test

app.py

@@ -9,7 +9,7 @@ from ActionsRSE import display_actions_rse
 from AnalyseActionsRSE import display_analyse_actions_rse
 from partiesprenantes import display_materiality_partiesprenantes
 from partie_prenante_carte import display_pp
-from pp_viz import display_viz
+
 
 # Import modifiédes fonctions liées aux scripts
 from projetRSE import display_rse_projects
@@ -22,6 +22,7 @@ from RAG_PDF_WEB import rag_pdf_web
 from prompt import get_prompts_list,prompt_execution,execute_prompt
 from chat_with_pps import display_chat
 from high_chart import test_chart
+from chat_te import display_chat_te
 
 def main():
     st.markdown(":point_left: Cliquez pour vous inspirer", unsafe_allow_html=True)
@@ -70,7 +71,8 @@ def main():
             [
                 "Audit flash RSE de vos contenus",
                 "Parties prenantes",
-                "Chatbot RSE"
+                "Chatbot partie prenante",
+                "Chatbot TE",
             ]
         )
 
@@ -87,7 +89,7 @@ def main():
         #     if selected_company:
         #         display_materiality_matrix(selected_company, data, bziiit_data)
         
-        elif ia_mode == "Chatbot RSE":
+        elif ia_mode == "Chatbot partie prenante":
             display_chat()
         
         elif ia_mode == "Audit flash RSE de vos contenus":
@@ -101,8 +103,9 @@ def main():
 
         #     selected_prompt = prompt_execution()
         #     if selected_prompt:
-        #         execute_prompt(selected_prompt)
-
+        #         execute_prompt(selected_prompt) 
+        elif ia_mode == "Chatbot TE":
+            display_chat_te()
 
     elif section_principale == "Documentation":
             display_documentation()

chat_te.py

@@ -10,7 +10,24 @@ from langchain import hub
 from langchain_core.prompts.prompt import PromptTemplate
 from langchain_community.vectorstores import FAISS
 from langchain_community.embeddings import OpenAIEmbeddings
-load_dotenv()  
+from langchain_community.document_loaders import PyPDFLoader
+from langchain_experimental.text_splitter import SemanticChunker
+load_dotenv() 
+
+def get_docs_from_pdf(file):
+    loader = PyPDFLoader(file)
+    docs = loader.load_and_split()
+    return docs
+
+def get_doc_chunks(docs):
+    text_splitter = SemanticChunker(OpenAIEmbeddings())
+    chunks = text_splitter.split_documents(docs)
+    return chunks 
+
+def get_vectorstore_from_docs(doc_chunks):
+    embedding = OpenAIEmbeddings()
+    vectorstore = FAISS.from_documents(documents=doc_chunks, embedding=embedding)
+    return vectorstore
 
 def get_conversation_chain(vectorstore):
     llm = ChatOpenAI(model="gpt-4o",temperature=0.5, max_tokens=2048)
@@ -26,49 +43,44 @@ def get_conversation_chain(vectorstore):
     )
     return rag_chain
 
-def get_response(user_query, chat_history):
+def create_db(file):
+    docs = get_docs_from_pdf(file)
+    doc_chunks = get_doc_chunks(docs)
+    vectorstore = get_vectorstore_from_docs(doc_chunks)
+    return vectorstore
+
+def get_response(chain,user_query, chat_history):
 
     template = """
     Chat history: {chat_history}
     User question: {user_question}
     """
-
-    embeddings = OpenAIEmbeddings()
-    db = FAISS.load_local("vectorstore_op", embeddings)
+    
 
     question = ChatPromptTemplate.from_template(template)
     question = question.format(chat_history=chat_history, user_question=user_query)
 
-    chain = get_conversation_chain(db)
-
     return chain.stream(question)
 
-def display_chart():
-    if "pp_grouped" not in st.session_state or st.session_state['pp_grouped'] is None or len(st.session_state['pp_grouped']) == 0:
-        st.warning("Aucune partie prenante n'a été définie")
-        return None
-    plot = construct_plot()
-    st.plotly_chart(plot)
-
-
-def display_chat():
+def display_chat_te():
     # app config
     st.title("Chatbot")
 
     # session state
-    if "chat_history" not in st.session_state:
-        st.session_state.chat_history = [
-            AIMessage(content="Salut, voici votre cartographie des parties prenantes. Que puis-je faire pour vous?"),
+    if "chat_history_te" not in st.session_state:
+        st.session_state.chat_history_te = [
+            AIMessage(content="Salut, posez-moi vos question sur la transistion ecologique."),
         ]
-
+    if "chain" not in st.session_state:
+        db=create_db("DATA_bziiit/op.pdf")
+        chain = get_conversation_chain(db)
+        st.session_state.chain = chain
         
     # conversation
-    for message in st.session_state.chat_history:
+    for message in st.session_state.chat_history_te:
         if isinstance(message, AIMessage):
             with st.chat_message("AI"):
                 st.write(message.content)
-                if "cartographie des parties prenantes" in message.content:
-                    display_chart()
         elif isinstance(message, HumanMessage):
             with st.chat_message("Moi"):
                 st.write(message.content)
@@ -76,15 +88,12 @@ def display_chat():
     # user input
     user_query = st.chat_input("Par ici...")
     if user_query is not None and user_query != "":
-        st.session_state.chat_history.append(HumanMessage(content=user_query))
+        st.session_state.chat_history_te.append(HumanMessage(content=user_query))
 
         with st.chat_message("Moi"):
             st.markdown(user_query)
 
         with st.chat_message("AI"):
+            response = st.write_stream(get_response(st.session_state.chain,user_query, st.session_state.chat_history_te))
 
-            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'])))
-            if "cartographie des parties prenantes" in message.content:
-                    display_chart()
-
-        st.session_state.chat_history.append(AIMessage(content=response))
+        st.session_state.chat_history_te.append(AIMessage(content=response))

chat_with_pps.py

@@ -68,8 +68,9 @@ def display_chat():
         st.session_state.chat_history = [
             AIMessage(content="Salut, voici votre cartographie des parties prenantes. Que puis-je faire pour vous?"),
         ]
-
-        
+    
+    
+ 
     # conversation
     for message in st.session_state.chat_history:
         if isinstance(message, AIMessage):
@@ -81,6 +82,8 @@ def display_chat():
             with st.chat_message("Moi"):
                 st.write(message.content)
 
+    if "pp_grouped" not in st.session_state or st.session_state['pp_grouped'] is None or len(st.session_state['pp_grouped']) == 0:
+        return None
     # user input
     user_query = st.chat_input("Par ici...")
     if user_query is not None and user_query != "":

partie_prenante_carte.py

@@ -15,7 +15,7 @@ from langchain.llms import HuggingFaceHub
 from langchain import hub
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.runnables import RunnablePassthrough
-from langchain_community.document_loaders import WebBaseLoader,FireCrawlLoader,PDFLoader
+from langchain_community.document_loaders import WebBaseLoader,FireCrawlLoader
 from langchain_core.prompts.prompt import PromptTemplate
 from session import set_partie_prenante
 import os