import streamlit as st import os import json import pandas as pd from docx import Document from dotenv import load_dotenv from openai import AzureOpenAI # Load environment variables load_dotenv() # Azure OpenAI credentials key = os.getenv("AZURE_OPENAI_API_KEY") endpoint_url = "https://interview-key.openai.azure.com/" api_version = "2024-05-01-preview" deployment_id = "interview" # Initialize Azure OpenAI client client = AzureOpenAI( api_version=api_version, azure_endpoint=endpoint_url, api_key=key ) # Streamlit app layout st.set_page_config(layout="wide") # Add custom CSS for center alignment st.markdown(""" """, unsafe_allow_html=True) 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." ) try: response = client.chat.completions.create( model=deployment_id, messages=[ {"role": "system", "content": "You are an AI specialized in extracting structured data from text documents."}, {"role": "user", "content": prompt}, ], max_tokens=1250, n=1, stop=None, temperature=0.1, ) return response.choices[0].message.content except Exception as e: st.error(f"Error extracting terms from contract: {e}") return None def analyze_task_compliance(task_description, cost_estimate, contract_terms): print("Task D: ", task_description, cost_estimate) 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 each task description and specify if it violates any conditions from the contract. " "If there are violations, list the reasons for each violation. Provide detailed answers and do not give only true or false answers.\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." ) try: response = client.chat.completions.create( model=deployment_id, messages=[ {"role": "system", "content": "You are an AI specialized in analyzing text for compliance with specified conditions."}, {"role": "user", "content": prompt}, ], max_tokens=1250, n=1, stop=None, temperature=0.1, ) return json.loads(response.choices[0].message.content) except Exception as e: st.error(f"Error analyzing task compliance: {e}") return None def main(): st.markdown("

Contract Compliance Analyzer

", unsafe_allow_html=True) # Initialize session state if 'contract_terms' not in st.session_state: st.session_state.contract_terms = None if 'compliance_results' not in st.session_state: st.session_state.compliance_results = None # File upload buttons one after another docx_file = st.sidebar.file_uploader("Upload Contract Document (DOCX)", type="docx", key="docx_file") data_file = st.sidebar.file_uploader("Upload Task Descriptions (XLSX or CSV)", type=["xlsx", "csv"], key="data_file") submit_button = st.sidebar.button("Submit") if submit_button and docx_file and data_file: # Extract contract text and terms contract_text = extract_text_from_docx(docx_file) extracted_terms_json = extract_terms_from_contract(contract_text) if extracted_terms_json is None: return try: st.session_state.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 or CSV if data_file.type == "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet": tasks_df = pd.read_excel(data_file) else: tasks_df = pd.read_csv(data_file) compliance_results = [] # Process tasks sequentially for _, row in tasks_df.iterrows(): result = analyze_task_compliance(row['Task Description'], row['Amount'], st.session_state.contract_terms) if result is not None: print(result) compliance_results.append(result) st.session_state.compliance_results = compliance_results col1, col2 = st.columns(2) with col1: if st.session_state.contract_terms: st.write("Extracted Contract Terms:") st.json(st.session_state.contract_terms) # Download button for contract terms st.download_button( label="Download Contract Terms", data=json.dumps(st.session_state.contract_terms, indent=4), file_name="contract_terms.json", mime="application/json" ) with col2: if st.session_state.compliance_results: st.write("Compliance Results:") st.json(st.session_state.compliance_results) # Download button for compliance results st.download_button( label="Download Compliance Results", data=json.dumps(st.session_state.compliance_results, indent=4), file_name="compliance_results.json", mime="application/json" ) if __name__ == "__main__": main()