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") print(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()