whatif

main.py

@@ -133,6 +133,7 @@ async def generate(user_input: UserInput):
     except Exception as e:
         return {"message": str(e)}
     
+    
 @app.post("/whatif")
 async def generate_whatif(whatif_input: WhatifInput):
     try:

rag.py

@@ -11,7 +11,6 @@ import random
 from itext2kg.models import KnowledgeGraph
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 
-
 import faiss
 from langchain_community.docstore.in_memory import InMemoryDocstore
 
@@ -27,7 +26,7 @@ import unicodedata
 load_dotenv()
 index_name = os.environ.get("INDEX_NAME")
 # Global initialization
-embedding_model = "text-embedding-3-large"
+embedding_model = "text-embedding-3-small"
 
 embedding = OpenAIEmbeddings(model=embedding_model)
 # vector_store = PineconeVectorStore(index=index_name, embedding=embedding)
@@ -183,7 +182,7 @@ def generate_whatif_stream(question:str,response:str, stream:bool = True) -> str
         context = retrieve_context_from_vectorestore(f"{question} {response}")
         print(f"Context: {context}")
 
-        if generate_stream:
+        if stream:
             return llm_chain.stream({"question":question,"response":response,"context":context})
         else:
             return llm_chain.invoke({"question":question,"response":response,"context":context})