chore: import upstream snapshot with attribution

examples/tutorials/tracing/math_to_code.py

@@ -0,0 +1,93 @@
+import ast
+import os
+
+from dotenv import load_dotenv
+from openai import AzureOpenAI
+
+from promptflow.tracing import start_trace, trace
+
+
+@trace
+def infinite_loop_check(code_snippet):
+    tree = ast.parse(code_snippet)
+    for node in ast.walk(tree):
+        if isinstance(node, ast.While):
+            if not node.orelse:
+                return True
+    return False
+
+
+@trace
+def syntax_error_check(code_snippet):
+    try:
+        ast.parse(code_snippet)
+    except SyntaxError:
+        return True
+    return False
+
+
+@trace
+def error_fix(code_snippet):
+    tree = ast.parse(code_snippet)
+    for node in ast.walk(tree):
+        if isinstance(node, ast.While):
+            if not node.orelse:
+                node.orelse = [ast.Pass()]
+    return ast.unparse(tree)
+
+
+@trace
+def code_refine(original_code: str) -> str:
+    original_code = original_code.replace("python", "").replace("`", "").strip()
+    fixed_code = None
+
+    if infinite_loop_check(original_code):
+        fixed_code = error_fix(original_code)
+    else:
+        fixed_code = original_code
+
+    if syntax_error_check(fixed_code):
+        fixed_code = error_fix(fixed_code)
+
+    return fixed_code
+
+
+@trace
+def code_gen(client: AzureOpenAI, question: str) -> str:
+    sys_prompt = (
+        "I want you to act as a math expert specializing in Algebra, Geometry, and Calculus. "
+        "Given the question, develop python code to model the user's question. "
+        "Make sure only reply the executable code, no other words."
+    )
+    completion = client.chat.completions.create(
+        model=os.getenv("CHAT_DEPLOYMENT_NAME", "gpt-35-turbo"),
+        messages=[
+            {
+                "role": "system",
+                "content": sys_prompt,
+            },
+            {"role": "user", "content": question},
+        ],
+    )
+    raw_code = completion.choices[0].message.content
+    result = code_refine(raw_code)
+    return result
+
+
+if __name__ == "__main__":
+    start_trace()
+
+    if "AZURE_OPENAI_API_KEY" not in os.environ:
+        # load environment variables from .env file
+        load_dotenv()
+
+    client = AzureOpenAI(
+        api_key=os.getenv("AZURE_OPENAI_API_KEY"),
+        azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
+        api_version="2023-12-01-preview",
+    )
+
+    question = "What is 37593 * 67?"
+
+    code = code_gen(client, question)
+    print(code)