Create cli.py

health_function_lm/cli.py

@@ -0,0 +1,70 @@
+"""
+Command-line interface for health-function-lm.
+
+Usage
+-----
+  health-fn "Log my blood pressure as 120/80"
+  health-fn --pretty "What is my resting heart rate?"
+  echo "Log weight 70kg" | health-fn
+"""
+
+import argparse
+import json
+import sys
+
+from .model import HealthFunctionLM
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        prog="health-fn",
+        description="Run a health query through the function-calling model.",
+    )
+    parser.add_argument(
+        "query",
+        nargs="?",
+        help="Natural-language health query. Reads from stdin if omitted.",
+    )
+    parser.add_argument(
+        "--pretty",
+        action="store_true",
+        default=True,
+        help="Pretty-print JSON output (default: on).",
+    )
+    parser.add_argument(
+        "--repo-id",
+        default="ramgovindv/health_function_call_llama3.2_3b_gguf",
+        help="Hugging Face repo ID.",
+    )
+    parser.add_argument(
+        "--filename",
+        default="Llama-3.2-3B-Instruct.Q4_K_M.gguf",
+        help="GGUF filename inside the repo.",
+    )
+    parser.add_argument(
+        "--n-ctx", type=int, default=2048, help="Context window size."
+    )
+    parser.add_argument(
+        "--n-threads", type=int, default=4, help="Number of CPU threads."
+    )
+
+    args = parser.parse_args()
+
+    query = args.query or sys.stdin.read().strip()
+    if not query:
+        parser.error("Provide a query as an argument or via stdin.")
+
+    lm = HealthFunctionLM(
+        repo_id=args.repo_id,
+        filename=args.filename,
+        n_ctx=args.n_ctx,
+        n_threads=args.n_threads,
+    )
+
+    result = lm.query(query)
+    indent = 2 if args.pretty else None
+    print(json.dumps(result, indent=indent))
+
+
+if __name__ == "__main__":
+    main()