Include PDF generation

app.py

@@ -1,12 +1,12 @@
 import streamlit as st
 import os
+import base64
 
 from dotenv import load_dotenv
 from rag import Rag
-from vectore_store.PineconeConnector import PineconeConnector
-from vectore_store.VectoreStoreManager import VectoreStoreManager
 
 from util import getYamlConfig
+from utils.document import generate_pdf
 
 load_dotenv()
 
@@ -35,10 +35,11 @@ def init_app():
 
         for chapter in st.session_state["chapters"]:
             st.session_state[f"chapter_{chapter['num']}"] = {
+                "title": chapter['name'],
                 "num": chapter['num'],
                 "messages": [],
                 "prompt_system": chapter['prompt_system'],
-                "prompt": chapter['prompts'],
+                "prompts": chapter['prompts'],
             }
             
 
@@ -86,6 +87,22 @@ def main():
         }
     )
 
+    if st.sidebar.button("Générer le PDF"):
+
+        chapters = []
+
+        for chapter in st.session_state["chapters"]:
+            chapters.append(st.session_state[f"chapter_{chapter['num']}"])
+
+        pdf_buffer = generate_pdf(chapters)
+
+        st.sidebar.download_button(
+            label="📥 Télécharger le PDF",
+            data=pdf_buffer,
+            file_name="diagnostique_CEGARA.pdf",
+            mime="application/pdf"
+        )
+
     st.sidebar.markdown("### Documentation")
     st.sidebar.markdown("*Documentation :* [*Lien*]({})".format("https://docs.google.com/presentation/d/1b-cnCKge1qRBS26U5FfMScQPco4gZTn7tN1idhccsso/edit?usp=sharing"))
     st.sidebar.markdown("*Evaluation App. IA :*")

pages/chatbot.py

@@ -23,7 +23,7 @@ def display_messages():
                 model = message.kwargs.get("model", "Unknown Model")  # Get the model, default to "Unknown Model"
                 st.write(f"**Model :** {model}")
                 st.markdown(message.content)
-                st_copy_to_clipboard(message.content,key=f"message_{chapter_num}_{i}")
+                st_copy_to_clipboard(message.content,key=f"message_{chapter_num}_{i}_{uuid.uuid4()}")
         
         elif isinstance(message, HumanMessage):
             with st.chat_message("Moi"):
@@ -54,13 +54,15 @@ def show_prompts(prompts: list[str]):
     expander = st.expander("Prompts pré-définis")
 
     for i, p in enumerate(prompts):
-        if expander.button(p, key=f"button_{chapter_num}_{i}"):
+        if expander.button(p, key=f"button_{chapter_num}_{i}_{uuid.uuid4()}"):
             launchQuery(p)
 
 
 def page():
-    yaml_data = getYamlConfig()["chapters"]
-    
+
+    chapters = []
+    for chapter in st.session_state["chapters"]:
+        chapters.append(st.session_state[f"chapter_{chapter['num']}"])
 
     ###############################################
     # Récupération du chapitre depuis YAML Config #
@@ -72,7 +74,7 @@ def page():
     
     setChapter(int(chapter_num))
     
-    chapter = next((ch for ch in yaml_data if ch['num'] == chapter_num), None)
+    chapter = next((ch for ch in chapters if ch['num'] == chapter_num), None)
     if not chapter:
         st.text("Chapitre non trouvé")
         return
@@ -88,7 +90,7 @@ def page():
     if "messages" not in st.session_state[chapter_session_key]:
         st.session_state[chapter_session_key]["messages"] = [ ]
 
-    if len(st.session_state[chapter_session_key]["messages"]) == 0 :
+    if len(st.session_state[chapter_session_key]["messages"]) < 2 :
         st.session_state[chapter_session_key]["messages"] = [ SystemMessage(content=chapter["prompt_system"]) ]
 
 
@@ -96,7 +98,7 @@ def page():
     #### UI ####
     ############
 
-    st.subheader(chapter['name'])
+    st.subheader(chapter['title'])
 
     st.markdown("<style>iframe{height:50px;}</style>", unsafe_allow_html=True)
 
@@ -110,8 +112,9 @@ def page():
     display_messages()
 
 
-    user_query = st.chat_input("", key=str(uuid.uuid4()))
+    user_query = st.chat_input("", key=f"input_{chapter_session_key}")
     
+    print(f"submission : {user_query}")
     if user_query is not None and user_query != "":
         print(user_query)
 

requirements.txt

@@ -19,6 +19,7 @@ langchain_anthropic
 llamaapi
 pyyaml
 st_copy_to_clipboard
-faiss-gpu
+# faiss-gpu
 faiss-cpu
-tiktoken
+tiktoken
+reportlab

utils/document.py

@@ -1,6 +1,12 @@
 import pymupdf
 import tiktoken
 
+from io import BytesIO
+from reportlab.lib.pagesizes import A4
+from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
+from reportlab.lib.styles import getSampleStyleSheet
+from reportlab.lib.enums import TA_CENTER
+from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
 
 def count_tokens(input_string: str) -> int:
     tokenizer = tiktoken.get_encoding("cl100k_base")
@@ -106,3 +112,53 @@ def audit_descriptif_pdf(file,max_img_width=500) -> dict:
     }
 
     return global_audit
+
+
+def generate_pdf(chapter_data: list):
+    buffer = BytesIO()
+    doc = SimpleDocTemplate(buffer, pagesize=A4)
+
+    styles = getSampleStyleSheet()
+    style_title = styles["Title"]
+    style_title.alignment = TA_CENTER  # Centrer le titre
+    style_header = styles["Heading2"]
+    style_message = styles["BodyText"]
+
+    elements = []
+
+    # Titre principal du document
+    elements.append(Paragraph("Conseiller augmenté CEGARA", style_title))
+    elements.append(Spacer(1, 20))  # Espacement après le titre
+
+    # Trier les chapitres par "num"
+    chapters = sorted(chapter_data, key=lambda x: x["num"])
+
+    for chapter in chapters:
+        # Ajouter le titre de la discussion
+        elements.append(Paragraph(f"Chapitre {chapter['num']}: {chapter['title']}", style_header))
+        elements.append(Spacer(1, 10))
+
+        if len(chapter["messages"]) > 1 :
+            for msg in chapter["messages"]:
+                if isinstance(msg, HumanMessage):
+                    color = "blue"
+                    sender = "👤 Utilisateur"
+                elif isinstance(msg, AIMessage):
+                    color = "green"
+                    sender = "🤖 IA"
+                elif isinstance(msg, SystemMessage):
+                    color = "red"
+                    sender = "⚙️ Système"
+                else:
+                    color = "black"
+                    sender = "🔹 Message"
+
+                print(msg.content)
+                elements.append(Paragraph(f"<b><font color='{color}'>{sender} :</font></b> {msg.content}", style_message))
+                elements.append(Spacer(1, 5))
+
+        elements.append(Spacer(1, 15))  # Espacement entre discussions
+
+    doc.build(elements)
+    buffer.seek(0)
+    return buffer