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| import gradio as gr | |
| from scrape_3gpp import * | |
| from excel_chat import * | |
| from classification import * | |
| from chart_generation import * | |
| from charts_advanced import * | |
| from users_management import * | |
| # Categories | |
| categories = [ | |
| { | |
| "topic": "Confidentiality and Privacy Protection", | |
| "description": "This topic covers the protection of confidentiality, privacy, and integrity in security systems. It also includes authentication and authorization processes.", | |
| "experts": ["Mireille"] | |
| }, | |
| { | |
| "topic": "Distributed Trust and End-User Trust Models", | |
| "description": "This topic focuses on distributed trust models and how end-users establish trust in secure systems.", | |
| "experts": ["Mireille", "Khawla"] | |
| }, | |
| { | |
| "topic": "Secure Element and Key Provisioning", | |
| "description": "This topic involves the secure element in systems and the process of key provisioning.", | |
| "experts": ["Mireille"] | |
| }, | |
| { | |
| "topic": "Residential Gateway Security", | |
| "description": "This topic covers the security aspects of Residential Gateways.", | |
| "experts": ["Mireille"] | |
| }, | |
| { | |
| "topic": "Standalone Non-Public Network (SNPN) Inter-Connection and Cybersecurity", | |
| "description": "This topic focuses on the inter-connection of Standalone Non-Public Networks and related cyber-security topics.", | |
| "experts": ["Khawla"] | |
| }, | |
| { | |
| "topic": "Distributed Ledger and Blockchain in SNPN", | |
| "description": "This topic covers the use of distributed ledger technology and blockchain in securing Standalone Non-Public Networks.", | |
| "experts": ["Khawla"] | |
| }, | |
| { | |
| "topic": "Distributed Networks and Communication", | |
| "description": "This topic involves distributed networks such as mesh networks, ad-hoc networks, and multi-hop networks, and their cyber-security aspects.", | |
| "experts": ["Guillaume"] | |
| }, | |
| { | |
| "topic": "Swarm of Drones and Unmanned Aerial Vehicles Network Infrastructure", | |
| "description": "This topic covers the network infrastructure deployed by Swarm of Drones and Unmanned Aerial Vehicles.", | |
| "experts": ["Guillaume"] | |
| }, | |
| { | |
| "topic": "USIM and Over-the-Air Services", | |
| "description": "This topic involves USIM and related over-the-air services such as Steering of Roaming, roaming services, network selection, and UE configuration.", | |
| "experts": ["Vincent"] | |
| }, | |
| { | |
| "topic": "Eco-Design and Societal Impact of Technology", | |
| "description": "This topic covers eco-design concepts, including energy saving, energy efficiency, carbon emissions, and the societal impact of technology.", | |
| "experts": ["Pierre"] | |
| }, | |
| { | |
| "topic": "Service Requirements of New Services", | |
| "description": "This topic involves defining service requirements for new services, detecting low signals of new trends and technologies, and assessing their impact on USIM services or over-the-air services.", | |
| "experts": ["Ly-Thanh"] | |
| }, | |
| { | |
| "topic": "Satellite and Non Terrestrial Networks", | |
| "description": "This topic covers satellite networks, Non Terrestrial Networks, Private Networks, IoT, Inter Satellite communication, and Radio Access Network.", | |
| "experts": ["Nicolas"] | |
| }, | |
| { | |
| "topic": "Public Safety and Emergency Communication", | |
| "description": "This topic involves Public Safety Communication, Military Communication, Emergency Calls, Emergency Services, Disaster Communication Access, and other related areas.", | |
| "experts": ["Dorin"] | |
| } | |
| ] | |
| df_cate = pd.DataFrame(categories) | |
| # def update_label(label1): | |
| # return gr.update(choices=list(df.columns)) | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown("## Extaction, Classification and AI tool") | |
| with gr.Column(): | |
| md_username = gr.Markdown() | |
| btn_logout = gr.Button("Logout") | |
| with gr.Accordion(label="**Login** to keep user preferences", open=False): | |
| st_user = gr.State() | |
| with gr.Column(): | |
| tb_user = gr.Textbox(label='Username') | |
| tb_pwd = gr.Textbox(label='Password', type='password') | |
| with gr.Row(): | |
| btn_login = gr.Button('Login') | |
| with gr.Tab("File extraction"): | |
| gr.Markdown(" Put either just a link, or a link and an excel file with an 'Actions' column") | |
| with gr.Row(): | |
| dd_url = gr.Dropdown(label="(e.g. https://www.3gpp.org/ftp/TSG_SA/WG1_Serv/TSGS1_105_Athens/Docs)", multiselect=False, value="https://www.3gpp.org/ftp/", allow_custom_value=True, scale=9) | |
| btn_search = gr.Button("Search") | |
| with gr.Accordion("Filter by file status", open=False): | |
| with gr.Row(): | |
| dd_status = gr.Dropdown(label="Status to look for (Optional)", allow_custom_value=False, multiselect=True, scale=7) | |
| btn_search_status = gr.Button("Search for status", scale=2) | |
| btn_extract = gr.Button("Extract excel from URL") | |
| with gr.Tab("Ask LLM"): | |
| dd_source_ask = gr.Dropdown(label="Source Column(s)", multiselect=True) | |
| tb_destcol = gr.Textbox(label="Destination column label (e.g. Summary, ELI5, PAB)") | |
| dd_prompt = gr.Dropdown(label="Prompt", allow_custom_value=True, multiselect=True, max_choices=1) | |
| dd_llm = gr.Dropdown(["Mistral Tiny","Mistral Small","Mistral Medium", "Claude Sonnet", "Claude Opus", "Groq (mixtral)"],value=”Groq (mixtral)”, label="Choose your LLM") | |
| with gr.Accordion("Filters", open=False): | |
| with gr.Row(): | |
| dd_searchcol = gr.Dropdown(label="Column to look into (Optional)", multiselect=False, scale=4) | |
| dd_keywords = gr.Dropdown(label="Words to look for (Optional)", multiselect=True, allow_custom_value=True, scale=5) | |
| mist_button = gr.Button("Ask AI") | |
| with gr.Tab("Classification by topic"): | |
| dd_source_class = gr.Dropdown(label="Source Column", multiselect=False) | |
| gr.Markdown("### The predefined categories can be modified at any time") | |
| df_category = gr.DataFrame(label='categories', value=df_cate, interactive=True) | |
| btn_classif = gr.Button("Categorize") | |
| with gr.Tab(" Personalised Charts Generation"): | |
| with gr.Row(): | |
| dd_label1 = gr.Dropdown(label="Label 1", multiselect=False) | |
| dd_label2 = gr.Dropdown(label="Label 2", value="", multiselect=False) | |
| btn_chart = gr.Button("Generate Bar Plot") | |
| plt_figure = gr.Plot() | |
| with gr.Tab("Meeting Report (charts)"): | |
| #gr.Markdown("## 🚧 Actuellement en maintenance 🚧") | |
| with gr.Tab("Overall"): | |
| btn_overall = gr.Button("Overall Review") | |
| with gr.Tab("By Expert"): | |
| dd_exp=gr.Dropdown(label="Experts", multiselect=False, allow_custom_value=True,) | |
| btn_expert = gr.Button("Top 10 by expert") | |
| with gr.Tab("By Company"): | |
| tb_com=gr.Textbox(label="Company Name",info="You can write 1, 2 or 3 company names at the same time") | |
| btn_type = gr.Button("Company info") | |
| with gr.Row(): | |
| plt_chart = gr.Plot(label="Graphique") | |
| plt_chart2 = gr.Plot(label="Graphique") | |
| plt_chart3 = gr.Plot(label="Graphique") | |
| with gr.Accordion("Excel Preview", open=False): | |
| df_output = gr.DataFrame() | |
| fi_excel = gr.File(label="Excel File") | |
| # authentication | |
| btn_login.click(auth_user, inputs=[tb_user, tb_pwd], outputs=[st_user, md_username, dd_prompt, dd_keywords]) | |
| tb_pwd.submit(auth_user, inputs=[tb_user, tb_pwd], outputs=[st_user, md_username, dd_prompt, dd_keywords]) | |
| btn_logout.click(logout, inputs=None, outputs=[st_user, md_username, dd_prompt, dd_keywords]) | |
| btn_search_status.click(extract_statuses, inputs=dd_url, outputs=dd_status) | |
| btn_search.click(browse_folder, inputs=dd_url, outputs=dd_url) | |
| dd_url.change(browse_folder, inputs=dd_url, outputs=dd_url) | |
| #fi_excel.change(get_expert,inputs=fi_excel, outputs=dd_exp) | |
| fi_excel.change(get_columns, inputs=[fi_excel], outputs=[dd_source_ask, dd_source_class, dd_label1, dd_label2, dd_searchcol, df_output]) | |
| btn_extract.click(extractionPrincipale, inputs=[dd_url, fi_excel, dd_status], outputs=[fi_excel]) | |
| mist_button.click(chat_with_mistral, inputs=[dd_source_ask, tb_destcol, dd_prompt, fi_excel, dd_url, dd_searchcol, dd_keywords, dd_llm, st_user], outputs=[fi_excel, df_output, dd_prompt, dd_keywords]) | |
| btn_classif.click(classification, inputs=[dd_source_class, fi_excel, df_category], outputs=[fi_excel, df_output]) | |
| btn_chart.click(create_bar_plot, inputs=[fi_excel, dd_label1, dd_label2], outputs=[plt_figure]) | |
| btn_overall.click(generate_company_chart,inputs=[fi_excel], outputs=[plt_chart]) | |
| btn_overall.click(status_chart,inputs=[fi_excel], outputs=[plt_chart2]) | |
| btn_overall.click(category_chart,inputs=[fi_excel], outputs=[plt_chart3]) | |
| btn_expert.click(chart_by_expert,inputs=[fi_excel,dd_exp], outputs=[plt_chart]) | |
| btn_type.click(company_document_type,inputs=[fi_excel,tb_com], outputs=[plt_chart]) | |
| # dd_label1.change(update_label, inputs=[dd_label1], outputs=[dd_label2]) | |
| demo.launch(debug=True) |