Ilyas KHIAT
commited on
Commit
·
c673bf2
1
Parent(s):
3befd1b
ui/ux fixes
Browse files- chat_with_pps.py +45 -18
- export_doc.py +5 -3
- high_chart.py +2 -10
- partie_prenante_carte.py +48 -7
- parties preanantes.csv +5 -0
- parties_prenantes (10).csv +2 -0
- parties_prenantes (5).csv +2 -0
- parties_prenantes -bziiit-.csv +2 -0
- temp.html +5 -10
chat_with_pps.py
CHANGED
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@@ -11,6 +11,7 @@ from st_copy_to_clipboard import st_copy_to_clipboard
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from high_chart import test_chart
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from export_doc import export_conversation,convert_pp_to_csv,get_conversation
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import random
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def parse_conversation(file_content):
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conversation = []
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@@ -153,7 +154,8 @@ def choose_model(index):
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@st.experimental_dialog("Ma cartographie",width="large")
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def disp_carto_in_chat():
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test_chart()
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@st.experimental_dialog("Télécharger",width="small")
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def dowmload_history():
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@@ -170,7 +172,7 @@ def dowmload_history():
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if format == f"Tableau des parties prenantes (CSV)":
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csv = convert_pp_to_csv(st.session_state['pp_grouped'])
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if csv:
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st.download_button("Télécharger le CSV", data=csv, file_name=f"parties_prenantes {brand_name}
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if format == f"Historique de conversation (Fichier Texte)":
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conv = get_conversation()
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@@ -184,15 +186,33 @@ def dowmload_history():
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if st.button("Fermer"):
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st.rerun()
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@st.experimental_dialog("Importer",width="small")
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def import_conversation():
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uploaded_file = st.file_uploader("
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if uploaded_file is not None:
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@@ -262,13 +282,17 @@ def display_chat():
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with st.chat_message("Moi"):
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st.write(message.content)
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#check if the last message is from the user , that means execute button has been clicked
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last_message = st.session_state.chat_history[-1]
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if isinstance(last_message, HumanMessage):
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with st.chat_message("AI"):
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@@ -286,13 +310,16 @@ def display_chat():
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st.markdown(user_query)
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with st.chat_message("AI"):
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st.markdown(f"**{st.session_state.model}**")
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-
if "/rajoute"
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partie_prenante = extract_pp_from_query(user_query)
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format_pp_add_viz(partie_prenante)
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-
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from high_chart import test_chart
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from export_doc import export_conversation,convert_pp_to_csv,get_conversation
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import random
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import pandas as pd
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def parse_conversation(file_content):
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conversation = []
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@st.experimental_dialog("Ma cartographie",width="large")
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def disp_carto_in_chat():
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if test_chart() == "saved":
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st.rerun()
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@st.experimental_dialog("Télécharger",width="small")
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def dowmload_history():
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if format == f"Tableau des parties prenantes (CSV)":
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csv = convert_pp_to_csv(st.session_state['pp_grouped'])
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if csv:
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st.download_button("Télécharger le CSV", data=csv, file_name=f"parties_prenantes -{brand_name}-.csv", mime="application/vnd.ms-excel")
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if format == f"Historique de conversation (Fichier Texte)":
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conv = get_conversation()
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if st.button("Fermer"):
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st.rerun()
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def add_existing_pps(pp,pouvoir,influence):
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for i in range(len(st.session_state['pp_grouped'])):
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if st.session_state['pp_grouped'][i]['name'] == pp:
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st.session_state['pp_grouped'][i]['x'] = influence
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st.session_state['pp_grouped'][i]['y'] = pouvoir
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return None
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st.session_state['pp_grouped'].append({'name':pp, 'x':influence,'y':pouvoir, 'color':generate_random_color()})
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def load_csv(file):
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df = pd.read_csv(file)
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for index, row in df.iterrows():
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add_existing_pps(row['parties prenantes'],row['pouvoir'],row['influence'])
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@st.experimental_dialog("Importer",width="small")
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def import_conversation():
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uploaded_file = st.file_uploader("Télécharger le fichier CSV", type="csv")
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if uploaded_file is not None:
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file_name = uploaded_file.name
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try:
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load_csv(file_name)
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brand_name_from_csv = file_name.split("-")[1]
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st.session_state["Nom de la marque"] = brand_name_from_csv
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st.rerun()
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except Exception as e:
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st.error("Erreur lors de la lecture du fichier")
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with st.chat_message("Moi"):
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st.write(message.content)
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#check if the last message is from the user , that means execute button has been clicked in the prompts
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last_message = st.session_state.chat_history[-1]
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if isinstance(last_message, HumanMessage):
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with st.chat_message("AI"):
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if last_message.content.startswith("/rajoute"):
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response = "Partie prenante ajoutée"
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st.write(response)
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st.session_state.chat_history.append(AIMessage(content=response))
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else:
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response = st.write_stream(get_response(last_message.content, st.session_state.chat_history,format_context(st.session_state['pp_grouped'],st.session_state['Nom de la marque']),st.session_state.model))
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st.session_state.chat_history.append(AIMessage(content=response))
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st.markdown(user_query)
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with st.chat_message("AI"):
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st.markdown(f"**{st.session_state.model}**")
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if user_query.startswith("/rajoute"):
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partie_prenante = extract_pp_from_query(user_query)
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format_pp_add_viz(partie_prenante)
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disp_carto_in_chat()
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else:
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st.warning(user_query)
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response = st.write_stream(get_response(user_query, st.session_state.chat_history,format_context(st.session_state['pp_grouped'],st.session_state['Nom de la marque']),st.session_state.model))
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if "cartographie" in response:
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display_chart()
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st.session_state.chat_history.append(AIMessage(content=response))
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export_doc.py
CHANGED
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@@ -14,7 +14,7 @@ def colored_circle(color):
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return f'<span style="display: inline-block; width: 15px; height: 15px; border-radius: 50%; background-color: {color};"></span>'
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def list_to_markdown(lst):
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return "\n".join([f'<p>{colored_circle(item["color"])} {item["name"]}
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def categorize(row):
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if 50 <= row['pouvoir'] <= 100 and 0 <= row['influence'] < 50:
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@@ -34,12 +34,14 @@ def convert_pp_to_csv(pp_grouped):
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st.error("Aucune partie prenante n'a été définie")
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return None
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pp_df = pd.DataFrame(pp_grouped)
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pp_df.rename(columns={"name": "parties prenantes", "x": "influence", "y": "pouvoir"}, inplace=True)
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pp_df.drop(columns=['color'], inplace=True)
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# Apply the function to the DataFrame to create a new column 'categorie'
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pp_df['categorie'] = pp_df.apply(categorize, axis=1)
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pp_df = pp_df[["parties prenantes","categorie", "pouvoir", "influence"]]
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-
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@st.cache_data
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def create_pdf_from_markdown(logo_path, conversation,summary,brand_name,graph_html,app_url,list_pps):
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@@ -87,7 +89,7 @@ def create_pdf_from_markdown(logo_path, conversation,summary,brand_name,graph_ht
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</head>
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<body>
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<div style="text-align: center;">
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<h1>Cartographie des parties prenantes {brand_name}</h1>
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<p>Date de l'analyse IA RSE : {analysis_date}</p>
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<p>IA utilisées :</p>
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<ul>
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return f'<span style="display: inline-block; width: 15px; height: 15px; border-radius: 50%; background-color: {color};"></span>'
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def list_to_markdown(lst):
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return "\n".join([f'<p>{colored_circle(item["color"])} <b>{item["name"]}</b>: Pouvoir:{item["y"]}% Influence:{item["x"]}%</p>' for item in lst[:20]])
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def categorize(row):
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if 50 <= row['pouvoir'] <= 100 and 0 <= row['influence'] < 50:
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st.error("Aucune partie prenante n'a été définie")
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return None
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pp_df = pd.DataFrame(pp_grouped)
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pp_df.index.name = 'N°'
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pp_df.rename(columns={"name": "parties prenantes", "x": "influence", "y": "pouvoir"}, inplace=True)
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pp_df.drop(columns=['color'], inplace=True)
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# Apply the function to the DataFrame to create a new column 'categorie'
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pp_df['categorie'] = pp_df.apply(categorize, axis=1)
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pp_df = pp_df[["parties prenantes","categorie", "pouvoir", "influence"]]
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pp_df.rename_axis('N°', axis=1)
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return pp_df.to_csv(index=True,encoding="utf-8")
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@st.cache_data
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def create_pdf_from_markdown(logo_path, conversation,summary,brand_name,graph_html,app_url,list_pps):
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</head>
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<body>
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<div style="text-align: center;">
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<h1>Cartographie des parties prenantes "{brand_name}"</h1>
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<p>Date de l'analyse IA RSE : {analysis_date}</p>
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<p>IA utilisées :</p>
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<ul>
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high_chart.py
CHANGED
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@@ -193,16 +193,8 @@ def test_chart():
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# if chart:
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# st.session_state['pp_grouped'] = chart
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col0,
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if col1.button("Sauvegarder",key="save"):
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st.session_state['pp_grouped'] = chart.copy()
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if col2.button("Télécharger",key="download"):
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if not chart:
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st.error("Un truc ne va pas. Veuillez réessayer")
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else:
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st.session_state['pp_grouped'] = chart.copy()
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fig = dc.construct_plot()
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st.plotly_chart(fig)
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# if chart:
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# st.session_state['pp_grouped'] = chart
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col0,col1,col2 = st.columns([1,1,1])
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if col1.button("Sauvegarder",key="save"):
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st.session_state['pp_grouped'] = chart.copy()
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return "saved"
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partie_prenante_carte.py
CHANGED
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@@ -6,7 +6,6 @@ import random
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import streamlit as st
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from dotenv import load_dotenv
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from PyPDF2 import PdfReader
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from langchain.text_splitter import CharacterTextSplitter,RecursiveCharacterTextSplitter
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from langchain_experimental.text_splitter import SemanticChunker
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from langchain_community.embeddings import OpenAIEmbeddings
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from langchain import hub
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from langchain_core.output_parsers import StrOutputParser
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from langchain_core.runnables import RunnablePassthrough
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from langchain_community.document_loaders import WebBaseLoader,FireCrawlLoader
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from langchain_core.prompts.prompt import PromptTemplate
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from session import set_partie_prenante
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import os
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delete_pp(temp)
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del st.session_state.urls[index]
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del st.session_state["parties_prenantes"][index]
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st.
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if len(st.session_state.urls) > index:
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# Instead of using markdown, use an expander in the first column
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if col2.button("❌", key=f"butp{index}"):
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del st.session_state["pp_grouped"][index]
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st.
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if len(st.session_state["pp_grouped"]) > index:
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name = st.session_state["pp_grouped"][index]["name"]
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brand_name = st.text_input("Nom de la marque", st.session_state["Nom de la marque"])
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st.session_state["Nom de la marque"] = brand_name
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option = st.radio("Source", ("A partir de votre site web", "A partir de vos documents entreprise","A partir de
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#if the user chooses to extract from website
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if option == "A partir de votre site web":
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# disp_vertical_slider(partie_prenante)
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# st.altair_chart(c, use_container_width=True)
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if option ==
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uploaded_file = st.file_uploader("Télécharger le fichier CSV", type="csv")
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if uploaded_file is not None:
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-
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if st.session_state["not_pp"] == "444":
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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")
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import streamlit as st
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from dotenv import load_dotenv
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from langchain.text_splitter import CharacterTextSplitter,RecursiveCharacterTextSplitter
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from langchain_experimental.text_splitter import SemanticChunker
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from langchain_community.embeddings import OpenAIEmbeddings
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from langchain import hub
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from langchain_core.output_parsers import StrOutputParser
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from langchain_core.runnables import RunnablePassthrough
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from langchain_community.document_loaders import WebBaseLoader,FireCrawlLoader,PyPDFLoader
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from langchain_core.prompts.prompt import PromptTemplate
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from session import set_partie_prenante
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import os
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delete_pp(temp)
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del st.session_state.urls[index]
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del st.session_state["parties_prenantes"][index]
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st.rerun() # Rerun the app to update the display
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if len(st.session_state.urls) > index:
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# Instead of using markdown, use an expander in the first column
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if col2.button("❌", key=f"butp{index}"):
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del st.session_state["pp_grouped"][index]
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st.rerun()
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if len(st.session_state["pp_grouped"]) > index:
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name = st.session_state["pp_grouped"][index]["name"]
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brand_name = st.text_input("Nom de la marque", st.session_state["Nom de la marque"])
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st.session_state["Nom de la marque"] = brand_name
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option = st.radio("Source", ("A partir de votre site web", "A partir de vos documents entreprise","A partir de cartographie existante"))
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#if the user chooses to extract from website
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if option == "A partir de votre site web":
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# disp_vertical_slider(partie_prenante)
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# st.altair_chart(c, use_container_width=True)
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if option =="A partir de vos documents entreprise":
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| 403 |
+
|
| 404 |
+
uploaded_file = st.file_uploader("Télécharger le fichier PDF", type="pdf")
|
| 405 |
+
if uploaded_file is not None:
|
| 406 |
+
|
| 407 |
+
if st.button("ajouter",key="add_pp_pdf"):
|
| 408 |
+
st.session_state["not_pp"] = ""
|
| 409 |
+
|
| 410 |
+
with st.spinner("Processing..."):
|
| 411 |
+
file_name = uploaded_file.name
|
| 412 |
+
with open(file_name, mode='wb') as w:
|
| 413 |
+
w.write(uploaded_file.getvalue())
|
| 414 |
+
pdf = PyPDFLoader(file_name)
|
| 415 |
+
text = pdf.load()
|
| 416 |
+
st.session_state["latest_doc"] = text
|
| 417 |
+
input_variables = {"BRAND_NAME": brand_name, "BRAND_DESCRIPTION": ""}
|
| 418 |
+
partie_prenante = extract_pp(text, input_variables)
|
| 419 |
+
|
| 420 |
+
if "444" in partie_prenante: #444 is the code for no brand found , chosen
|
| 421 |
+
st.session_state["not_pp"] = "444"
|
| 422 |
+
|
| 423 |
+
elif "445" in partie_prenante: #445 is the code for no website found with the given url
|
| 424 |
+
st.error("Aucun site web trouvé avec l'url donnée")
|
| 425 |
+
st.session_state["not_pp"] = ""
|
| 426 |
+
|
| 427 |
+
else:
|
| 428 |
+
st.session_state["not_pp"] = ""
|
| 429 |
+
partie_prenante = sorted(partie_prenante)
|
| 430 |
+
st.session_state["urls"].append(file_name)
|
| 431 |
+
add_pp(partie_prenante)
|
| 432 |
+
|
| 433 |
+
if option == "A partir de cartographie existante":
|
| 434 |
uploaded_file = st.file_uploader("Télécharger le fichier CSV", type="csv")
|
| 435 |
if uploaded_file is not None:
|
| 436 |
+
if st.button("ajouter",key="add_pp_csv"):
|
| 437 |
+
file_name = uploaded_file.name
|
| 438 |
+
with open(file_name, mode='wb') as w:
|
| 439 |
+
w.write(uploaded_file.getvalue())
|
| 440 |
+
|
| 441 |
+
try:
|
| 442 |
+
load_csv(file_name)
|
| 443 |
+
brand_name_from_csv = file_name.split("-")[1]
|
| 444 |
+
st.session_state["Nom de la marque"] = brand_name_from_csv
|
| 445 |
+
except Exception as e:
|
| 446 |
+
st.error("Erreur lors de la lecture du fichier")
|
| 447 |
+
|
| 448 |
|
| 449 |
if st.session_state["not_pp"] == "444":
|
| 450 |
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 preanantes.csv
ADDED
|
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
parties prenantes,categorie,pouvoir,influence
|
| 2 |
+
tt,Tenir informé,17,80
|
| 3 |
+
gr,Rendre satisfait,70,24
|
| 4 |
+
test,Gérer étroitement,55,50
|
| 5 |
+
boob,Gérer étroitement,77,74
|
parties_prenantes (10).csv
ADDED
|
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Col Name,parties prenantes,categorie,pouvoir,influence
|
| 2 |
+
0,test,Gérer étroitement,50,50
|
parties_prenantes (5).csv
ADDED
|
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
|
|
|
| 1 |
+
parties prenantes,categorie,pouvoir,influence
|
| 2 |
+
b,Gérer étroitement,50,50
|
parties_prenantes -bziiit-.csv
ADDED
|
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
|
|
|
| 1 |
+
N°,parties prenantes,categorie,pouvoir,influence
|
| 2 |
+
0,tt,Gérer étroitement,50,50
|
temp.html
CHANGED
|
@@ -22,8 +22,8 @@
|
|
| 22 |
</head>
|
| 23 |
<body>
|
| 24 |
<div style="text-align: center;">
|
| 25 |
-
<h1>Cartographie des parties prenantes bziiit</h1>
|
| 26 |
-
<p>Date de l'analyse IA RSE : 2024-06-
|
| 27 |
<p>IA utilisées :</p>
|
| 28 |
<ul>
|
| 29 |
<li>(US) ChatGpt 4.o</li>
|
|
@@ -33,18 +33,13 @@
|
|
| 33 |
</div>
|
| 34 |
<div class="page-break"></div>
|
| 35 |
<div style="text-align: center; margin-top: 20px;">
|
| 36 |
-
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">
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</div>
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<p><
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<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%
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<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%
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<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%
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<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%
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<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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<div class="page-break"></div>
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<h2>RESUME</h2>
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<p>Dans
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<hr />
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</head>
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<body>
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<div style="text-align: center;">
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+
<h1>Cartographie des parties prenantes "bziiit"</h1>
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<p>Date de l'analyse IA RSE : 2024-06-25</p>
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<p>IA utilisées :</p>
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<ul>
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<li>(US) ChatGpt 4.o</li>
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</div>
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<div class="page-break"></div>
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">
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<p><span style="display: inline-block; width: 15px; height: 15px; border-radius: 50%; background-color: #46ca57;"></span> test - <b>Pouvoir:</b> 50% <b>Influence:</b> 50%</p>
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<div class="page-break"></div>
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<h2>RESUME</h2>
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<p>Dans cette conversation, vous avez demandé une cartographie des parties prenantes pour la marque bziiit. Il a été identifié qu'il y a une seule partie prenante, nommée 0.test, qui possède un pouvoir de 50% et une influence de 50%. En fonction de ces paramètres, il semble que 0.test devrait être géré étroitement car leur pouvoir et leur influence sont tous deux à 50%. Ensuite, vous avez demandé un résumé de cette conversation.</p>
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