Update app.py

app.py

@@ -42,13 +42,27 @@ Question:
 {question}
 """
 prompt = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
+embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/multi-qa-mpnet-base-dot-v1")
 
-# Carica FAISS dal dataset
-faiss_index_path = hf_hub_download(repo_id="SelmaNajih001/DatasetStockFAISS", filename="index.faiss")
-docstore_path = hf_hub_download(repo_id="SelmaNajih001/DatasetStockFAISS", filename="docstore.json")
 
-embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/multi-qa-mpnet-base-dot-v1")
-vectorstore = FAISS.load_local("faiss_index", embeddings)
+import tempfile
+tmp_dir = tempfile.mkdtemp()
+
+# Scarica i file nella cartella temporanea
+faiss_index_path = hf_hub_download(
+    repo_id="SelmaNajih001/DatasetStockFAISS", 
+    filename="index.faiss",
+    cache_dir=tmp_dir
+)
+docstore_path = hf_hub_download(
+    repo_id="SelmaNajih001/DatasetStockFAISS", 
+    filename="index.pkl",
+    cache_dir=tmp_dir
+)
+
+# Usa la cartella per caricare FAISS
+vectorstore = FAISS.load_local(tmp_dir, embeddings)
+
 def analisi_finanziaria(query, k=4):
     # Recupera i documenti più rilevanti
     docs_found = vectorstore.similarity_search(query, k=k)