diff --git a/01_text_to_sql_pipeline_vLLM_llama.py b/01_text_to_sql_pipeline_vLLM_llama.py
index 0d0d60f..ccb0a56 100644
--- a/01_text_to_sql_pipeline_vLLM_llama.py
+++ b/01_text_to_sql_pipeline_vLLM_llama.py
@@ -131,11 +131,6 @@ def extract_sql_query(self, response_object):
                 return value
         return None
 
-    def handle_streaming_response(self, response_gen):
-        final_response = ""
-        for chunk in response_gen:
-            final_response += chunk
-        return final_response
 
     def pipe(self, user_message: str, model_id: str, messages: List[dict], body: dict) -> Union[str, Generator, Iterator]:
         # Use the established psycopg2 connection to create a SQLAlchemy engine
@@ -199,54 +194,22 @@ def pipe(self, user_message: str, model_id: str, messages: List[dict], body: dic
         
         Question: {query_str}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
         """
-        
-        
-        
-        synthesis_prompt = """
-        <|begin_of_text|><|start_header_id|>system<|end_header_id|>    
-        You are a helpful AI Assistant synthesizing the response from a PostgreSQL query.
-        Make sure to always use the stop token you were trained on at the end of a response: <|eot_id|>
-        
-        You are required to use the following format, each taking one line:
-        <|start_header_id|>user<|end_header_id|>
-        
-        SQLResponse: 
-        
-        
-        
-        ******** edit this *********
-        
-        
-        
-        Only use tables listed below.
-        movies
-        
-        Only use columns listed below.
-        [('Release Year',), ('title',), ('Origin/Ethnicity',), ('director',), ('Cast',), ('genre',), ('Wiki Page',), ('plot',)]
-        
-        Question: How many rows in the database?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
-        
-        SQLQuery: SELECT COUNT(*) FROM "movies"<|eot_id|>
-        
-        <|start_header_id|>user<|end_header_id|>
-        Only use tables listed below.
-        movies
-        
-        Only use columns listed below.
-        [('Release Year',), ('title',), ('Origin/Ethnicity',), ('director',), ('Cast',), ('genre',), ('Wiki Page',), ('plot',)]
-        
-        Question: How many comedy movies in 1995?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
-        
-        SQLQuery: SELECT COUNT(*) FROM "movies" WHERE "Release Year" = 1995 AND "genre" = 'comedy'<|start_header_id|>user<|end_header_id|>
-        
-        Only use tables listed below.
-        movies
-        
-        Only use columns listed below.
-        [('Release Year',), ('title',), ('Origin/Ethnicity',), ('director',), ('Cast',), ('genre',), ('Wiki Page',), ('plot',)]
-        
-        Question: {query_str}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
-        """
+
+        response_synthesis_prompt_str = (
+            "<|begin_of_text|><|start_header_id|>system<|end_header_id|>"
+            "Given an input question, synthesize a response from the SQL Response results.\n"
+            "Also provide full received SQL query in your response.\n"
+            "Format SQL query with: ```sql <sql query>```"
+            "Answer in the language in which you were asked the question.\n"
+            "Question: {query_str}\n"
+            "SQL query: {sql_query}\n"
+            "SQL Response: {context_str}\n"
+            "Answer: <|eot_id|><|start_header_id|>assistant<|end_header_id|>"
+        )
+
+        response_synthesis_prompt = PromptTemplate(
+            response_synthesis_prompt_str,
+        )
 
         text_to_sql_template = PromptTemplate(text_to_sql_prompt)
 
@@ -257,35 +220,39 @@ def pipe(self, user_message: str, model_id: str, messages: List[dict], body: dic
             embed_model="local",
             text_to_sql_prompt=text_to_sql_template,
             synthesize_response=False,
-            #response_synthesis_prompt=synthesis_prompt,
+            #response_synthesis_prompt=response_synthesis_prompt,
             streaming=True
         )
 
         try:
             response = query_engine.query(user_message)
             sql_query = self.extract_sql_query(response.metadata)
+
             if hasattr(response, 'response_gen'):
-                final_response = self.handle_streaming_response(response.response_gen)
-                result = f"Generated SQL Query:\n```sql\n{sql_query}\n```\nResponse:\n{final_response}"
                 self.engine.dispose()
-                return result
+                return response.response_gen
+            
             else:
                 final_response = response.response
                 result = f"Generated SQL Query:\n```sql\n{sql_query}\n```\nResponse:\n{final_response}"
                 self.engine.dispose()
                 return result
+            
         except aiohttp.ClientResponseError as e:
             logging.error(f"ClientResponseError: {e}")
             self.engine.dispose()
             return f"ClientResponseError: {e}"
+        
         except aiohttp.ClientPayloadError as e:
             logging.error(f"ClientPayloadError: {e}")
             self.engine.dispose()
             return f"ClientPayloadError: {e}"
+        
         except aiohttp.ClientConnectionError as e:
             logging.error(f"ClientConnectionError: {e}")
             self.engine.dispose()
             return f"ClientConnectionError: {e}"
+        
         except Exception as e:
             logging.error(f"Unexpected error: {e}")
             self.engine.dispose()