# 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
# import time

# # Load the OpenAI API key from environment variables
# load_dotenv()
# api_key = os.getenv("OPENAI_API_KEY")
# openai.api_key = api_key

# # Streamlit app layout
# st.set_page_config(layout="wide")

# # Add custom CSS for center alignment
# st.markdown("""
#     <style>
#     .centered-title {
#         text-align: center;
#         font-size: 2.5em;
#         margin-top: 0;
#     }
#     </style>
#     """, 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."
#     )

#     retries = 2
#     wait_time = 1
#     for i in range(retries):
#         try:
#             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"]
#         except openai.error.RateLimitError:
#             if i < retries - 1:
#                 st.warning(f"Rate limit exceeded. Retrying in {wait_time} seconds...")
#                 time.sleep(wait_time)
#                 wait_time *= 2  # Exponential backoff
#             else:
#                 st.error("Rate limit exceeded. Please try again later.")
#                 return None

# 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."
#     )

#     retries = 5
#     wait_time = 1
#     for i in range(retries):
#         try:
#             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,
#                 stream=True,
#             )

#             compliance_analysis = ""
#             for chunk in response:
#                 chunk_text = chunk['choices'][0]['delta'].get('content', '')
#                 compliance_analysis += chunk_text
#                 st.write(chunk_text)
#                 st.json(chunk_text)

#             return json.loads(compliance_analysis)
#         except openai.error.RateLimitError:
#             if i < retries - 1:
#                 st.warning(f"Rate limit exceeded. Retrying in {wait_time} seconds...")
#                 time.sleep(wait_time)
#                 wait_time *= 2  # Exponential backoff
#             else:
#                 st.error("Rate limit exceeded. Please try again later.")
#                 return None

# def main():
#     st.markdown("<h1 class='centered-title'>Contract Compliance Analyzer</h1>", unsafe_allow_html=True)

#     # File upload buttons one after another
#     st.sidebar.file_uploader("Upload Contract Document (DOCX)", type="docx", key="docx_file")
#     st.sidebar.file_uploader("Upload Task Descriptions (XLSX or CSV)", type=["xlsx", "csv"], key="data_file")
#     submit_button = st.sidebar.button("Submit")

#     docx_file = st.session_state.get("docx_file")
#     data_file = st.session_state.get("data_file")

#     if submit_button and docx_file and data_file:
#         # Clear previous information
#         st.session_state.clear()

#         # 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:
#             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 = []
#         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()
#                     if result is not None:
#                         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()


# import streamlit as st
# import os
# import openai
# import json
# import pandas as pd
# from docx import Document
# from dotenv import load_dotenv
# import time


# # Load the OpenAI API key from environment variables
# load_dotenv()
# api_key = os.getenv("OPENAI_API_KEY")
# openai.api_key = api_key

# # Streamlit app layout
# st.set_page_config(layout="wide")

# # Add custom CSS for center alignment
# st.markdown("""
#     <style>
#     .centered-title {
#         text-align: center;
#         font-size: 2.5em;
#         margin-top: 0;
#     }
#     </style>
#     """, 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 = 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"]
#     except openai.error.OpenAIError as e:
#         st.error(f"Error extracting terms from contract: {e}")
#         return None

# def analyze_task_compliance(task_description, cost_estimate, contract_text):
#     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{contract_text}\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 = 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,
#         )

#         return json.loads(response.choices[0].message["content"])
#     except openai.error.OpenAIError as e:
#         st.error(f"Error analyzing task compliance: {e}")
#         return None

# def main():
#     start = time.time()
#     st.markdown("<h1 class='centered-title'>Contract Compliance Analyzer</h1>", unsafe_allow_html=True)

#     # File upload buttons one after another
#     st.sidebar.file_uploader("Upload Contract Document (DOCX)", type="docx", key="docx_file")
#     st.sidebar.file_uploader("Upload Task Descriptions (XLSX or CSV)", type=["xlsx", "csv"], key="data_file")
#     submit_button = st.sidebar.button("Submit")

#     docx_file = st.session_state.get("docx_file")
#     data_file = st.session_state.get("data_file")

#     if submit_button and docx_file and data_file:
#         # Clear previous information
#         st.session_state.clear()

#         # 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:
#             contract_terms = json.loads(extracted_terms_json)
#         except json.JSONDecodeError as e:
#             st.error(f"JSON decoding error: {e}")
#             return
#         # Introducing a 1-second delay before analyzing task compliance
#         time.sleep(8)
#         # 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():
#             task_description = row['Task Description']
#             cost_estimate = row['Amount']
#             result = analyze_task_compliance(task_description, cost_estimate, contract_text)
            
#             if result is not None:
#                 compliance_results.append(result)
        
#         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"
#             )
#     end = time.time()
#     print("Total Time: ", end-start)

# if __name__ == "__main__":
#     main()


import streamlit as st
import os
import openai
import json
import pandas as pd
from docx import Document
from dotenv import load_dotenv
import time
import retrying

# Load the OpenAI API key from environment variables
load_dotenv()
api_key = os.getenv("OPENAI_API_KEY")
openai.api_key = api_key

# Streamlit app layout
st.set_page_config(layout="wide")

# Add custom CSS for center alignment
st.markdown("""
    <style>
    .centered-title {
        text-align: center;
        font-size: 2.5em;
        margin-top: 0;
    }
    </style>
    """, 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 = 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"]
    except openai.error.OpenAIError as e:
        st.error(f"Error extracting terms from contract: {e}")
        return None

# Add a retry decorator with exponential backoff
@retrying.retry(wait_exponential_multiplier=1000, wait_exponential_max=10000, stop_max_attempt_number=5)
def analyze_task_compliance(task_description, cost_estimate, contract_text):
    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{contract_text}\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 = 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,
        )

        return json.loads(response.choices[0].message["content"])
    except openai.error.OpenAIError as e:
        st.error(f"Error analyzing task compliance: {e}")
        return None

def main():
    start = time.time()
    st.markdown("<h1 class='centered-title'>Contract Compliance Analyzer</h1>", unsafe_allow_html=True)

    # File upload buttons one after another
    st.sidebar.file_uploader("Upload Contract Document (DOCX)", type="docx", key="docx_file")
    st.sidebar.file_uploader("Upload Task Descriptions (XLSX or CSV)", type=["xlsx", "csv"], key="data_file")
    submit_button = st.sidebar.button("Submit")

    docx_file = st.session_state.get("docx_file")
    data_file = st.session_state.get("data_file")

    if submit_button and docx_file and data_file:
        # Clear previous information
        st.session_state.clear()

        # 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:
            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():
            task_description = row['Task Description']
            cost_estimate = row['Amount']
            result = analyze_task_compliance(task_description, cost_estimate, contract_text)
            
            if result is not None:
                compliance_results.append(result)
        
        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"
            )
    end = time.time()
    print("Total Time: ", end-start)

if __name__ == "__main__":
    main()