Upload Venkat.py

Venkat.py

@@ -197,7 +197,7 @@ def rag(domain: str, question: str):
     print(db_exists)
     # if db_exists:
     embeddings = _load_embeddings_from_db(db_exists, domain)
-    extractor = Extractor(embeddings)
+    extractor = Extractor(similarity=embeddings, path="google/flan-t5-large")
     # llm = HuggingFaceHub(
     #     repo_id="google/flan-t5-xxl",
     #     model_kwargs={"temperature": 1, "max_length": 1000000},
@@ -213,6 +213,6 @@ load embedding and models for extractor during start up
 '''
 
 # Create extractor instance
-extractor = Extractor(path="google/flan-t5-base")
+#extractor = Extractor(path="google/flan-t5-large")
 #extractor = Extractor(embeddings, "TheBloke/Llama-2-7B-GGUF")
 #extractor = Extractor(embeddings, "google/flan-t5-xl")