Update main.py

main.py

@@ -59,7 +59,10 @@ vectorstore = PineconeVectorStore(
     index_name=index_name, embedding=embeddings
 )
 retriever = vectorstore.as_retriever(search_type="similarity_score_threshold", search_kwargs={"score_threshold": .7, "k": 150,"filter": {'categorie': {'$eq': 'bibliographie-OPP-DGDIN'}}})
-    
+#search = vectorstore.similarity_search(query,k=50, filter={"categorie": {"$eq": "bibliographie-OPP-DGDIN"}, 'Source': {'$eq': 'Source : Persée'}})    
+search = vectorstore.similarity_search(query,k=50, filter={"categorie": {"$eq": "bibliographie-OPP-DGDIN"}})
+cl.user_session.set("search", search)
+
 @cl.on_chat_start
 async def on_chat_start():
     await cl.Message(f"> REVIEWSTREAM").send()
@@ -163,7 +166,6 @@ async def on_message(message: cl.Message):
                 self.sources.add(source_page_pair)  # Add unique pairs to the set
 
         def on_llm_end(self, response, *, run_id, parent_run_id, **kwargs):
-            if len(self.sources):
                 sources_text = "\n".join([f"{source}#page={page}" for source, page in self.sources])
                 self.msg.elements.append(
                     cl.Text(name="Sources", content=sources_text, display="inline")
@@ -182,6 +184,25 @@ async def on_message(message: cl.Message):
         answer = results["answer"]
 
     await cl.Message(content=answer).send()
+    if cl.user_session.get("search"):
+        test = []
+        sources_text = ""
+        count = 0
+        search = cl.user_session.get("search")
+        for i in range(0,len(search)):
+            if search[i].metadata['Lien'] not in test:
+                if count <= 15:
+                    count = count + 1
+                    test.append(search[i].metadata['Lien'])
+                    sources_text = sources_text + "<a href='" + search[i].metadata['Lien'] + "'>" + search[i].metadata['Titre'] + '</a>, ' + search[i].metadata['Auteurs'] + ', ' + search[i].metadata['Lien'] + "\n"
+    elements = [
+        cl.Text(name="Sources", content=sources_text, display="inline")
+    ]
+
+    await cl.Message(
+        content="Sources : ",
+        elements=elements,
+    ).send()            
     #await msg.send()
     #memory.chat_memory.add_user_message(message.content)
     #memory.chat_memory.add_ai_message(msg.content)