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| import streamlit as st | |
| import os | |
| from application.services import gemini_api_service, streamlit_function | |
| from google.genai.errors import ClientError | |
| from application.utils import logger | |
| from application.schemas.response_schema import ( | |
| GEMINI_GHG_PARAMETERS, GEMINI_ENVIRONMENTAL_PARAMETERS_CSRD, | |
| GEMINI_ENVIRONMENT_PARAMETERS, GEMINI_SOCIAL_PARAMETERS, | |
| GEMINI_GOVERNANCE_PARAMETERS, GEMINI_MATERIALITY_PARAMETERS, | |
| GEMINI_NET_ZERO_INTERVENTION_PARAMETERS, FULL_RESPONSE_SCHEMA | |
| ) | |
| import test | |
| logger = logger.get_logger() | |
| streamlit_function.config_homepage() | |
| st.title("Sustainability Report Analyzer") | |
| st.write("Upload your sustainability report PDF and generate insights using different models.") | |
| MODEL = ["gemini-1.5-pro-latest", "gemini-2.0-flash", "gemini-1.5-flash", "gemini-2.5-exp"] | |
| MODEL_1 = "gemini-1.5-pro-latest" | |
| MODEL_2 = "gemini-2.0-flash" | |
| MODEL_3 = "gemini-1.5-flash" | |
| API_1 = "gemini" | |
| API_2 = "gemini" | |
| API_3 = "gemini" | |
| pdf_file = streamlit_function.upload_file("pdf", label="Upload Sustainability Report PDF") | |
| for key in [f"{MODEL_1}_result", f"{MODEL_2}_result", f"{MODEL_3}_result", "pdf_file"]: | |
| if key not in st.session_state: | |
| st.session_state[key] = None | |
| if "excel_file" not in st.session_state: | |
| st.session_state["excel_file"] = None | |
| if st.session_state.pdf_file: | |
| with st.container(): | |
| col1, col2, col3 = st.columns([5, 5, 5], gap="small") | |
| file_name = st.session_state.pdf_file[0].name.removesuffix(".pdf") | |
| excel_file=None | |
| with col1: | |
| if st.button(f"Generate {MODEL_1} Response"): | |
| with st.spinner(f"Calling {MODEL_1}..."): | |
| result = gemini_api_service.extract_emissions_data_as_json(API_1 , MODEL_1, st.session_state.pdf_file[0],FULL_RESPONSE_SCHEMA) | |
| excel_file = streamlit_function.export_results_to_excel(result, MODEL_1, file_name) | |
| st.session_state[f"{MODEL_1}_result"] = result | |
| if st.session_state[f"{MODEL_1}_result"]: | |
| st.write(f"Extracted Metrics by {MODEL_1}_result") | |
| st.json(st.session_state[f"{MODEL_1}_result"]) | |
| with col2: | |
| if st.button(f"Generate {MODEL_2} Response"): | |
| with st.spinner(f"Calling {MODEL_2}..."): | |
| result = gemini_api_service.extract_emissions_data_as_json(API_2, MODEL_2, st.session_state.pdf_file[0],FULL_RESPONSE_SCHEMA) | |
| excel_file = streamlit_function.export_results_to_excel(result, MODEL_2, file_name) | |
| st.session_state[f"{MODEL_2}_result"] = result | |
| if st.session_state[f"{MODEL_2}_result"]: | |
| st.write(f"Extracted Metrics by {MODEL_2}_result") | |
| st.json(st.session_state[f"{MODEL_2}_result"]) | |
| with col3: | |
| try: | |
| if st.button(f"Generate {MODEL_3} Response"): | |
| with st.spinner(f"Calling {MODEL_3}..."): | |
| result = gemini_api_service.extract_emissions_data_as_json(API_3, MODEL_3, st.session_state.pdf_file[0], FULL_RESPONSE_SCHEMA) | |
| excel_file = streamlit_function.export_results_to_excel(result, MODEL_3, file_name) | |
| st.session_state[f"{MODEL_3}_result"] = result | |
| except ClientError as e: | |
| st.error(f"Gemini API Error: {e}") | |
| logger.error("Error Details:", e.message, e.response) | |
| if st.session_state[f"{MODEL_3}_result"]: | |
| st.write(f"Extracted Metrics by {MODEL_3}_result") | |
| st.json(st.session_state[f"{MODEL_3}_result"]) | |
| file_path = f"data/{file_name}.xlsx" | |
| if os.path.exists(file_path): | |
| with open(file_path, "rb") as file: | |
| st.download_button( | |
| label="Download Excel File", | |
| data=file, | |
| file_name=f"{file_name}.xlsx", | |
| mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" | |
| ) |