forked from smol-ai/developer
-
Notifications
You must be signed in to change notification settings - Fork 0
/
debugger.py
83 lines (66 loc) · 2.96 KB
/
debugger.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
import modal
import os
from constants import DEFAULT_DIR, DEFAULT_MODEL, DEFAULT_MAX_TOKENS, EXTENSION_TO_SKIP
stub = modal.Stub("smol-debugger-v1")
openai_image = modal.Image.debian_slim().pip_install("openai")
def read_file(filename):
with open(filename, 'r') as file:
return file.read()
def walk_directory(directory):
code_contents = {}
for dirpath, _, filenames in os.walk(directory):
for filename in filenames:
if not any(filename.endswith(ext) for ext in EXTENSION_TO_SKIP):
try:
relative_filepath = os.path.relpath(os.path.join(dirpath, filename), directory)
code_contents[relative_filepath] = read_file(os.path.join(dirpath, filename))
except Exception as e:
code_contents[relative_filepath] = f"Error reading file {filename}: {str(e)}"
return code_contents
@stub.local_entrypoint()
def main(prompt, directory=DEFAULT_DIR, model="gpt-3.5-turbo"):
code_contents = walk_directory(directory)
# Now, `code_contents` is a dictionary that contains the content of all your non-image files
# You can send this to OpenAI's text-davinci-003 for help
context = "\n".join(f"{path}:\n{contents}" for path, contents in code_contents.items())
system = "You are an AI debugger who is trying to debug a program for a user based on their file system. The user has provided you with the following files and their contents, finally folllowed by the error message or issue they are facing."
prompt = "My files are as follows: " + context + "\n\n" + "My issue is as follows: " + prompt
prompt += "\n\nGive me ideas for what could be wrong and what fixes to do in which files."
res = generate_response.call(system, prompt, model)
# print res in teal
print("\033[96m" + res + "\033[0m")
@stub.function(
image=openai_image,
secret=modal.Secret.from_dotenv(),
retries=modal.Retries(
max_retries=3,
backoff_coefficient=2.0,
initial_delay=1.0,
),
concurrency_limit=5,
timeout=120,
)
def generate_response(system_prompt, user_prompt, model="gpt-3.5-turbo", *args):
import openai
# Set up your OpenAI API credentials
openai.api_key = os.environ["OPENAI_API_KEY"]
messages = []
messages.append({"role": "system", "content": system_prompt})
messages.append({"role": "user", "content": user_prompt})
# loop thru each arg and add it to messages alternating role between "assistant" and "user"
role = "assistant"
for value in args:
messages.append({"role": role, "content": value})
role = "user" if role == "assistant" else "assistant"
params = {
'model': model,
# "model": "gpt-4",
"messages": messages,
"max_tokens": 1500,
"temperature": 0,
}
# Send the API request
response = openai.ChatCompletion.create(**params)
# Get the reply from the API response
reply = response.choices[0]["message"]["content"]
return reply