Add app.py

app.py

@@ -0,0 +1,69 @@
+import importlib.util
+import sys
+import traceback
+
+import gradio as gr
+
+from heal import repair
+
+
+def import_module_from_string(name: str, source: str):
+    """
+    Import module from source string.
+    Example use:
+    import_module_from_string("m", "f = lambda: print('hello')")
+    m.f()
+    """
+    spec = importlib.util.spec_from_loader(name, loader=None)
+    module = importlib.util.module_from_spec(spec)
+    exec(source, module.__dict__)
+    sys.modules[name] = module
+    globals()[name] = module
+
+def main(code: str):
+    success = False
+    while not success:
+        try:
+            import_module_from_string("bad_code", code)
+            success = True
+        except:
+            traceback_data = traceback.format_exc()
+            print(traceback_data)
+
+            corrected = repair(code, traceback_data)
+            print(corrected)
+
+            code = corrected
+    return code
+
+
+demo = gr.Interface(
+    fn=main,
+    inputs=gr.Textbox(lines=2, placeholder="Broken Python code here..."),
+    outputs="text",
+    title="Athelas: Self-Healing Code",
+    description="Submit some broken Python code, and Athelas will repair it!",
+    examples=[
+        """
+        import mth
+
+        def ad(x, y):
+            ret x + y
+
+        def ad_test():
+            asset cal(4, 3) == 6
+
+        f read_(file):
+        with open(file) as f:
+            etu f.read()
+
+        def fib(n):
+            golden_ratio = (1 + math.sqrt(5)) / 93#2
+            val = (golden_rat**n - (1 - golden_ratio)**n) / math.sqrt(5)
+            return int(round(val))
+        """
+    ],
+    cache_examples=True
+)
+
+demo.launch()

heal.py

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+import openai
+import os
+
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+def repair(code: str, stacktrace: str):
+    prompt = """
+    You are an AI assistant that can repair a certain piece of errorful code given its stacktrace.
+
+    Here's the code:
+    {}
+
+    Here's the stacktrace from running it:
+    {}
+
+    Write the corrected code:
+    """.format(code, stacktrace)
+
+
+    response = openai.Completion.create(
+        model="text-davinci-003",
+        prompt=prompt,
+        temperature=0.7,
+        max_tokens=256,
+        top_p=1,
+        frequency_penalty=0,
+        presence_penalty=0
+    )
+    return response['choices'][0]['text']

requirements.txt

@@ -0,0 +1 @@
+openai