Support model-based (/engineless) completions in openai cli

openai/api_resources/abstract/engine_api_resource.py

@@ -37,12 +37,6 @@ def create(
         organization=None,
         **params,
     ):
-        """
-        Create a new instance of this model.
-
-        Parameters:
-        timeout (float): the number of seconds to wait on the promise returned by the API, where 0 means wait forever.
-        """
         engine = params.pop("engine", None)
         timeout = params.pop("timeout", None)
         stream = params.get("stream", False)

openai/api_resources/completion.py

@@ -3,16 +3,29 @@
 from openai import util
 from openai.api_resources.abstract import DeletableAPIResource, ListableAPIResource
 from openai.api_resources.abstract.engine_api_resource import EngineAPIResource
-from openai.error import TryAgain
+from openai.error import TryAgain, InvalidRequestError
 
 
 class Completion(EngineAPIResource, ListableAPIResource, DeletableAPIResource):
-    engine_required = True
+    engine_required = False
     OBJECT_NAME = "completion"
 
     @classmethod
-    def create(cls, *args, timeout=None, **kwargs):
+    def create(cls, *args, **kwargs):
+        """
+        Creates a new completion for the provided prompt and parameters.
+
+        See https://beta.openai.com/docs/api-reference/completions/create for a list
+        of valid parameters.
+        """
         start = time.time()
+        timeout = kwargs.get("timeout", None)
+        if kwargs.get("model", None) is None and kwargs.get("engine", None) is None:
+            raise InvalidRequestError(
+                "Must provide an 'engine' or 'model' parameter to create a Completion.",
+                param="engine",
+            )
+
         while True:
             try:
                 return super().create(*args, **kwargs)

openai/cli.py

@@ -138,8 +138,14 @@ def create(cls, args):
         if args.n is not None and args.n > 1 and args.stream:
             raise ValueError("Can't stream completions with n>1 with the current CLI")
 
+        if args.engine and args.model:
+            warnings.warn(
+                "In most cases, you should not be specifying both engine and model."
+            )
+
         resp = openai.Completion.create(
             engine=args.engine,
+            model=args.model,
             n=args.n,
             max_tokens=args.max_tokens,
             logprobs=args.logprobs,
@@ -253,30 +259,14 @@ def create(cls, args):
             return
 
         sys.stdout.write(
-            "Created job: {job_id}\n"
-            "Streaming events until the job is complete...\n\n"
-            "(Ctrl-C will interrupt the stream, but not cancel the job)\n".format(
+            "Created fine-tune: {job_id}\n"
+            "Streaming events until fine-tuning is complete...\n\n"
+            "(Ctrl-C will interrupt the stream, but not cancel the fine-tune)\n".format(
                 job_id=resp["id"]
             )
         )
         cls._stream_events(resp["id"])
 
-        resp = openai.FineTune.retrieve(id=resp["id"])
-        status = resp["status"]
-        sys.stdout.write("\nJob complete! Status: {status}".format(status=status))
-        if status == "succeeded":
-            sys.stdout.write(" 🎉")
-            sys.stdout.write(
-                "\nTry out your fine-tuned model: {model}\n"
-                "(Pass this as the model parameter to a completion request)".format(
-                    model=resp["fine_tuned_model"]
-                )
-            )
-            # TODO(rachel): Print instructions on how to use the model here.
-        elif status == "failed":
-            sys.stdout.write("\nPlease contact [email protected] for assistance.")
-        sys.stdout.write("\n")
-
     @classmethod
     def get(cls, args):
         resp = openai.FineTune.retrieve(id=args.id)
@@ -296,8 +286,8 @@ def signal_handler(sig, frame):
             status = openai.FineTune.retrieve(job_id).status
             sys.stdout.write(
                 "\nStream interrupted. Job is still {status}. "
-                "To cancel your job, run:\n"
-                "`openai api fine_tunes.cancel -i {job_id}`\n".format(
+                "To cancel your job, run:\n\n"
+                "openai api fine_tunes.cancel -i {job_id}\n".format(
                     status=status, job_id=job_id
                 )
             )
@@ -318,6 +308,22 @@ def signal_handler(sig, frame):
             sys.stdout.write("\n")
             sys.stdout.flush()
 
+        resp = openai.FineTune.retrieve(id=job_id)
+        status = resp["status"]
+        if status == "succeeded":
+            sys.stdout.write("\nJob complete! Status: succeeded 🎉")
+            sys.stdout.write(
+                "\nTry out your fine-tuned model:\n\n"
+                "openai api completions.create -m {model} -p <YOUR_PROMPT>".format(
+                    model=resp["fine_tuned_model"]
+                )
+            )
+        elif status == "failed":
+            sys.stdout.write(
+                "\nJob failed. Please contact [email protected] if you need assistance."
+            )
+        sys.stdout.write("\n")
+
     @classmethod
     def cancel(cls, args):
         resp = openai.FineTune.cancel(id=args.id)
@@ -422,7 +428,16 @@ def help(args):
 
     # Completions
     sub = subparsers.add_parser("completions.create")
-    sub.add_argument("-e", "--engine", required=True, help="The engine to use")
+    sub.add_argument(
+        "-e",
+        "--engine",
+        help="The engine to use. See https://beta.openai.com/docs/engines for more about what engines are available.",
+    )
+    sub.add_argument(
+        "-m",
+        "--model",
+        help="The model to use. At most one of `engine` or `model` should be specified.",
+    )
     sub.add_argument(
         "--stream", help="Stream tokens as they're ready.", action="store_true"
     )

openai/version.py

@@ -1 +1 @@
-VERSION = "0.7.0"
+VERSION = "0.8.0"