify if it violates any conditions from the contract. "
+        "If there are violations, list the reasons for each violation.\n\n"
+        f"Contract terms:\n{json.dumps(contract_terms, indent=4)}\n\n"
+        f"Task description:\n{task_description}\n"
+        f"Cost estimate:\n{cost_estimate}\n\n"
+        "Provide the compliance analysis in a clear JSON format."
+    )
+
+    response = openai.ChatCompletion.create(
+        model="gpt-4",
+        messages=[
+            {"role": "system", "content": "You are an AI specialized in analyzing text for compliance with specified conditions."},
+            {"role": "user", "content": prompt},
+        ],
+        max_tokens=4096,
+        n=1,
+        stop=None,
+        temperature=0.1,
+    )
+    
+    # Parse the response to extract structured explanations
+    response_content = response.choices[0].message["content"]
+    compliance_analysis = json.loads(response_content)
+    
+    return compliance_analysis
+
+def main():
+    st.title("Contract Compliance Analyzer")
+
+    # File upload buttons in the same row
+    col1, col2 = st.columns(2)
+    
+    with col1:
+        docx_file = st.file_uploader("Upload Contract Document (DOCX)", type="docx")
+    
+    with col2:
+        xlsx_file = st.file_uploader("Upload Task Descriptions (XLSX)", type="xlsx")
+
+    if docx_file and xlsx_file:
+        # Extract contract text and terms
+        contract_text = extract_text_from_docx(docx_file)
+        extracted_terms_json = extract_terms_from_contract(contract_text)
+        
+        try:
+            contract_terms = json.loads(extracted_terms_json)
+        except json.JSONDecodeError as e:
+            st.error(f"JSON decoding error: {e}")
+            return
+
+        # Read task descriptions and cost estimates from XLSX
+        tasks_df = pd.read_excel(xlsx_file)
+
+        compliance_results = []
+        futures = []
+
+        # Use ThreadPoolExecutor to analyze tasks concurrently
+        with ThreadPoolExecutor(max_workers=10) as executor:  # Adjust max_workers as needed
+            for _, row in tasks_df.iterrows():
+                task_description = row['Task Description']
+                cost_estimate = row['Amount']
+                futures.append(executor.submit(analyze_task_compliance, task_description, cost_estimate, contract_terms))
+            
+            for future in as_completed(futures):
+                try:
+                    result = future.result()
+                    compliance_results.append(result)
+                except Exception as e:
+                    st.error(f"An error occurred: {e}")
+
+        col1, col2 = st.columns(2)
+
+        with col1:
+            st.write("Extracted Contract Terms:")
+            st.json(contract_terms)
+            
+            # Download button for contract terms
+            st.download_button(
+                label="Download Contract Terms",
+                data=json.dumps(contract_terms, indent=4),
+                file_name="contract_terms.json",
+                mime="application/json"
+            )
+
+        with col2:
+            st.write("Compliance Results:")
+            st.json(compliance_results)
+
+            # Download button for compliance results
+            compliance_results_json = json.dumps(compliance_results, indent=4)
+            st.download_button(
+                label="Download Compliance Results",
+                data=compliance_results_json,
+                file_name="compliance_results.json",
+                mime="application/json"
+            )
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+openai==0.28
+python-dotenv
+flask
+python-docx
+pandas
+streamlit