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Don't block on API calls #4

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Merged
merged 4 commits into from
May 18, 2023
Merged

Don't block on API calls #4

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188b4e4
Don't block on API calls
tomdyson May 17, 2023
c5eac45
Version bump
tomdyson May 17, 2023
88e8083
Add OPENAPI_KEY explicitly
tomdyson May 18, 2023
4069d3b
Import OA key
tomdyson May 18, 2023
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2 changes: 1 addition & 1 deletion nldb/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,3 @@
"""talk to your database"""

__version__ = "0.3.8"
__version__ = "0.4.0"
6 changes: 3 additions & 3 deletions nldb/api.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,8 +23,8 @@ def load_prompt_template():
async def ask(q: Union[str, None] = None):
"""Process a text query and return the SQL statement, results, and explanation."""
nldb = NLDB(prompt_template)
sql_statement = nldb.text_to_sql(q)
results, plain_text_results, answer = nldb.sql_to_answer(sql_statement)
sql_statement = await nldb.text_to_sql(q)
results, plain_text_results, answer = await nldb.sql_to_answer(sql_statement)
return {
"response": {
"sql": sql_statement,
Expand Down Expand Up @@ -68,4 +68,4 @@ async def serve_index():


def serve():
uvicorn.run("nldb.api:app", host=UVICORN_HOST, port=UVICORN_PORT, workers=2)
uvicorn.run("nldb.api:app", host=UVICORN_HOST, port=UVICORN_PORT, workers=1)
24 changes: 10 additions & 14 deletions nldb/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,6 @@
import os
import re
import sqlite3
from functools import lru_cache
from inspect import cleandoc
from timeit import default_timer as timer
from typing import Tuple
Expand All @@ -12,7 +11,7 @@
import openai
from tabulate import tabulate

from nldb.config import DATABASE
from nldb.config import DATABASE, OPENAI_API_KEY


class ttimer:
Expand Down Expand Up @@ -53,7 +52,7 @@ def markdown_to_python(markdown_str):
return None


def cache_chat_completion(prompt_messages):
async def cache_chat_completion(prompt_messages):
"""File-based cache for GPT-3.5 chat completions"""
# hash the prompt messages
m = hashlib.sha256()
Expand All @@ -65,10 +64,11 @@ def cache_chat_completion(prompt_messages):
if os.path.exists(cache_file):
return json.loads(open(cache_file).read())
# otherwise, run the completion
resp = openai.ChatCompletion.create(
resp = await openai.ChatCompletion.acreate(
model="gpt-3.5-turbo",
messages=prompt_messages,
temperature=0,
api_key=OPENAI_API_KEY,
)
# save the response to the cache
if not os.path.exists(cache_dir):
Expand All @@ -92,17 +92,15 @@ def get_prompt_template(self) -> str:
uncommented_lines = [line for line in lines if not line.strip().startswith("#")]
return "\n".join(uncommented_lines).strip()

@lru_cache
def text_to_sql(self, question: str) -> str:
async def text_to_sql(self, question: str) -> str:
# uses GPT-3.5 to convert a question into a SQL statement
self.question = question
prompt_messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": self.prompt_template % question},
]
with ttimer() as gpt_timer:
resp = cache_chat_completion(prompt_messages)
print
resp = await cache_chat_completion(prompt_messages)
self.timings.append(gpt_timer.time)
self.tokens += resp["usage"]["total_tokens"]

Expand All @@ -123,8 +121,7 @@ def execute_sql(self, query: str) -> Tuple[list, list]:
connection.close()
return (columns, result)

@lru_cache
def sql_to_answer(self, sql: str) -> Tuple[str, str]:
async def sql_to_answer(self, sql: str) -> Tuple[str, str]:
# executes the SQL statement and asks GPT to explain them
prompt_template = self.prompt_template
question = self.question
Expand Down Expand Up @@ -159,15 +156,14 @@ def sql_to_answer(self, sql: str) -> Tuple[str, str]:
]

with ttimer() as gpt_timer:
resp = cache_chat_completion(prompt_messages)
resp = await cache_chat_completion(prompt_messages)
self.timings.append(gpt_timer.time)

answer = resp["choices"][0]["message"]["content"].strip()
self.tokens += resp["usage"]["total_tokens"]
return (html_results, plain_text_results, answer)

@lru_cache
def results_to_chart(self, question: str, results: str) -> Tuple[str, str]:
async def results_to_chart(self, question: str, results: str) -> Tuple[str, str]:
# uses GPT-3.5 to convert a question and answer into a chart
chart_prompt = f"""Given this question:

Expand Down Expand Up @@ -199,7 +195,7 @@ def results_to_chart(self, question: str, results: str) -> Tuple[str, str]:
},
]
with ttimer() as gpt_timer:
resp = cache_chat_completion(prompt_messages)
resp = await cache_chat_completion(prompt_messages)
self.timings.append(gpt_timer.time)

chart_code = resp["choices"][0]["message"]["content"].strip()
Expand Down