Fix PR comments

.vscode/cspell.json

@@ -1323,12 +1323,20 @@
     {
       "filename": "sdk/ai/azure-ai-inference/**",
       "words": [
-        "ubinary",
-        "mros",
-        "Nify",
         "ctxt",
-        "wday",
-        "dtype"
+        "dels",
+        "dtype",
+        "fmatter",
+        "fspath",
+        "fstring",
+        "ldel",
+        "mros",
+        "nify",
+        "okwargs",
+        "prompty",
+        "rdel",
+        "ubinary",
+        "wday"
       ]
     },
     {

sdk/ai/azure-ai-inference/azure/ai/inference/prompts/_core.py

@@ -10,7 +10,7 @@
 from pathlib import Path
 from typing import Any, AsyncIterator, Dict, Iterator, List, Literal, Union
 from ._tracer import Tracer, to_dict
-from ._utils import load_json, load_json_async
+from ._utils import load_json
 
 
 @dataclass
@@ -185,20 +185,6 @@ def _process_file(file: str, parent: Path) -> Any:
         else:
             raise FileNotFoundError(f"File {file} not found")
 
-    @staticmethod
-    async def _process_file_async(file: str, parent: Path) -> Any:
-        file_path = Path(parent / Path(file)).resolve().absolute()
-        if file_path.exists():
-            items = await load_json_async(file_path)
-            if isinstance(items, list):
-                return [Prompty.normalize(value, parent) for value in items]
-            elif isinstance(items, Dict):
-                return {key: Prompty.normalize(value, parent) for key, value in items.items()}
-            else:
-                return items
-        else:
-            raise FileNotFoundError(f"File {file} not found")
-
     @staticmethod
     def _process_env(variable: str, env_error=True, default: Union[str, None] = None) -> Any:
         if variable in os.environ.keys():
@@ -237,32 +223,6 @@ def normalize(attribute: Any, parent: Path, env_error=True) -> Any:
         else:
             return attribute
 
-    @staticmethod
-    async def normalize_async(attribute: Any, parent: Path, env_error=True) -> Any:
-        if isinstance(attribute, str):
-            attribute = attribute.strip()
-            if attribute.startswith("${") and attribute.endswith("}"):
-                # check if env or file
-                variable = attribute[2:-1].split(":")
-                if variable[0] == "env" and len(variable) > 1:
-                    return Prompty._process_env(
-                        variable[1],
-                        env_error,
-                        variable[2] if len(variable) > 2 else None,
-                    )
-                elif variable[0] == "file" and len(variable) > 1:
-                    return await Prompty._process_file_async(variable[1], parent)
-                else:
-                    raise ValueError(f"Invalid attribute format ({attribute})")
-            else:
-                return attribute
-        elif isinstance(attribute, list):
-            return [await Prompty.normalize_async(value, parent) for value in attribute]
-        elif isinstance(attribute, Dict):
-            return {key: await Prompty.normalize_async(value, parent) for key, value in attribute.items()}
-        else:
-            return attribute
-
 
 def param_hoisting(top: Dict[str, Any], bottom: Dict[str, Any], top_key: Union[str, None] = None) -> Dict[str, Any]:
     if top_key:

sdk/ai/azure-ai-inference/azure/ai/inference/prompts/_patch.py

@@ -88,7 +88,7 @@ def __init__(
                 "prompt_template": prompt_template,
             }
         else:
-            raise ValueError("Please invalid arguments for PromptTemplate")
+            raise ValueError("Please pass valid arguments for PromptTemplate")
 
     def create_messages(self, data: Optional[Dict[str, Any]] = None, **kwargs) -> List[Dict[str, Any]]:
         """Render the prompt template with the given data.

sdk/ai/azure-ai-inference/azure/ai/inference/prompts/_prompty_utils.py

@@ -18,8 +18,6 @@
 )
 from ._utils import (
     load_global_config,
-    load_global_config_async,
-    load_prompty_async,
     load_prompty,
 )
 
@@ -82,62 +80,6 @@ def headless(
     return Prompty(model=modelSettings, template=templateSettings, content=content)
 
 
-@trace(description="Create a headless prompty object for programmatic use.")
-async def headless_async(
-    api: str,
-    content: Union[str, List[str], dict],
-    configuration: Dict[str, Any] = {},
-    parameters: Dict[str, Any] = {},
-    connection: str = "default",
-) -> Prompty:
-    """Create a headless prompty object for programmatic use.
-
-    Parameters
-    ----------
-    api : str
-        The API to use for the model
-    content : Union[str, List[str], dict]
-        The content to process
-    configuration : Dict[str, Any], optional
-        The configuration to use, by default {}
-    parameters : Dict[str, Any], optional
-        The parameters to use, by default {}
-    connection : str, optional
-        The connection to use, by default "default"
-
-    Returns
-    -------
-    Prompty
-        The headless prompty object
-
-    Example
-    -------
-    >>> import prompty
-    >>> p = await prompty.headless_async(
-            api="embedding",
-            configuration={"type": "azure", "azure_deployment": "text-embedding-ada-002"},
-            content="hello world",
-        )
-    >>> emb = prompty.execute(p)
-
-    """
-
-    # get caller's path (to get relative path for prompty.json)
-    caller = Path(traceback.extract_stack()[-2].filename)
-    templateSettings = TemplateSettings(type="NOOP", parser="NOOP")
-
-    global_config = await load_global_config_async(caller.parent, connection)
-    c = await Prompty.normalize_async(param_hoisting(configuration, global_config), caller.parent)
-
-    modelSettings = ModelSettings(
-        api=api,
-        configuration=c,
-        parameters=parameters,
-    )
-
-    return Prompty(model=modelSettings, template=templateSettings, content=content)
-
-
 def _load_raw_prompty(attributes: dict, content: str, p: Path, global_config: dict):
     if "model" not in attributes:
         attributes["model"] = {}
@@ -205,7 +147,7 @@ def load(prompty_file: Union[str, Path], configuration: str = "default") -> Prom
 
     Parameters
     ----------
-    prompty_file : str
+    prompty_file : Union[str, Path]
         The path to the prompty file
     configuration : str, optional
         The configuration to use, by default "default"
@@ -251,59 +193,6 @@ def load(prompty_file: Union[str, Path], configuration: str = "default") -> Prom
     return prompty
 
 
-@trace(description="Load a prompty file.")
-async def load_async(prompty_file: Union[str, Path], configuration: str = "default") -> Prompty:
-    """Load a prompty file.
-
-    Parameters
-    ----------
-    prompty_file : str
-        The path to the prompty file
-    configuration : str, optional
-        The configuration to use, by default "default"
-
-    Returns
-    -------
-    Prompty
-        The loaded prompty object
-
-    Example
-    -------
-    >>> import prompty
-    >>> p = prompty.load("prompts/basic.prompty")
-    >>> print(p)
-    """
-
-    p = Path(prompty_file)
-    if not p.is_absolute():
-        # get caller's path (take into account trace frame)
-        caller = Path(traceback.extract_stack()[-3].filename)
-        p = Path(caller.parent / p).resolve().absolute()
-
-    # load dictionary from prompty file
-    matter = await load_prompty_async(p)
-
-    attributes = matter["attributes"]
-    content = matter["body"]
-
-    # normalize attribute dictionary resolve keys and files
-    attributes = await Prompty.normalize_async(attributes, p.parent)
-
-    # load global configuration
-    config = await load_global_config_async(p.parent, configuration)
-    global_config = await Prompty.normalize_async(config, p.parent)
-
-    prompty = _load_raw_prompty(attributes, content, p, global_config)
-
-    # recursive loading of base prompty
-    if "base" in attributes:
-        # load the base prompty from the same directory as the current prompty
-        base = await load_async(p.parent / attributes["base"])
-        prompty = Prompty.hoist_base_prompty(prompty, base)
-
-    return prompty
-
-
 @trace(description="Prepare the inputs for the prompt.")
 def prepare(
     prompt: Prompty,
@@ -524,57 +413,3 @@ def execute(
     result = run(prompt, content, configuration, parameters, raw)
 
     return result
-
-
-@trace(description="Execute a prompty")
-async def execute_async(
-    prompt: Union[str, Prompty],
-    configuration: Dict[str, Any] = {},
-    parameters: Dict[str, Any] = {},
-    inputs: Dict[str, Any] = {},
-    raw: bool = False,
-    config_name: str = "default",
-):
-    """Execute a prompty.
-
-    Parameters
-    ----------
-    prompt : Union[str, Prompty]
-        The prompty object or path to the prompty file
-    configuration : Dict[str, Any], optional
-        The configuration to use, by default {}
-    parameters : Dict[str, Any], optional
-        The parameters to use, by default {}
-    inputs : Dict[str, Any], optional
-        The inputs to the prompt, by default {}
-    raw : bool, optional
-        Whether to skip processing, by default False
-    connection : str, optional
-        The connection to use, by default "default"
-
-    Returns
-    -------
-    Any
-        The result of the prompt
-
-    Example
-    -------
-    >>> import prompty
-    >>> inputs = {"name": "John Doe"}
-    >>> result = await prompty.execute_async("prompts/basic.prompty", inputs=inputs)
-    """
-    if isinstance(prompt, str):
-        path = Path(prompt)
-        if not path.is_absolute():
-            # get caller's path (take into account trace frame)
-            caller = Path(traceback.extract_stack()[-3].filename)
-            path = Path(caller.parent / path).resolve().absolute()
-        prompt = await load_async(path, config_name)
-
-    # prepare content
-    content = await prepare_async(prompt, inputs)
-
-    # run LLM model
-    result = await run_async(prompt, content, configuration, parameters, raw)
-
-    return result

sdk/ai/azure-ai-inference/azure/ai/inference/prompts/_utils.py

@@ -7,7 +7,6 @@
 import re
 import yaml
 import json
-import aiofiles
 from typing import Any, Dict, Union
 from pathlib import Path
 
@@ -22,22 +21,10 @@ def load_text(file_path, encoding="utf-8"):
         return file.read()
 
 
-async def load_text_async(file_path, encoding="utf-8"):
-    async with aiofiles.open(file_path, mode="r", encoding=encoding) as f:
-        content = await f.read()
-        return content
-
-
 def load_json(file_path, encoding="utf-8"):
     return json.loads(load_text(file_path, encoding=encoding))
 
 
-async def load_json_async(file_path, encoding="utf-8"):
-    # async file open
-    content = await load_text_async(file_path, encoding=encoding)
-    return json.loads(content)
-
-
 def _find_global_config(prompty_path: Path = Path.cwd()) -> Union[Path, None]:
     prompty_config = list(Path.cwd().glob("**/prompty.json"))
 
@@ -65,31 +52,11 @@ def load_global_config(prompty_path: Path = Path.cwd(), configuration: str = "de
     return {}
 
 
-async def load_global_config_async(prompty_path: Path = Path.cwd(), configuration: str = "default") -> Dict[str, Any]:
-    # prompty.config laying around?
-    config = _find_global_config(prompty_path)
-
-    # if there is one load it
-    if config is not None:
-        c = await load_json_async(config)
-        if configuration in c:
-            return c[configuration]
-        else:
-            raise ValueError(f'Item "{configuration}" not found in "{config}"')
-
-    return {}
-
-
 def load_prompty(file_path, encoding="utf-8") -> Dict[str, Any]:
     contents = load_text(file_path, encoding=encoding)
     return parse(contents)
 
 
-async def load_prompty_async(file_path, encoding="utf-8"):
-    contents = await load_text_async(file_path, encoding=encoding)
-    return parse(contents)
-
-
 def parse(contents):
     global _yaml_regex
 

sdk/ai/azure-ai-inference/dev_requirements.txt

@@ -4,7 +4,4 @@
 ../../monitor/azure-monitor-opentelemetry
 aiohttp
 opentelemetry-sdk
-aiofiles
-dataclasses
 types-pyyaml
-types-aiofiles

sdk/ai/azure-ai-inference/setup.py

@@ -62,11 +62,7 @@
     package_data={
         "azure.ai.inference": ["py.typed"],
     },
-    install_requires=[
-        "isodate>=0.6.1",
-        "azure-core>=1.30.0",
-        "typing-extensions>=4.6.0",
-    ],
+    install_requires=["isodate>=0.6.1", "azure-core>=1.30.0", "typing-extensions>=4.6.0"],
     python_requires=">=3.8",
     extras_require={"opentelemetry": ["azure-core-tracing-opentelemetry"]},
 )