diff --git a/.gitignore b/.gitignore
index 42ba370..ef8e385 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,5 +1,6 @@
 __pycache__/
 venv/
+test_venv/
 .env
 .pytest_cache/
 .vscode
diff --git a/api.py b/api.py
index e8119f1..478167a 100644
--- a/api.py
+++ b/api.py
@@ -230,7 +230,7 @@ async def youtube_video_transcribe_summarizer_gemini(url: str = Form(...)):
             print("Retrieving response from Redis cache")
             return ResponseText(response=cached_response.decode("utf-8"))
 
-        model = genai.GenerativeModel(settings.GEMINI_PRO)
+        model = genai.GenerativeModel(settings.GEMINI_FLASH)
         transcript_text = extract_transcript_details(url)
         response = model.generate_content(settings.youtube_transcribe_prompt + transcript_text)
         redis.set(cache_key, response.text, ex=60)
diff --git a/helper_functions.py b/helper_functions.py
index 2a81eb2..8e11be4 100644
--- a/helper_functions.py
+++ b/helper_functions.py
@@ -93,7 +93,7 @@ def get_qa_chain():
     return chain
 
 def get_url_doc_qa(url,doc):
-    llm = GoogleGenerativeAI(model= settings.GEMINI_PRO, google_api_key=os.getenv("GOOGLE_API_KEY"),temperature=0.3)
+    llm = GoogleGenerativeAI(model= settings.GEMINI_FLASH, google_api_key=os.getenv("GOOGLE_API_KEY"),temperature=0.3)
     if url:
         loader = WebBaseLoader(url)
         data = loader.load()
@@ -135,7 +135,7 @@ def get_gemini_pdf(pdf):
     text_splitter = RecursiveCharacterTextSplitter(chunk_size=10000, chunk_overlap=1000)
     chunks = text_splitter.split_text(text)
     vector_store = FAISS.from_texts(chunks, embedding=google_embedding)
-    llm = GoogleGenerativeAI(model= settings.GEMINI_PRO, google_api_key=os.getenv("GOOGLE_API_KEY"),temperature=0.7)
+    llm = GoogleGenerativeAI(model= settings.GEMINI_FLASH, google_api_key=os.getenv("GOOGLE_API_KEY"),temperature=0.7)
     retriever = vector_store.as_retriever(score_threshold=0.7)
     PROMPT = PromptTemplate(
         template=settings.prompt_pdf, input_variables=["context", "question"]
@@ -188,7 +188,7 @@ def questions_generator(doc):
     # splitter_ans_gen = TokenTextSplitter(chunk_size = 1000,chunk_overlap = 100)
     # document_answer_gen = splitter_ans_gen.split_documents(document_ques_gen)
 
-    llm_ques_gen_pipeline = ChatGoogleGenerativeAI(model= settings.GEMINI_PRO,google_api_key=os.getenv("GOOGLE_API_KEY"),temperature=0.3)
+    llm_ques_gen_pipeline = ChatGoogleGenerativeAI(model= settings.GEMINI_FLASH,google_api_key=os.getenv("GOOGLE_API_KEY"),temperature=0.3)
     PROMPT_QUESTIONS = PromptTemplate(template=settings.question_prompt_template, input_variables=["text"])
     REFINE_PROMPT_QUESTIONS = PromptTemplate(input_variables=["existing_answer", "text"],template=settings.question_refine_template)
     ques_gen_chain = load_summarize_chain(llm = llm_ques_gen_pipeline,