Update app.py

app.py

@@ -13,7 +13,7 @@ from haystack.components.generators import OpenAIGenerator
 from haystack.components.builders import PromptBuilder
 from haystack.components.converters import TextFileToDocument
 from haystack.components.preprocessors import DocumentSplitter
-from haystack.utils import Secret # Import the Secret class
+from haystack.utils import Secret
 
 # --- Logging ---
 logging.basicConfig(stream=sys.stdout, level=logging.INFO)
@@ -52,7 +52,7 @@ if not os.path.exists(file_path):
         f.write(r.text)
 
 # --- Haystack Pipeline for Indexing ---
-document_store = PineconeDocumentStore(api_key=Secret.from_env_var("PINECONE_API_KEY"), index=index_name) # Use Secret object
+document_store = PineconeDocumentStore(api_key=Secret.from_env_var("PINECONE_API_KEY"), index=index_name)
 
 indexing_pipeline = Pipeline()
 indexing_pipeline.add_component("converter", TextFileToDocument())
@@ -85,9 +85,9 @@ query_pipeline = Pipeline()
 query_pipeline.add_component("embedder", OpenAITextEmbedder())
 query_pipeline.add_component("retriever", PineconeEmbeddingRetriever(document_store=document_store))
 query_pipeline.add_component("prompt_builder", PromptBuilder(template=template))
-query_pipeline.add_component("llm", OpenAIGenerator(api_key=Secret.from_env_var("OPENAI_API_KEY"))) # Use Secret object
+query_pipeline.add_component("llm", OpenAIGenerator(api_key=Secret.from_env_var("OPENAI_API_KEY")))
 
-query_pipeline.connect("embedder.query", "retriever.query")
+query_pipeline.connect("embedder.embedding", "retriever.query_embedding") # Corrected connection
 query_pipeline.connect("retriever.documents", "prompt_builder.documents")
 query_pipeline.connect("prompt_builder", "llm")