promtp

app.py

@@ -10,6 +10,7 @@ from langchain_community.cross_encoders import HuggingFaceCrossEncoder
 from langchain_community.vectorstores import FAISS
 from langchain.retrievers import ContextualCompressionRetriever
 from langchain.retrievers.document_compressors import CrossEncoderReranker
+from langchain.prompts import PromptTemplate
 from langchain.chains import RetrievalQA
 from transformers import pipeline
 
@@ -21,6 +22,21 @@ login(os.environ["HF_TOKEN"])
 # Inicialización del sistema
 # -----------------------------
 
+QA_PROMPT = PromptTemplate(
+    template="""Answer the following question in a short and concise way,
+using only the information from the context below.
+If you don’t know the answer, just say "I don’t know".
+
+Context:
+{context}
+
+Question:
+{question}
+
+Concise Answer:""",
+    input_variables=["context", "question"],
+)
+
 # 1. Cargar documentos PDF
 pdfs = ["ejemplo2.pdf"]
 docs = []
@@ -59,7 +75,8 @@ llm = HuggingFacePipeline(pipeline=generator)
 qa_chain = RetrievalQA.from_chain_type(
     llm=llm,
     retriever=compression_retriever,
-    return_source_documents=True
+    return_source_documents=True,
+    chain_type_kwargs={"prompt": QA_PROMPT}
 )
 
 # -----------------------------