add DSPy operator CLI

Author: ks6088ts

docs/references.md

@@ -84,3 +84,9 @@
 
 - [LM Studio](https://lmstudio.ai/)
 - [Hugging Face CLI](https://huggingface.co/docs/huggingface_hub/guides/cli)
+
+### DSPy
+
+- [DSPy (Declarative Self-improving Python)](https://dspy.ai/)
+- [Language Models](https://dspy.ai/learn/programming/language_models/)
+- [Language Models / v3.0.3](https://github.com/stanfordnlp/dspy/blob/3.0.3/docs/docs/learn/programming/language_models.md)

scripts/dspy_operator.py

@@ -0,0 +1,80 @@
+import logging
+from logging import basicConfig
+
+import dspy
+import typer
+from dotenv import load_dotenv
+
+from template_langgraph.llms.azure_openais import Settings
+from template_langgraph.loggers import get_logger
+
+# Initialize the Typer application
+app = typer.Typer(
+    add_completion=False,
+    help="DSPy operator CLI",
+)
+
+# Set up logging
+logger = get_logger(__name__)
+
+
+def set_verbose_logging(verbose: bool):
+    if verbose:
+        logger.setLevel(logging.DEBUG)
+        basicConfig(level=logging.DEBUG)
+
+
+@app.command()
+def run(
+    question: str = typer.Option(
+        "今日はどんな天気ですか？",
+        "--question",
+        "-q",
+        help="Question to ask the DSPy model",
+    ),
+    verbose: bool = typer.Option(
+        False,
+        "--verbose",
+        "-v",
+        help="Enable verbose output",
+    ),
+):
+    set_verbose_logging(verbose)
+
+    settings = Settings()
+
+    lm = dspy.LM(
+        model=f"azure/{settings.azure_openai_model_chat}",
+        api_key=settings.azure_openai_api_key,
+        api_base=settings.azure_openai_endpoint,
+        api_version=settings.azure_openai_api_version,
+    )
+    dspy.configure(lm=lm)
+
+    # Define a module (ChainOfThought) and assign it a signature (return an answer, given a question).
+    qa = dspy.ChainOfThought("question -> answer")
+
+    # Run with the default LM configured with `dspy.configure` above.
+    prediction = qa(question=question)
+    print(prediction)
+
+
+@app.command()
+def template(
+    verbose: bool = typer.Option(
+        False,
+        "--verbose",
+        "-v",
+        help="Enable verbose output",
+    ),
+):
+    set_verbose_logging(verbose)
+    logger.info("Running...")
+
+
+if __name__ == "__main__":
+    load_dotenv(
+        override=True,
+        verbose=True,
+    )
+    app()