Update app.py

app.py

@@ -6,7 +6,6 @@ os.environ["OPENAI_API_KEY"] = st.secrets['OPENAI_API_KEY']  # agregada en la co
 os.environ["LANGCHAIN_TRACING_V2"] = "true"
 os.environ["LANGCHAIN_API_KEY"] = st.secrets['OPENAI_API_KEY']
 
-from transformers import pipeline
 from langchain.prompts import PromptTemplate
 from langchain.chains.llm import LLMChain
 from langchain.chains.combine_documents.stuff import StuffDocumentsChain
@@ -44,7 +43,7 @@ with st.status("Cargando Aplicación...", expanded=False) as status:
 
     st.write("Base de datos FAISS...")
     #DB y retriever
-    db = FAISS.from_documents(docs, embeddings)  # Create a retriever object from the 'db' with a search configuration where it retrieves up to 4 relevant splits/documents.
+    db = FAISS.from_documents(docs[:2], embeddings)  # Create a retriever object from the 'db' with a search configuration where it retrieves up to 4 relevant splits/documents.
 
     st.write("Retriever...")
     retriever = db.as_retriever(search_kwargs={"k": 3})
@@ -86,10 +85,9 @@ with st.status("Cargando Aplicación...", expanded=False) as status:
     status.update(label="Finalizado!", state="complete")
     
 def main(): 
-    pipe = pipeline('sentiment-analysis')
-    text = st.text_area('Ingrese su pregunta')
-    if text:
-        out = pipe(text)
+    pregunta = st.text_area('Ingrese su pregunta')
+    if pregunta:
+        out = chain.invoke(str(pregunta))
         st.write(out)
 
 if __name__ == "__main__":