Fix pending UI blocking calls

app.toml

@@ -5,7 +5,7 @@ Description = "QnA with tabular data using NLQ"
 LongDescription = "about.md"
 InstanceLifecycle = "MANAGED"
 Tags = ["DATA_SCIENCE", "MACHINE_LEARNING", "NLP", "GENERATIVE_AI"]
-Version = "0.2.3"
+Version = "0.2.4"
 
 [Runtime]
 MemoryLimit = "64Gi"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "sql-sidekick"
-version = "0.2.3"
+version = "0.2.4"
 license = "Apache-2.0 license"
 description = "An AI assistant for SQL generation"
 authors = [

sidekick/prompter.py

@@ -24,7 +24,7 @@
  execute_query_pd, extract_table_names,
  generate_suggestions, save_query, setup_dir)
 
-__version__ = "0.2.3"
+__version__ = "0.2.4"
 
 # Load the config file and initialize required paths
 app_base_path = (Path(__file__).parent / "../").resolve()

sidekick/utils.py

@@ -629,7 +629,7 @@ def check_vulnerability(input_query: str):
 
 
 def generate_suggestions(remote_url, client_key:str, column_names: list, n_qs: int=10):
- results = []
+ text_completion = []
 
  column_info = ','.join(column_names)
  _system_prompt = f"Act as a data analyst, based on below data schema help answer the question"
@@ -640,12 +640,13 @@ def generate_suggestions(remote_url, client_key:str, column_names: list, n_qs: i
  if "h2ogpt-" in recommender_model:
  try:
  client = H2OGPTE(address=remote_url, api_key=client_key)
- text_completion = client.answer_question(
+ response = client.answer_question(
  system_prompt=_system_prompt,
  text_context_list=[],
  question=_user_prompt,
  llm=recommender_model
  )
+ text_completion = response.content.split("\n")[2:]
  except Exception as e:
  remote_url = os.getenv("H2OGPT_BASE_URL", None)
  client_key = os.getenv("H2OGPT_BASE_API_TOKEN", None)
@@ -660,7 +661,7 @@ def generate_suggestions(remote_url, client_key:str, column_names: list, n_qs: i
  max_tokens=512,
  temperature=0.5,
  seed=42)
- text_completion = completion.choices[0].message
+ text_completion = completion.choices[0].message.content.split("\n")[2:]
  elif 'gpt-3.5' in recommender_model.lower() or 'gpt-4' in recommender_model.lower():
  # Check if the API key is set, else inform user
  logger.info(f"Using OpenAI model: {recommender_model}")
@@ -674,9 +675,8 @@ def generate_suggestions(remote_url, client_key:str, column_names: list, n_qs: i
  seed=42,
  temperature=0.7
  )
- text_completion = completion.choices[0].message
+ text_completion = completion.choices[0].message.content.split("\n")
  else:
  raise Exception("Model url or key is missing.")
- _res = text_completion.content.split("\n")[2:]
- results = "\n".join(_res)
+ results = "\n".join(text_completion)
  return results