chore: import upstream snapshot with attribution

examples/flex-flows/basic/llm.py

@@ -0,0 +1,64 @@
+import os
+
+from dotenv import load_dotenv
+from openai.version import VERSION as OPENAI_VERSION
+
+from promptflow.tracing import trace
+
+
+def get_client():
+    if OPENAI_VERSION.startswith("0."):
+        raise Exception(
+            "Please upgrade your OpenAI package to version >= 1.0.0 or using the command: pip install --upgrade openai."
+        )
+    api_key = os.environ.get("OPENAI_API_KEY", None)
+    if api_key:
+        from openai import OpenAI
+
+        return OpenAI()
+    else:
+        from openai import AzureOpenAI
+
+        return AzureOpenAI(
+            api_version=os.environ.get("OPENAI_API_VERSION", "2023-07-01-preview")
+        )
+
+
+@trace
+def my_llm_tool(
+    prompt: str,
+    # for AOAI, deployment name is customized by user, not model name.
+    deployment_name: str,
+    max_tokens: int = 120,
+    temperature: float = 1.0,
+    top_p: float = 1.0,
+    n: int = 1,
+) -> str:
+    if "OPENAI_API_KEY" not in os.environ and "AZURE_OPENAI_API_KEY" not in os.environ:
+        # load environment variables from .env file
+        load_dotenv()
+
+    if "OPENAI_API_KEY" not in os.environ and "AZURE_OPENAI_API_KEY" not in os.environ:
+        raise Exception(
+            "Please specify environment variables: OPENAI_API_KEY or AZURE_OPENAI_API_KEY"
+        )
+    messages = [{"content": prompt, "role": "system"}]
+    response = get_client().chat.completions.create(
+        messages=messages,
+        model=deployment_name,
+        max_tokens=int(max_tokens),
+        temperature=float(temperature),
+        top_p=float(top_p),
+        n=int(n),
+    )
+
+    # get first element because prompt is single.
+    return response.choices[0].message.content
+
+
+if __name__ == "__main__":
+    result = my_llm_tool(
+        prompt="Write a simple Hello, world! program that displays the greeting message.",
+        deployment_name="gpt-4o",
+    )
+    print(result)