feat: support OCR handwriting recognition feature (#50)

Co-authored-by: mengqian <cherish_a_meng@163.com>

examples/handwriting_ocr_example.py

@@ -0,0 +1,31 @@
+from zai import ZaiClient
+
+client = ZaiClient(
+    base_url="",
+    api_key=""
+)
+
+
+def handwriting_ocr_example():
+    """
+    Full Example: Submit image for recognition and wait for the result to be returned.
+    """
+    # Create recognition task
+    # Please modify the local file path
+    file_path = 'Your image path'
+    with open(file_path, 'rb') as f:
+        print("Submitting a handwriting recognition task ...")
+        response = client.ocr.handwriting_ocr(
+            file=f,
+            tool_type="hand_write",
+            probability=True
+        )
+        print("Task created successfully. Response:")
+        print(response)
+
+    print("Handwriting OCR demo completed.")
+
+
+if __name__ == "__main__":
+    print("=== Handwriting recognition quick demo ===\n")
+    handwriting_ocr_example()

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "zai-sdk"
-version = "0.0.4.2"
+version = "0.0.4.3"
 description = "A SDK library for accessing big model apis from Z.ai"
 authors = ["Z.ai"]
 readme = "README.md"

src/zai/_client.py

@@ -24,6 +24,7 @@ if TYPE_CHECKING:
     from zai.api_resource.web_search import WebSearchApi
     from zai.api_resource.web_reader import WebReaderApi
     from zai.api_resource.file_parser import FileParser
+    from zai.api_resource.ocr import HandwritingOCR
 
 from .core import (
     NOT_GIVEN,
@@ -200,6 +201,11 @@ class BaseClient(HttpClient):
         from zai.api_resource.file_parser import FileParser
         return FileParser(self)
 
+    @cached_property
+    def ocr(self) -> HandwritingOCR:
+        from zai.api_resource.ocr import HandwritingOCR
+        return HandwritingOCR(self)
+
     @property
     @override
     def auth_headers(self) -> dict[str, str]:

src/zai/_version.py

@@ -1,2 +1,2 @@
 __title__ = 'Z.ai'
-__version__ = '0.0.4.2'
+__version__ = '0.0.4.3'

src/zai/api_resource/__init__.py

@@ -10,17 +10,17 @@ from .chat import (
 	Completions,
 )
 from .embeddings import Embeddings
+from .file_parser import FileParser
 from .files import Files, FilesWithRawResponse
 from .images import Images
 from .moderations import Moderations
+from .ocr import HandwritingOCR
 from .tools import Tools
 from .videos import (
 	Videos,
 )
-from .web_search import WebSearchApi
 from .web_reader import WebReaderApi
-from .file_parser import FileParser
+from .web_search import WebSearchApi
-
 
 __all__ = [
     'Videos',
@@ -40,4 +40,5 @@ __all__ = [
     'WebReaderApi',
     'Agents',
     'FileParser',
+    'HandwritingOCR'
 ]

src/zai/api_resource/ocr/__init__.py

@@ -0,0 +1,3 @@
+from .handwriting_ocr import HandwritingOCR
+
+__all__ = ["HandwritingOCR"]

src/zai/api_resource/ocr/handwriting_ocr.py

@@ -0,0 +1,67 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Mapping, cast
+
+import httpx
+from typing_extensions import Literal
+from zai.core import (
+    BaseAPI,
+    maybe_transform,
+    NOT_GIVEN,
+    Body,
+    Headers,
+    NotGiven,
+    FileTypes,
+    deepcopy_minimal,
+    extract_files,
+    make_request_options
+)
+from zai.types.ocr.handwriting_ocr_params import HandwritingOCRParams
+from zai.types.ocr.handwriting_ocr_resp import HandwritingOCRResp
+
+if TYPE_CHECKING:
+    from zai._client import ZaiClient
+
+__all__ = ["HandwritingOCR"]
+
+
+class HandwritingOCR(BaseAPI):
+
+    def __init__(self, client: "ZaiClient") -> None:
+        super().__init__(client)
+
+    def handwriting_ocr(
+            self,
+            *,
+            file: FileTypes,
+            tool_type: Literal["hand_write"],
+            language_type: str = None,  # optional,
+            probability: bool = None,
+            extra_headers: Headers | None = None,
+            extra_body: Body | None = None,
+            timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
+    ) -> HandwritingOCRResp:
+        if not file:
+            raise ValueError("`file` must be provided.")
+        if not tool_type:
+            raise ValueError("`tool_type` must be provided.")
+        body = deepcopy_minimal(
+            {
+                "file": file,
+                "tool_type": tool_type,
+                "language_type": language_type,
+                "probability": probability
+            }
+        )
+        files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])
+        if files:
+            extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
+        return self._post(
+            "/files/ocr",
+            body=maybe_transform(body, HandwritingOCRParams),
+            files=files,
+            options=make_request_options(
+                extra_headers=extra_headers, extra_body=extra_body, timeout=timeout
+            ),
+            cast_type=HandwritingOCRResp,
+        )

src/zai/types/ocr/handwriting_ocr_params.py

@@ -0,0 +1,13 @@
+from __future__ import annotations
+
+from typing_extensions import Literal, TypedDict
+from zai.core import FileTypes
+
+__all__ = ["HandwritingOCRParams"]
+
+
+class HandwritingOCRParams(TypedDict, total=False):
+    file: FileTypes  # Required
+    tool_type: Literal["hand_write"]  # Required
+    language_type: str  # Optional
+    probability: bool

src/zai/types/ocr/handwriting_ocr_resp.py

@@ -0,0 +1,33 @@
+from typing import List
+from typing import Optional
+
+from zai.core import BaseModel
+
+__all__ = ["HandwritingOCRResp"]
+
+
+class Location(BaseModel):
+    left: int
+    top: int
+    width: int
+    height: int
+
+
+class Probability(BaseModel):
+    average: float
+    variance: float
+    min: float
+
+
+class WordsResult(BaseModel):
+    location: Location
+    words: str
+    probability: Probability
+
+
+class HandwritingOCRResp(BaseModel):
+    task_id: str  # Task ID or Result ID
+    message: str  # Status message
+    status: str  # OCR task status
+    words_result_num: int  # Number of recognition results
+    words_result: Optional[List[WordsResult]] = None  # List of recognition resultst details (if any)