Add CLI tools for chat fine-tuning

src/openai/cli/_api/_main.py

@@ -2,7 +2,7 @@
 
 from argparse import ArgumentParser
 
-from . import chat, audio, files, image, models, completions, fine_tuning
+from . import chat, audio, files, image, models, completions, fine_tuning, chat_fine_tunes
 
 
 def register_commands(parser: ArgumentParser) -> None:
@@ -15,3 +15,4 @@ def register_commands(parser: ArgumentParser) -> None:
     models.register(subparsers)
     completions.register(subparsers)
     fine_tuning.register(subparsers)
+    chat_fine_tunes.register(subparsers)

src/openai/cli/_api/chat_fine_tunes.py

@@ -0,0 +1,13 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+from argparse import ArgumentParser
+
+from .chat_fine_tunes import jobs
+
+if TYPE_CHECKING:
+    from argparse import _SubParsersAction
+
+
+def register(subparser: _SubParsersAction[ArgumentParser]) -> None:
+    jobs.register(subparser)

src/openai/cli/_api/chat_fine_tunes/__init__.py

@@ -0,0 +1 @@
+# API commands for chat fine-tuning (convenience aliases)

src/openai/cli/_api/chat_fine_tunes/jobs.py

@@ -0,0 +1,135 @@
+from __future__ import annotations
+
+import json
+from typing import TYPE_CHECKING
+from argparse import ArgumentParser
+
+from ..._utils import get_client, print_model
+from ...._types import Omittable, omit
+from ...._utils import is_given
+from ..._models import BaseModel
+from ....pagination import SyncCursorPage
+from ....types.fine_tuning import (
+    FineTuningJob,
+    FineTuningJobEvent,
+)
+
+if TYPE_CHECKING:
+    from argparse import _SubParsersAction
+
+
+def register(subparser: _SubParsersAction[ArgumentParser]) -> None:
+    sub = subparser.add_parser("chat_fine_tunes.create")
+    sub.add_argument(
+        "-m",
+        "--model",
+        help="The model to fine-tune.",
+        required=True,
+    )
+    sub.add_argument(
+        "-t",
+        "--training-file",
+        help="The training file to fine-tune the model on.",
+        required=True,
+    )
+    sub.add_argument(
+        "-H",
+        "--hyperparameters",
+        help="JSON string of hyperparameters to use for fine-tuning.",
+        type=str,
+    )
+    sub.add_argument(
+        "-s",
+        "--suffix",
+        help="A suffix to add to the fine-tuned model name.",
+    )
+    sub.add_argument(
+        "-v",
+        "--validation-file",
+        help="The validation file to use for fine-tuning.",
+    )
+    sub.set_defaults(func=CLIChatFineTunes.create, args_model=CLIChatFineTunesCreateArgs)
+
+    sub = subparser.add_parser("chat_fine_tunes.get")
+    sub.add_argument(
+        "-i",
+        "--id",
+        help="The ID of the fine-tuning job to retrieve.",
+        required=True,
+    )
+    sub.set_defaults(func=CLIChatFineTunes.retrieve, args_model=CLIChatFineTunesRetrieveArgs)
+
+    sub = subparser.add_parser("chat_fine_tunes.list")
+    sub.add_argument(
+        "-a",
+        "--after",
+        help="Identifier for the last job from the previous pagination request. If provided, only jobs created after this job will be returned.",
+    )
+    sub.add_argument(
+        "-l",
+        "--limit",
+        help="Number of fine-tuning jobs to retrieve.",
+        type=int,
+    )
+    sub.set_defaults(func=CLIChatFineTunes.list, args_model=CLIChatFineTunesListArgs)
+
+    sub = subparser.add_parser("chat_fine_tunes.cancel")
+    sub.add_argument(
+        "-i",
+        "--id",
+        help="The ID of the fine-tuning job to cancel.",
+        required=True,
+    )
+    sub.set_defaults(func=CLIChatFineTunes.cancel, args_model=CLIChatFineTunesCancelArgs)
+
+
+class CLIChatFineTunesCreateArgs(BaseModel):
+    model: str
+    training_file: str
+    hyperparameters: Omittable[str] = omit
+    suffix: Omittable[str] = omit
+    validation_file: Omittable[str] = omit
+
+
+class CLIChatFineTunesRetrieveArgs(BaseModel):
+    id: str
+
+
+class CLIChatFineTunesListArgs(BaseModel):
+    after: Omittable[str] = omit
+    limit: Omittable[int] = omit
+
+
+class CLIChatFineTunesCancelArgs(BaseModel):
+    id: str
+
+
+class CLIChatFineTunes:
+    @staticmethod
+    def create(args: CLIChatFineTunesCreateArgs) -> None:
+        hyperparameters = json.loads(str(args.hyperparameters)) if is_given(args.hyperparameters) else omit
+        fine_tuning_job: FineTuningJob = get_client().fine_tuning.jobs.create(
+            model=args.model,
+            training_file=args.training_file,
+            hyperparameters=hyperparameters,
+            suffix=args.suffix,
+            validation_file=args.validation_file,
+        )
+        print_model(fine_tuning_job)
+
+    @staticmethod
+    def retrieve(args: CLIChatFineTunesRetrieveArgs) -> None:
+        fine_tuning_job: FineTuningJob = get_client().fine_tuning.jobs.retrieve(fine_tuning_job_id=args.id)
+        print_model(fine_tuning_job)
+
+    @staticmethod
+    def list(args: CLIChatFineTunesListArgs) -> None:
+        fine_tuning_jobs: SyncCursorPage[FineTuningJob] = get_client().fine_tuning.jobs.list(
+            after=args.after or omit, limit=args.limit or omit
+        )
+        print_model(fine_tuning_jobs)
+
+    @staticmethod
+    def cancel(args: CLIChatFineTunesCancelArgs) -> None:
+        fine_tuning_job: FineTuningJob = get_client().fine_tuning.jobs.cancel(fine_tuning_job_id=args.id)
+        print_model(fine_tuning_job)

src/openai/cli/_tools/_main.py

@@ -3,7 +3,7 @@
 from typing import TYPE_CHECKING
 from argparse import ArgumentParser
 
-from . import migrate, fine_tunes
+from . import migrate, fine_tunes, chat_fine_tunes
 
 if TYPE_CHECKING:
     from argparse import _SubParsersAction
@@ -15,3 +15,4 @@ def register_commands(parser: ArgumentParser, subparser: _SubParsersAction[Argum
     namespaced = parser.add_subparsers(title="Tools", help="Convenience client side tools")
 
     fine_tunes.register(namespaced)
+    chat_fine_tunes.register(namespaced)

src/openai/cli/_tools/chat_fine_tunes.py

@@ -0,0 +1,63 @@
+from __future__ import annotations
+
+import sys
+from typing import TYPE_CHECKING
+from argparse import ArgumentParser
+
+from .._models import BaseModel
+from ...lib._validators import (
+    get_chat_validators,
+    write_out_file,
+    read_any_format,
+    apply_validators,
+    apply_necessary_remediation,
+)
+
+if TYPE_CHECKING:
+    from argparse import _SubParsersAction
+
+
+def register(subparser: _SubParsersAction[ArgumentParser]) -> None:
+    sub = subparser.add_parser("chat_fine_tunes.prepare_data")
+    sub.add_argument(
+        "-f",
+        "--file",
+        required=True,
+        help="JSONL, JSON file containing chat messages with roles (system, user, assistant) to be analyzed."
+        "This should be the local file path.",
+    )
+    sub.add_argument(
+        "-q",
+        "--quiet",
+        required=False,
+        action="store_true",
+        help="Auto accepts all suggestions, without asking for user input. To be used within scripts.",
+    )
+    sub.set_defaults(func=prepare_data, args_model=PrepareDataArgs)
+
+
+class PrepareDataArgs(BaseModel):
+    file: str
+
+    quiet: bool
+
+
+def prepare_data(args: PrepareDataArgs) -> None:
+    sys.stdout.write("Analyzing chat fine-tuning data...\n")
+    fname = args.file
+    auto_accept = args.quiet
+    df, remediation = read_any_format(fname)
+    apply_necessary_remediation(None, remediation)
+
+    validators = get_chat_validators()
+
+    assert df is not None
+
+    apply_validators(
+        df,
+        fname,
+        remediation,
+        validators,
+        auto_accept,
+        write_out_file_func=write_out_file,
+    )

src/openai/lib/_validators.py

@@ -747,6 +747,56 @@ def get_common_xfix(series: Any, xfix: str = "suffix") -> str:
 Validator: TypeAlias = "Callable[[pd.DataFrame], Remediation | None]"
 
 
+def chat_messages_validator(df: pd.DataFrame) -> Remediation:
+    """
+    This validator will ensure that the messages column contains properly formatted chat messages.
+    """
+    import json
+
+    immediate_msg = None
+    error_msg = None
+
+    # Check if we have a messages column
+    if 'messages' not in df.columns:
+        error_msg = "`messages` column/key is missing. Chat fine-tuning requires a 'messages' column with an array of message objects."
+    else:
+        # Try to validate the format
+        try:
+            for idx, row in df.iterrows():
+                if 'messages' in row:
+                    messages = json.loads(row['messages']) if isinstance(row['messages'], str) else row['messages']
+                    if not isinstance(messages, list):
+                        raise ValueError(f"Messages must be a list in row {idx}")
+                    for msg in messages:
+                        if not isinstance(msg, dict) or 'role' not in msg or 'content' not in msg:
+                            raise ValueError(f"Each message must have 'role' and 'content' in row {idx}")
+                        if msg['role'] not in ['system', 'user', 'assistant']:
+                            raise ValueError(f"Role must be 'system', 'user', or 'assistant' in row {idx}")
+            immediate_msg = f"\n- Your file contains {len(df)} chat conversations with properly formatted messages"
+        except (json.JSONDecodeError, ValueError, TypeError) as e:
+            error_msg = f"Invalid messages format: {str(e)}. Messages must be a JSON array of objects with 'role' and 'content' fields."
+
+    return Remediation(
+        name="chat_messages",
+        immediate_msg=immediate_msg,
+        error_msg=error_msg,
+    )
+
+
+def chat_num_examples_validator(df: pd.DataFrame) -> Remediation:
+    """
+    This validator will print out the number of chat examples and recommend increasing if less than 10.
+    """
+    MIN_EXAMPLES = 10
+    optional_suggestion = (
+        ""
+        if len(df) >= MIN_EXAMPLES
+        else ". For chat fine-tuning, we recommend having at least 10 examples, but preferably 50-100 for better results"
+    )
+    immediate_msg = f"\n- Your file contains {len(df)} chat conversations{optional_suggestion}"
+    return Remediation(name="chat_num_examples", immediate_msg=immediate_msg)
+
+
 def get_validators() -> list[Validator]:
     return [
         num_examples_validator,
@@ -767,6 +817,17 @@ def get_validators() -> list[Validator]:
     ]
 
 
+def get_chat_validators() -> list[Validator]:
+    """
+    Get validators specifically for chat fine-tuning data format.
+    """
+    return [
+        chat_num_examples_validator,
+        chat_messages_validator,
+        duplicated_rows_validator,
+    ]
+
+
 def apply_validators(
     df: pd.DataFrame,
     fname: str,