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import os
from langchain import OpenAI
from langchain.chat_models import ChatOpenAI
def get_sql_index_tool(sql_index, table_context_dict):
table_context_str = "\n".join(table_context_dict.values())
def run_sql_index_query(query_text):
try:
response = sql_index.as_query_engine(synthesize_response=False).query(query_text)
except Exception as e:
return f"Error running SQL {e}.\nNot able to retrieve answer."
text = str(response)
sql = response.extra_info["sql_query"]
return f"Here are the details on the SQL table: {table_context_str}\nSQL Query Used: {sql}\nSQL Result: {text}\n"
# return f"SQL Query Used: {sql}\nSQL Result: {text}\n"
return run_sql_index_query
def get_llm(llm_name, model_temperature, api_key):
os.environ["OPENAI_API_KEY"] = api_key
if llm_name == "text-davinci-003":
return OpenAI(temperature=model_temperature, model_name=llm_name)
else:
return ChatOpenAI(temperature=model_temperature, model_name=llm_name)
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