recursive calls if not json parsable

- makes recursive calls to API (with a comment about it not being parsable) if response was not parsable
- pass prompt.txt as system prompt
- use env var for `DEFAULT_MODEL`
- use env var for OPENAI_API_KEY
pull/13/head
Felix Boehme 2023-04-13 11:29:06 -04:00
rodzic 7c072fba2a
commit 0656a83da7
1 zmienionych plików z 74 dodań i 29 usunięć

Wyświetl plik

@ -1,18 +1,27 @@
import difflib
import fire
import json
import os
import shutil
import subprocess
import sys
import openai
import fire
from dotenv import load_dotenv
from termcolor import cprint
from dotenv import load_dotenv
# Set up the OpenAI API
load_dotenv()
openai.api_key = os.getenv("OPENAI_API_KEY")
import openai
openai.api_key = os.environ.get("OPENAI_API_KEY")
DEFAULT_MODEL = os.environ.get("DEFAULT_MODEL", "gpt-4")
with open("prompt.txt") as f:
SYSTEM_PROMPT = f.read()
def run_script(script_name, script_args):
@ -26,7 +35,47 @@ def run_script(script_name, script_args):
return result.decode("utf-8"), 0
def send_error_to_gpt(file_path, args, error_message, model):
def send_error_to_gpt(file_path, args, error_message, model=DEFAULT_MODEL):
def json_validated_response(model, messages):
"""
This function is needed because the API can return a non-json response.
This will run recursively until a valid json response is returned.
"""
response = openai.ChatCompletion.create(
model=model,
messages=messages,
temperature=0.5,
)
messages.append(response.choices[0].message)
content = response.choices[0].message.content
# see if json can be parsed
try:
json_start_index = content.index(
"["
) # find the starting position of the JSON data
json_data = content[
json_start_index:
] # extract the JSON data from the response string
json_response = json.loads(json_data)
except (json.decoder.JSONDecodeError, ValueError) as e:
cprint(f"{e}. Re-running the query.", "red")
# debug
cprint(f"\n\GPT RESPONSE:\n\n{content}\n\n", "yellow")
# append a user message that says the json is invalid
messages.append(
{
"role": "user",
"content": "Your response could not be parsed by json.loads. Please restate your last message as pure JSON.",
}
)
# rerun the api call
return json_validated_response(model, messages)
except Exception as e:
cprint(f"Unknown error: {e}", "red")
cprint(f"\n\GPT RESPONSE:\n\n{content}\n\n", "yellow")
raise e
return json_response
with open(file_path, "r") as f:
file_lines = f.readlines()
@ -35,12 +84,7 @@ def send_error_to_gpt(file_path, args, error_message, model):
file_with_lines.append(str(i + 1) + ": " + line)
file_with_lines = "".join(file_with_lines)
with open("prompt.txt") as f:
initial_prompt_text = f.read()
prompt = (
initial_prompt_text +
"\n\n"
"Here is the script that needs fixing:\n\n"
f"{file_with_lines}\n\n"
"Here are the arguments it was provided:\n\n"
@ -52,26 +96,27 @@ def send_error_to_gpt(file_path, args, error_message, model):
)
# print(prompt)
response = openai.ChatCompletion.create(
model=model,
messages=[
{
"role": "user",
"content": prompt,
}
],
temperature=1.0,
)
messages = [
{
"role": "system",
"content": SYSTEM_PROMPT,
},
{
"role": "user",
"content": prompt,
},
]
return response.choices[0].message.content.strip()
return json_validated_response(model, messages)
def apply_changes(file_path, changes_json):
def apply_changes(file_path, changes: list):
"""
Pass changes as loaded json (list of dicts)
"""
with open(file_path, "r") as f:
original_file_lines = f.readlines()
changes = json.loads(changes_json)
# Filter out explanation elements
operation_changes = [change for change in changes if "operation" in change]
explanations = [
@ -114,7 +159,7 @@ def apply_changes(file_path, changes_json):
print(line, end="")
def main(script_name, *script_args, revert=False, model="gpt-4"):
def main(script_name, *script_args, revert=False, model=DEFAULT_MODEL):
if revert:
backup_file = script_name + ".bak"
if os.path.exists(backup_file):
@ -140,11 +185,11 @@ def main(script_name, *script_args, revert=False, model="gpt-4"):
print("Output:", output)
json_response = send_error_to_gpt(
file_path=script_name,
args=script_args,
error_message=output,
model=model,
file_path=script_name,
args=script_args,
error_message=output,
)
apply_changes(script_name, json_response)
cprint("Changes applied. Rerunning...", "blue")