OpenData-Bordeaux-IA-RSE

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Ilyas KHIAT commited on Jun 20

Commit

d486d32

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1 Parent(s): cc70b08

exprt import

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Files changed (7) hide show

chat_with_pps.py +30 -6
download_chart.py +2 -2
export_doc.py +45 -8
high_chart.py +1 -0
partie_prenante_carte.py +19 -1
parties_prenantes.csv +7 -0
temp.html +10 -31

chat_with_pps.py CHANGED Viewed

@@ -9,7 +9,7 @@ from download_chart import construct_plot
 from prompt import get_prompts_list
 from st_copy_to_clipboard import st_copy_to_clipboard
 from high_chart import test_chart
-from export_doc import export_conversation
 import random
@@ -117,12 +117,36 @@ def choose_model(index):
 def disp_carto_in_chat():
     test_chart()
-@st.experimental_dialog("Telecharger",width="large")
 def dowmload_history():
-    with st.spinner("Generation en cours..."):
-        summary = get_response("Donne moi un RESUME de la Conversation", st.session_state.chat_history,format_context(st.session_state['pp_grouped'],st.session_state['Nom de la marque']),st.session_state.model)
-        summary = ''.join(summary)
-    export_conversation(AIMessage(content=summary).content)
 def extract_pp_from_query(query):
     return " ".join(query.split(" ")[1:])

 from prompt import get_prompts_list
 from st_copy_to_clipboard import st_copy_to_clipboard
 from high_chart import test_chart
+from export_doc import export_conversation,convert_pp_to_csv,get_conversation
 import random
 def disp_carto_in_chat():
     test_chart()
+@st.experimental_dialog("Telecharger",width="small")
 def dowmload_history():
+    brand_name = st.session_state['Nom de la marque']
+    format = st.radio("Choisissez le document à telecharger",["",f"Rapport des parties prenantes {brand_name} (PDF)",f"DataFrame des parties prenantes {brand_name} (CSV)",f"historique de conversation {brand_name} (Fichier Texte)"])
+    if format == f"Rapport des parties prenantes {st.session_state['Nom de la marque']} (PDF)":
+        with st.spinner("Generation en cours..."):
+            summary = get_response("Donne moi un RESUME de la Conversation", st.session_state.chat_history,format_context(st.session_state['pp_grouped'],st.session_state['Nom de la marque']),st.session_state.model)
+            summary = ''.join(summary)
+            pdf = export_conversation(AIMessage(content=summary).content)
+            if pdf:
+                st.download_button("Télécharger le PDF", data=pdf, file_name=f"Cartographie {brand_name}.pdf", mime="application/pdf")
+    if format == f"DataFrame des parties prenantes {brand_name} (CSV)":
+        csv = convert_pp_to_csv(st.session_state['pp_grouped'])
+        if csv:
+            st.download_button("Télécharger le CSV", data=csv, file_name=f"parties_prenantes {brand_name}.csv", mime="text/csv")
+    if format == f"historique de conversation {brand_name} (Fichier Texte)":
+        conv = get_conversation()
+        if not conv:
+            st.error("Une erreur s'est produite lors de la récupération de l'historique de conversation")
+            return None
+        else:
+            conversation = "\n".join([f"{entry['speaker']}:\n{entry['text']}\n" for entry in conv])
+            st.download_button("Télécharger l'historique de conversation", data=conversation, file_name=f"conversation {brand_name}.txt", mime="text/plain")
+    if st.button("Fermer"):
+        st.rerun()
 def extract_pp_from_query(query):
     return " ".join(query.split(" ")[1:])

download_chart.py CHANGED Viewed

@@ -35,14 +35,14 @@ def construct_plot():
     y_array = [stakeholder['y'] for stakeholder in stakeholders]
     name_array = [stakeholder['name'] for stakeholder in stakeholders]
-    color_sequence = px.colors.qualitative.Plotly
     # Add stakeholders to plot
     for i,stakeholder in enumerate(stakeholders):
         fig.add_trace(go.Scatter(
             x=[stakeholder['x']],
             y=[stakeholder['y']],
             mode='markers+text',
-            marker=dict(color=color_sequence[i % len(color_sequence)],size=20),
             textposition="top center",
             name=stakeholder['name']
         ))

     y_array = [stakeholder['y'] for stakeholder in stakeholders]
     name_array = [stakeholder['name'] for stakeholder in stakeholders]
+    #color_sequence = px.colors.qualitative.Plotly
     # Add stakeholders to plot
     for i,stakeholder in enumerate(stakeholders):
         fig.add_trace(go.Scatter(
             x=[stakeholder['x']],
             y=[stakeholder['y']],
             mode='markers+text',
+            marker=dict(color=stakeholder['color'],size=33),
             textposition="top center",
             name=stakeholder['name']
         ))

export_doc.py CHANGED Viewed

@@ -8,19 +8,54 @@ from langchain_core.messages import AIMessage, HumanMessage
 from datetime import datetime
 from download_chart import construct_plot
 from kaleido.scopes.plotly import PlotlyScope
-def create_pdf_from_markdown(logo_path, conversation,summary,brand_name,graph_html,app_url):
     # Convertir la conversation en markdown
     markdown_text = "\n".join([f"### {entry['speaker']}:\n {entry['text']}\n ---" for entry in conversation])
     markdown_summary = f"{summary}\n --- \n ---"
     # Convertir le markdown en HTML
     html_content = markdown2.markdown(markdown_text)
     html_summary = markdown2.markdown(markdown_summary)
     analysis_date = datetime.now().strftime("%Y-%m-%d")
     # image_base64 = base64.b64encode(image_path).decode('utf-8')
     img_bytes = PlotlyScope().transform(
         figure=graph_html,
         format="png",
@@ -65,6 +100,7 @@ def create_pdf_from_markdown(logo_path, conversation,summary,brand_name,graph_ht
         <div style="text-align: center; margin-top: 20px;">
             <img src="{fig1}">
         </div>
         <div class="page-break"></div>
         <h2>RESUME</h2>
         {html_summary}
@@ -170,6 +206,7 @@ def export_conversation(summary):
     brand_name = st.session_state["Nom de la marque"]
     app_url = "https://huggingface.co/spaces/bziiit/OpenData-Bordeaux-RSE"
     logo_path = "https://static.wixstatic.com/media/d7d3da_b69e03ae99224f7d8b6e358918e60071~mv2.png/v1/crop/x_173,y_0,w_1906,h_938/fill/w_242,h_119,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/BZIIIT_LOGO-HORIZ-COULEUR.png"  # Replace with your image path
     with st.spinner("Génération du PDF..."):
         conversation = get_conversation()
@@ -181,15 +218,15 @@ def export_conversation(summary):
             st.error("Erreur lors de la génération de la cartographie")
             graph = ""
         try:
-            pdf = create_pdf_from_markdown(logo_path=logo_path, conversation=conversation,summary=summary,brand_name=brand_name,graph_html=graph,app_url=app_url)
         except Exception as e:
             pdf = None
     if pdf:
-        st.success("PDF généré avec succès!")
     else:
         st.error("Erreur lors de la génération du PDF")
-    if st.download_button("Télécharger le PDF", data=pdf, file_name=f"Cartographie {brand_name}.pdf", mime="application/pdf"):
-        st.rerun()

 from datetime import datetime
 from download_chart import construct_plot
 from kaleido.scopes.plotly import PlotlyScope
+import pandas as pd
+def colored_circle(color):
+    return f'<span style="display: inline-block; width: 15px; height: 15px; border-radius: 50%; background-color: {color};"></span>'
+def list_to_markdown(lst):
+    return "\n".join([f'<p>{colored_circle(item["color"])} {item["name"]}:</p>\ **Pouvoir**: {item["y"]}% **Influence**: {item["x"]}%' for item in lst])
+def categorize(row):
+    if 50 <= row['pouvoir'] <= 100 and 0 <= row['influence'] < 50:
+        return 'Rendre satisfait'
+    elif 50 <= row['pouvoir'] <= 100 and 50 <= row['influence'] <= 100:
+        return 'Gérer étroitement'
+    elif 0 <= row['pouvoir'] < 50 and 0 <= row['influence'] < 50:
+        return 'Suivre de près'
+    elif 0 <= row['pouvoir'] < 50 and 50 <= row['influence'] <= 100:
+        return 'Tenir informé'
+    else:
+        return 'Non catégorisé'
+@st.cache_data
+def convert_pp_to_csv(pp_grouped):
+    if pp_grouped is None or len(pp_grouped) == 0:
+        st.error("Aucune partie prenante n'a été définie")
+        return None
+    pp_df = pd.DataFrame(pp_grouped)
+    pp_df.rename(columns={"name": "parties prenantes", "x": "influence", "y": "pouvoir"}, inplace=True)
+    pp_df.drop(columns=['color'], inplace=True)
+    # Apply the function to the DataFrame to create a new column 'categorie'
+    pp_df['categorie'] = pp_df.apply(categorize, axis=1)
+    pp_df = pp_df[["parties prenantes","categorie", "pouvoir", "influence"]]
+    return pp_df.to_csv().encode("utf-8")
+@st.cache_data
+def create_pdf_from_markdown(logo_path, conversation,summary,brand_name,graph_html,app_url,list_pps):
     # Convertir la conversation en markdown
     markdown_text = "\n".join([f"### {entry['speaker']}:\n {entry['text']}\n ---" for entry in conversation])
     markdown_summary = f"{summary}\n --- \n ---"
+    markdown_list_pps = list_to_markdown(list_pps)
     # Convertir le markdown en HTML
     html_content = markdown2.markdown(markdown_text)
     html_summary = markdown2.markdown(markdown_summary)
+    html_list_pps = markdown2.markdown(markdown_list_pps)
     analysis_date = datetime.now().strftime("%Y-%m-%d")
     # image_base64 = base64.b64encode(image_path).decode('utf-8')
+    graph_html.update_layout(showlegend=False)
     img_bytes = PlotlyScope().transform(
         figure=graph_html,
         format="png",
         <div style="text-align: center; margin-top: 20px;">
             <img src="{fig1}">
         </div>
+        {html_list_pps}
         <div class="page-break"></div>
         <h2>RESUME</h2>
         {html_summary}
     brand_name = st.session_state["Nom de la marque"]
     app_url = "https://huggingface.co/spaces/bziiit/OpenData-Bordeaux-RSE"
     logo_path = "https://static.wixstatic.com/media/d7d3da_b69e03ae99224f7d8b6e358918e60071~mv2.png/v1/crop/x_173,y_0,w_1906,h_938/fill/w_242,h_119,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/BZIIIT_LOGO-HORIZ-COULEUR.png"  # Replace with your image path
+    list_pps = st.session_state['pp_grouped']
     with st.spinner("Génération du PDF..."):
         conversation = get_conversation()
             st.error("Erreur lors de la génération de la cartographie")
             graph = ""
         try:
+            pdf = create_pdf_from_markdown(logo_path=logo_path, conversation=conversation,summary=summary,brand_name=brand_name,graph_html=graph,app_url=app_url,list_pps=list_pps)
         except Exception as e:
             pdf = None
     if pdf:
+        st.success("PDF généré avec succès!}")
     else:
         st.error("Erreur lors de la génération du PDF")
+    return pdf

high_chart.py CHANGED Viewed

@@ -1,6 +1,7 @@
 import streamlit as st
 import st_hc as hct
 import download_chart as dc

 import streamlit as st
 import st_hc as hct
 import download_chart as dc
+from export_doc import convert_pp_to_csv

partie_prenante_carte.py CHANGED Viewed

@@ -235,6 +235,20 @@ def add_pp(new_pp, default_value=50):
     for pp in new_pp:
         format_pp_add_viz(pp)
 def add_pp_input_text():
     new_pp = st.text_input("Ajouter une partie prenante")
     if st.button("Ajouter",key="add_single_pp"):
@@ -313,7 +327,7 @@ def display_pp():
     brand_name = st.text_input("Nom de la marque", st.session_state["Nom de la marque"])
     st.session_state["Nom de la marque"] = brand_name
-    option = st.radio("Source", ("A partir de votre site web", "A partir de vos documents entreprise"))
     #if the user chooses to extract from website
     if option == "A partir de votre site web":
@@ -386,6 +400,10 @@ def display_pp():
                     # disp_vertical_slider(partie_prenante)
                     # st.altair_chart(c, use_container_width=True)
     if st.session_state["not_pp"] == "444":
         st.warning("Aucune parties prenantes n'est identifiable sur l'URL fournie. Fournissez une autre URL ou bien cliquez sur le boutton ci-dessous pour un Conseils IA")

     for pp in new_pp:
         format_pp_add_viz(pp)
+def add_existing_pps(pp,pouvoir,influence):
+    for i in range(len(st.session_state['pp_grouped'])):
+        if st.session_state['pp_grouped'][i]['name'] == pp:
+            st.session_state['pp_grouped'][i]['x'] = influence
+            st.session_state['pp_grouped'][i]['y'] = pouvoir
+            return None
+    st.session_state['pp_grouped'].append({'name':pp, 'x':influence,'y':pouvoir, 'color':generate_random_color()})
+def load_csv(file):
+    df = pd.read_csv(file)
+    for index, row in df.iterrows():
+        add_existing_pps(row['parties prenantes'],row['pouvoir'],row['influence'])
 def add_pp_input_text():
     new_pp = st.text_input("Ajouter une partie prenante")
     if st.button("Ajouter",key="add_single_pp"):
     brand_name = st.text_input("Nom de la marque", st.session_state["Nom de la marque"])
     st.session_state["Nom de la marque"] = brand_name
+    option = st.radio("Source", ("A partir de votre site web", "A partir de vos documents entreprise","A partir de votre Cartographie des parties prenantes telechargée en CSV"))
     #if the user chooses to extract from website
     if option == "A partir de votre site web":
                     # disp_vertical_slider(partie_prenante)
                     # st.altair_chart(c, use_container_width=True)
+    if option == "A partir de votre Cartographie des parties prenantes telechargée en CSV":
+        uploaded_file = st.file_uploader("Télécharger le fichier CSV", type="csv")
+        if uploaded_file is not None:
+            load_csv(uploaded_file)
     if st.session_state["not_pp"] == "444":
         st.warning("Aucune parties prenantes n'est identifiable sur l'URL fournie. Fournissez une autre URL ou bien cliquez sur le boutton ci-dessous pour un Conseils IA")

parties_prenantes.csv ADDED Viewed

	@@ -0,0 +1,7 @@

+influence,pouvoir,color,parties prenantes
+50,50,#c55f4a,Adetem
+50,55,#61c9fd,Bordeaux technowest
+50,60,#ca28bd,Digital aquitaine
+20,65,#6f8cd4,La french tech bordeaux
+50,70,#76af72,Le hub france ia
+50,75,#b4ba75,Le mouvement impact france

temp.html CHANGED Viewed

@@ -23,7 +23,7 @@
     <body>
         <div style="text-align: center;">
             <h1>Cartographie des parties prenantes bziiit</h1>
-            <p>Date de l'analyse IA RSE : 2024-06-19</p>
             <p>IA utilisées :</p>
             <ul>
                 <li>(US) ChatGpt 4.o</li>
@@ -33,39 +33,18 @@
         </div>
         <div class="page-break"></div>
         <div style="text-align: center; margin-top: 20px;">
-            <img 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">
         </div>
         <div class="page-break"></div>
         <h2>RESUME</h2>
-        <p>Bien sûr, voici un résumé de la conversation :</p>
-<ul>
-<li>La marque est bziiit.</li>
-<li>Il y a 7 parties prenantes identifiées pour bziiit.</li>
-<li><p>Chaque partie prenante a été évaluée en termes de pouvoir et d'influence :</p>
-<ol>
-<li>Adetem : Pouvoir de 50%, Influence de 50%</li>
-<li>Bordeaux Technowest : Pouvoir de 55%, Influence de 50%</li>
-<li>Digital Aquitaine : Pouvoir de 60%, Influence de 50%</li>
-<li>Hub France IA : Pouvoir de 65%, Influence de 50%</li>
-<li>La French Tech Bordeaux : Pouvoir de 70%, Influence de 50%</li>
-<li>Mouvement Impact France : Pouvoir de 75%, Influence de 50%</li>
-<li>Vivexalto : Pouvoir de 80%, Influence de 50%</li>
-</ol></li>
-<li><p>Les parties prenantes ont été segmentées en quatre catégories basées sur leur pouvoir et leur influence :</p>
-<ul>
-<li>Rendre satisfait : Pouvoir entre 50 et 100, Influence entre 0 et 50</li>
-<li>Gérer étroitement : Pouvoir entre 50 et 100, Influence entre 50 et 100</li>
-<li>Suivre de près : Pouvoir entre 0 et 50, Influence entre 0 et 50</li>
-<li>Tenir informé : Pouvoir entre 0 et 50, Influence entre 50 et 100</li>
-</ul></li>
-</ul>
-<p>Tous les acteurs identifiés se trouvent dans la catégorie "Rendre satisfait" en raison de leur pouvoir significatif (entre 50% et 80%) et leur influence modérée (50%).</p>
-<p>Le résumé contextuel donné ci-dessus aide à comprendre la position de chaque partie prenante et leur impact potentiel sur la marque bziiit.</p>
 <hr />

     <body>
         <div style="text-align: center;">
             <h1>Cartographie des parties prenantes bziiit</h1>
+            <p>Date de l'analyse IA RSE : 2024-06-20</p>
             <p>IA utilisées :</p>
             <ul>
                 <li>(US) ChatGpt 4.o</li>
         </div>
         <div class="page-break"></div>
         <div style="text-align: center; margin-top: 20px;">
+            <img 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">
         </div>
+        <p><p><span style="display: inline-block; width: 15px; height: 15px; border-radius: 50%; background-color: #1337df;"></span> Adetem:</p> <strong>Pouvoir</strong>: 50% <strong>Influence</strong>: 50%
+<p><span style="display: inline-block; width: 15px; height: 15px; border-radius: 50%; background-color: #3e3365;"></span> Bordeaux technowest:</p> <strong>Pouvoir</strong>: 55% <strong>Influence</strong>: 50%
+<p><span style="display: inline-block; width: 15px; height: 15px; border-radius: 50%; background-color: #123a82;"></span> Digital aquitaine:</p> <strong>Pouvoir</strong>: 60% <strong>Influence</strong>: 50%
+<p><span style="display: inline-block; width: 15px; height: 15px; border-radius: 50%; background-color: #76318f;"></span> Hub france ia:</p> <strong>Pouvoir</strong>: 65% <strong>Influence</strong>: 50%
+<p><span style="display: inline-block; width: 15px; height: 15px; border-radius: 50%; background-color: #64af5e;"></span> La french tech bordeaux:</p> <strong>Pouvoir</strong>: 70% <strong>Influence</strong>: 50%
+<p><span style="display: inline-block; width: 15px; height: 15px; border-radius: 50%; background-color: #e9113b;"></span> Mouvement impact france:</p> <strong>Pouvoir</strong>: 75% <strong>Influence</strong>: 50%</p>
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         <h2>RESUME</h2>
+        <p>Dans la conversation actuelle, la marque en question est bziiit. Les parties prenantes de bziiit ont été identifiées et leurs pouvoirs et influences respectifs ont été détaillés. Les six parties prenantes sont Adetem, Bordeaux Technowest, Digital Aquitaine, Hub France IA, La French Tech Bordeaux et Mouvement Impact France, chacune avec des niveaux variés de pouvoir et d'influence. Les catégories de gestion des parties prenantes ont été définies comme suit : "Rendre satisfait", "Gérer étroitement", "Suivre de près" et "Tenir informé". La question posée demandait un résumé de la conversation jusqu'à présent.</p>
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