kopia lustrzana https://github.com/biobootloader/wolverine
Merge pull request #35 from nervousapps/patch-1
Add VALIDATE_JSON_RETRY environment variable, and testsclean-reqs
biobootloader
GitHub
commit
756ddbdd61
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@ -37,6 +37,13 @@ You can also use flag `--confirm=True` which will ask you `yes or no` before mak
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python -m wolverine examples/buggy_script.py "subtract" 20 3 --confirm=True
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## :label: Environement variables
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| env name | description | default value |
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| -------------------------------| ----------------| -------------------|
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| OPENAI_API_KEY | OpenAI API key | None |
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| DEFAULT_MODEL | GPT model to use | "gpt-4" |
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| VALIDATE_JSON_RETRY | Number of retries when requesting OpenAI API (-1 means unlimites) | -1 |
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## Future Plans
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This is just a quick prototype I threw together in a few hours. There are many possible extensions and contributions are welcome:
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@ -14,3 +14,5 @@ example response:
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{"operation": "Replace", "line": 18, "content": " x += 1"},
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{"operation": "Delete", "line": 20, "content": ""}
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]
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From now, your response must be only the json object, no talking, no comments.
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@ -0,0 +1,31 @@
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"""
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Conftest
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"""
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import os
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import pytest
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import tempfile
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TEST_FILES_DIR = os.path.join(os.path.dirname(__file__), "test_files")
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@pytest.fixture(scope='function')
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def temp_file():
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# Create a temporary file
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with tempfile.NamedTemporaryFile(mode="w", delete=False) as f:
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f.write("first line\nsecond line\nthird line")
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file_path = f.name
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yield file_path
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# Clean up the temporary file
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os.remove(file_path)
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def mock_open_ai_response_object(mocker, content: str):
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"""
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Mocks the response object from the openai api.
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"""
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mock_generator_object = mocker.MagicMock()
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mock_message_object = mocker.MagicMock()
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mock_message_object.configure_mock(**{"message.content": content})
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mock_generator_object.configure_mock(**{"choices": [mock_message_object]})
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return mock_generator_object
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@ -0,0 +1,8 @@
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Explanation: The function `subtract_numbers` is never defined in the script, causing a `NameError` when it is called in the `calculate` function.
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[
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{"explanation": "The 'subtract_numbers' function is never defined in the script."},
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{"operation": "InsertAfter", "line": 12, "content": "\n# Define subtract_numbers function\ndef subtract_numbers(a, b):\n return a - b\n"},
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{"operation": "Replace", "line": 18, "content": " if operation == \"add\":\n result = add_numbers(num1, num2)\n elif operation == \"subtract\":\n result = subtract_numbers(num1, num2)\n elif operation == \"multiply\":\n result = multiply_numbers(num1, num2)\n elif operation == \"divide\":\n result = divide_numbers(num1, num2)\n else:\n print(\"Invalid operation\")\n"},
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{"operation": "Replace", "line": 30, "content": " return result\n"}
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]
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@ -0,0 +1,7 @@
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Explanation: The function `subtract_numbers` is never defined in the script, causing a `NameError` when it is called in the `calculate` function.
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[
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{"explanation": "The 'subtract_numbers' function is never defined in the script."},
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{"operation": "InsertAfter", "line": 12, "content": "\n# Define subtract_numbers function\ndef subtract_numbers(a, b):\n return a - b\n"},
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{"operation": "Replace", "line": 18, "content": " if operation == \"add\":\n result = add_numbers(num1, num2)\n elif operation == \"subtract\":\n result = subtract_numbers(num1, num2)\n elif operation == \"multiply\":\n result = multiply_numbers(num1, num2)\n elif operation == \"divide\":\n result = divide_numbers(num1, num2)\n else:\n print(\"Invalid operation\")\n"},
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{"operation": "Replace", "line": 30, "content": " return result\n"}
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@ -1,18 +1,12 @@
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import os
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import pytest
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import tempfile
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from wolverine import apply_changes
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from wolverine import apply_changes, json_validated_response
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@pytest.fixture(scope='function')
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def temp_file():
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# Create a temporary file
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with tempfile.NamedTemporaryFile(mode="w", delete=False) as f:
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f.write("first line\nsecond line\nthird line")
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file_path = f.name
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yield file_path
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# Clean up the temporary file
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os.remove(file_path)
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from .conftest import (
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mock_open_ai_response_object,
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TEST_FILES_DIR
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)
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def test_apply_changes_replace(temp_file):
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@ -53,3 +47,40 @@ def test_apply_changes_insert(temp_file):
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content = f.read()
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assert content == 'first line\nsecond line\ninserted line\nthird line'
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@pytest.mark.parametrize("chat_completion_response, nb_retry, fail", [
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(os.path.join(TEST_FILES_DIR, "cc_resp.txt"), 3, False),
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(os.path.join(TEST_FILES_DIR, "cc_resp_fail.txt"), 3, True),
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(os.path.join(TEST_FILES_DIR, "cc_resp_fail.txt"), 10, True),
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])
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def test_json_validated_response(mocker, chat_completion_response, nb_retry, fail):
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# Open the test file
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with open(chat_completion_response, 'r') as file:
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response = file.read()
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# Mock the openAi chat completion API call
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mocker.patch(
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"openai.ChatCompletion.create",
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return_value=mock_open_ai_response_object(mocker=mocker, content=response))
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# ChatCompletion returned an invalid response
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if fail:
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with pytest.raises(Exception) as err:
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json_response = json_validated_response("gpt-4", [
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{
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"role": "user",
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"content": "prompt"
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}
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],
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nb_retry=nb_retry
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)
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# Check that the exception is raised after nb_retry time
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assert err.value == f"No valid json response found after 3 tries. Exiting."
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else:
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json_response = json_validated_response("gpt-4", [
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{
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"role": "user",
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"content": "prompt"
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}
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],
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nb_retry=nb_retry
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)
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assert json_response
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@ -6,6 +6,9 @@ import subprocess
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import sys
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import openai
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from typing import List, Dict
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from termcolor import cprint
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from dotenv import load_dotenv
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from termcolor import cprint
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@ -13,14 +16,18 @@ from termcolor import cprint
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load_dotenv()
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openai.api_key = os.getenv("OPENAI_API_KEY")
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# Default model is GPT-4
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DEFAULT_MODEL = os.environ.get("DEFAULT_MODEL", "gpt-4")
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# Nb retries for json_validated_response, default to -1, infinite
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VALIDATE_JSON_RETRY = int(os.getenv("VALIDATE_JSON_RETRY", -1))
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with open("prompt.txt", encoding="utf-8") as file:
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SYSTEM_PROMPT = file.read()
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# Read the system prompt
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with open(os.path.join(os.path.dirname(__file__), "..", "prompt.txt"), 'r') as f:
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SYSTEM_PROMPT = f.read()
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def run_script(script_name, script_args):
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def run_script(script_name: str, script_args: List) -> str:
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"""
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If script_name.endswith(".py") then run with python
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else run with node
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@ -42,53 +49,55 @@ def run_script(script_name, script_args):
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return result.decode("utf-8"), 0
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def json_validated_response(model, messages):
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def json_validated_response(model: str, messages: List[Dict], nb_retry: int = VALIDATE_JSON_RETRY) -> Dict:
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"""
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This function is needed because the API can return a non-json response.
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This will run recursively until a valid json response is returned.
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todo: might want to stop after a certain number of retries
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This will run recursively VALIDATE_JSON_RETRY times.
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If VALIDATE_JSON_RETRY is -1, it will run recursively until a valid json response is returned.
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"""
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response = openai.ChatCompletion.create(
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model=model,
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messages=messages,
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temperature=0.5,
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)
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messages.append(response.choices[0].message)
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content = response.choices[0].message.content
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# see if json can be parsed
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try:
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json_start_index = content.index(
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"["
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) # find the starting position of the JSON data
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json_data = content[
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json_start_index:
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] # extract the JSON data from the response string
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json_response = json.loads(json_data)
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except (json.decoder.JSONDecodeError, ValueError) as error:
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cprint(f"{error}. Re-running the query.", "red")
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# debug
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cprint(f"\nGPT RESPONSE:\n\n{content}\n\n", "yellow")
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# append a user message that says the json is invalid
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messages.append(
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{
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"role": "user",
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"content": (
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"Your response could not be parsed by json.loads. "
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"Please restate your last message as pure JSON."
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),
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}
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json_response = {}
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if nb_retry != 0:
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response = openai.ChatCompletion.create(
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model=model,
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messages=messages,
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temperature=0.5,
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)
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# rerun the api call
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return json_validated_response(model, messages)
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except Exception as error:
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cprint(f"Unknown error: {error}", "red")
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cprint(f"\nGPT RESPONSE:\n\n{content}\n\n", "yellow")
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raise error
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return json_response
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messages.append(response.choices[0].message)
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content = response.choices[0].message.content
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# see if json can be parsed
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try:
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json_start_index = content.index(
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"["
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) # find the starting position of the JSON data
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json_data = content[
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json_start_index:
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] # extract the JSON data from the response string
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json_response = json.loads(json_data)
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return json_response
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except (json.decoder.JSONDecodeError, ValueError) as e:
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cprint(f"{e}. Re-running the query.", "red")
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# debug
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cprint(f"\nGPT RESPONSE:\n\n{content}\n\n", "yellow")
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# append a user message that says the json is invalid
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messages.append(
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{
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"role": "user",
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"content": "Your response could not be parsed by json.loads. Please restate your last message as pure JSON.",
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}
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)
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# dec nb_retry
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nb_retry-=1
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# rerun the api call
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return json_validated_response(model, messages, nb_retry)
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except Exception as e:
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cprint(f"Unknown error: {e}", "red")
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cprint(f"\nGPT RESPONSE:\n\n{content}\n\n", "yellow")
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raise e
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raise Exception(f"No valid json response found after {VALIDATE_JSON_RETRY} tries. Exiting.")
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def send_error_to_gpt(file_path, args, error_message, model=DEFAULT_MODEL):
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with open(file_path) as f:
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def send_error_to_gpt(file_path: str, args: List, error_message: str, model: str = DEFAULT_MODEL) -> Dict:
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with open(file_path, "r") as f:
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file_lines = f.readlines()
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file_with_lines = []
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@ -122,7 +131,7 @@ def send_error_to_gpt(file_path, args, error_message, model=DEFAULT_MODEL):
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return json_validated_response(model, messages)
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def apply_changes(file_path, changes: list, confirm=False):
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def apply_changes(file_path: str, changes: List, confirm: bool = False):
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"""
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Pass changes as loaded json (list of dicts)
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"""
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