Merge pull request #14 from aymara-ai/release-please--branches--main--changes--next

dr3s · web-flow · commit c595fa142b65 · 2025-05-02T11:36:34.000-04:00
release: 1.0.0-alpha.13
diff --git a/.release-please-manifest.json b/.release-please-manifest.json
@@ -1,3 +1,3 @@
 {
-  ".": "1.0.0-alpha.12"
+  ".": "1.0.0-alpha.13"
 }
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,5 +1,24 @@
 # Changelog
 
+## 1.0.0-alpha.13 (2025-05-02)
+
+Full Changelog: [v1.0.0-alpha.12...v1.0.0-alpha.13](https://github.com/aymara-ai/aymara-sdk-python/compare/v1.0.0-alpha.12...v1.0.0-alpha.13)
+
+### Features
+
+* file upload utils ([2a728da](https://github.com/aymara-ai/aymara-sdk-python/commit/2a728dadbd363952487687a5bbfa21935877fe36))
+
+
+### Bug Fixes
+
+* image generation ([9a78e78](https://github.com/aymara-ai/aymara-sdk-python/commit/9a78e78fddcd44052e8e3c61d4c68baedda68387))
+
+
+### Chores
+
+* lint ([53cbfbd](https://github.com/aymara-ai/aymara-sdk-python/commit/53cbfbd1702b4f04a1a778993ec275a28168f98c))
+* lint ([2a0caac](https://github.com/aymara-ai/aymara-sdk-python/commit/2a0caac33ecfaf4f6ef64194bc607fc0ec5b8a91))
+
 ## 1.0.0-alpha.12 (2025-05-01)
 
 Full Changelog: [v1.0.0-alpha.11...v1.0.0-alpha.12](https://github.com/aymara-ai/aymara-sdk-python/compare/v1.0.0-alpha.11...v1.0.0-alpha.12)
diff --git a/examples/image_safety_eval.ipynb b/examples/image_safety_eval.ipynb
diff --git a/examples/image_safety_eval_runner.ipynb b/examples/image_safety_eval_runner.ipynb
diff --git a/pyproject.toml b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "aymara-ai-sdk"
-version = "1.0.0-alpha.12"
+version = "1.0.0-alpha.13"
 description = "The official Python library for the aymara-ai API"
 dynamic = ["readme"]
 license = "Apache-2.0"
diff --git a/src/aymara_ai/_version.py b/src/aymara_ai/_version.py
@@ -1,4 +1,4 @@
 # File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
 
 __title__ = "aymara_ai"
-__version__ = "1.0.0-alpha.12"  # x-release-please-version
+__version__ = "1.0.0-alpha.13"  # x-release-please-version
diff --git a/src/aymara_ai/lib/images_utils.py b/src/aymara_ai/lib/images_utils.py
@@ -126,7 +126,7 @@ def trim_caption(caption):
         row += 1
 
         # Image row
-        images = [a["local_file_path"] for a in responses[:n_images_per_eval] if a.ai_refused is False]
+        images = [a["local_file_path"] for a in responses[:n_images_per_eval] if a.get("ai_refused", False) is False]
         if eval_runs is None:
             captions = [
                 next(
diff --git a/src/aymara_ai/lib/runner.py b/src/aymara_ai/lib/runner.py
@@ -7,9 +7,9 @@
 from pathlib import Path
 
 import httpx
-import aiofiles
 
 from aymara_ai import AymaraAI, AsyncAymaraAI
+from aymara_ai.lib.uploads import upload_file, upload_file_async
 from aymara_ai.lib.async_utils import wait_until_complete, async_wait_until_complete
 from aymara_ai.types.eval_prompt import EvalPrompt
 from aymara_ai.types.shared_params import FileReference
@@ -57,27 +57,6 @@ def _default_response_adapter(model_output: Union[str, Path], prompt: EvalPrompt
         else:
             raise ValueError("Unsupported model output type for response adapter.")
 
-    def upload_file_content(
-        self, *, client: httpx.Client, file_name: str, file_content: Union[Path, bytes]
-    ) -> FileReference:
-        """
-        Helper to upload file content (from Path or bytes) and return (FileReference).
-        """
-        upload_resp = self.client.files.create(files=[{"local_file_path": file_name}])
-        file_info = upload_resp.files[0]
-        if not file_info.file_url:
-            raise RuntimeError("No presigned file_url returned for upload.")
-        if isinstance(file_content, Path):
-            with open(str(file_content), "rb") as f:
-                put_resp = client.put(file_info.file_url, content=f)
-                put_resp.raise_for_status()
-        elif isinstance(file_content, bytes):  # type: ignore
-            put_resp = client.put(file_info.file_url, content=file_content)
-            put_resp.raise_for_status()
-        else:
-            raise ValueError("Unsupported file_content type for upload.")
-        return FileReference(remote_file_path=file_info.remote_file_path)
-
     def run_eval(
         self,
         eval_params: Dict[str, Any],
@@ -114,17 +93,23 @@ def run_eval(
                     continue
 
                 file_content = model_output
-                file_name = "model_output.png"
+                file_name = None
                 if isinstance(model_output, Path):  # type: ignore
                     file_content = model_output
                     file_name = str(model_output)
-                file_ref = self.upload_file_content(client=client, file_content=file_content, file_name=file_name)
+                file_ref = upload_file(
+                    client=self.client,
+                    http_client=client,
+                    file_name=file_name,
+                    file_content=file_content,
+                    content_type=None,
+                )
                 response = EvalResponseParam(
                     content=file_ref,
                     prompt_uuid=prompt.prompt_uuid,
                     content_type="image",
                 )
-                response["local_file_path"] = file_name  # type: ignore
+                response["local_file_path"] = file_name if file_name is not None else "file.png"  # type: ignore
                 responses.append(response)
 
         # 5. Create eval run
@@ -175,29 +160,6 @@ def _default_response_adapter(model_output: Union[str, Path], prompt: EvalPrompt
         else:
             raise ValueError("Unsupported model output type for response adapter.")
 
-    async def upload_file_content_async(
-        self, *, client: httpx.AsyncClient, file_name: str, file_content: Union[Path, bytes]
-    ) -> FileReference:
-        """
-        Async helper to upload file content (from Path or bytes) and return (FileReference).
-        """
-        upload_resp = await self.client.files.create(files=[{"local_file_path": file_name}])
-        file_info = upload_resp.files[0]
-        if not file_info.file_url:
-            raise RuntimeError("No presigned file_url returned for upload.")
-        if isinstance(file_content, Path):
-            async with aiofiles.open(str(file_content), mode="rb") as f:
-                put_resp = await client.put(file_info.file_url, content=f)
-                if put_resp.status_code != 200:
-                    raise RuntimeError(f"Failed to upload file: {put_resp.status_code}")
-        elif isinstance(file_content, bytes):  # type: ignore
-            put_resp = await client.put(file_info.file_url, content=file_content)
-            if put_resp.status_code != 200:
-                raise RuntimeError(f"Failed to upload file: {put_resp.status_code}")
-        else:
-            raise ValueError("Unsupported file_content type for upload.")
-        return FileReference(remote_file_path=file_info.remote_file_path)
-
     async def run_eval(
         self,
         eval_params: Dict[str, Any],
@@ -237,19 +199,23 @@ async def run_eval(
                     continue
 
                 file_content = model_output
-                file_name = "model_output.png"
+                file_name = None
                 if isinstance(model_output, Path):  # type: ignore
                     file_content = model_output
                     file_name = str(model_output)
-                file_ref = await self.upload_file_content_async(
-                    client=client, file_name=file_name, file_content=file_content
+                file_ref = await upload_file_async(
+                    client=self.client,
+                    http_client=client,
+                    file_name=file_name,
+                    file_content=file_content,
+                    content_type=None,
                 )
                 response = EvalResponseParam(
                     content=file_ref,
                     prompt_uuid=prompt.prompt_uuid,
                     content_type="image",
                 )
-                response["local_file_path"] = file_name  # type: ignore
+                response["local_file_path"] = file_name if file_name is not None else "file.png"  # type: ignore
                 responses.append(response)
 
         # 5. Create eval run
diff --git a/src/aymara_ai/lib/uploads.py b/src/aymara_ai/lib/uploads.py
@@ -0,0 +1,117 @@
+import mimetypes
+from typing import Union, Optional
+from pathlib import Path
+
+import httpx
+import aiofiles
+
+from aymara_ai import AymaraAI, AsyncAymaraAI
+from aymara_ai.types.shared_params import FileReference
+
+
+def _default_file_name(content_type: Optional[str]) -> str:
+    if content_type:
+        ext = mimetypes.guess_extension(content_type)
+        if ext:
+            return f"file{ext}"
+        # fallback if extension can't be guessed
+        return "file.bin"
+    return "file.png"
+
+
+def upload_file(
+    client: Optional[AymaraAI] = None,
+    http_client: Optional[httpx.Client] = None,
+    file_name: Optional[str] = None,
+    file_content: Union[Path, bytes, None] = None,
+    content_type: Optional[str] = None,
+) -> FileReference:
+    """
+    Helper to upload file content (from Path or bytes) and return (FileReference).
+    Both client and http_client are optional and will be constructed if not provided.
+    file_name is optional and will be defaulted based on content_type or to 'file.png'.
+    content_type is optional and will be guessed from file_name if not provided.
+    """
+    if client is None:
+        client = AymaraAI()
+    close_http_client = False
+    if http_client is None:
+        http_client = httpx.Client()
+        close_http_client = True
+
+    try:
+        # Determine file_name
+        if file_name is None:
+            file_name = _default_file_name(content_type)
+        # Determine content_type
+        mime_type = content_type or mimetypes.guess_type(file_name)[0] or "application/octet-stream"
+        headers = {"Content-Type": mime_type}
+
+        upload_resp = client.files.create(files=[{"local_file_path": file_name}])
+        file_info = upload_resp.files[0]
+        if not file_info.file_url:
+            raise RuntimeError("No presigned file_url returned for upload.")
+
+        if isinstance(file_content, Path):
+            with open(str(file_content), "rb") as f:
+                put_resp = http_client.put(file_info.file_url, content=f, headers=headers)
+                put_resp.raise_for_status()
+        elif isinstance(file_content, bytes):
+            put_resp = http_client.put(file_info.file_url, content=file_content, headers=headers)
+            put_resp.raise_for_status()
+        else:
+            raise ValueError("Unsupported file_content type for upload.")
+        return FileReference(remote_file_path=file_info.remote_file_path)
+    finally:
+        if close_http_client:
+            http_client.close()
+
+
+async def upload_file_async(
+    client: Optional[AsyncAymaraAI] = None,
+    http_client: Optional[httpx.AsyncClient] = None,
+    file_name: Optional[str] = None,
+    file_content: Union[Path, bytes, None] = None,
+    content_type: Optional[str] = None,
+) -> FileReference:
+    """
+    Async helper to upload file content (from Path or bytes) and return (FileReference).
+    Both client and http_client are optional and will be constructed if not provided.
+    file_name is optional and will be defaulted based on content_type or to 'file.png'.
+    content_type is optional and will be guessed from file_name if not provided.
+    """
+    if client is None:
+        client = AsyncAymaraAI()
+    close_http_client = False
+    if http_client is None:
+        http_client = httpx.AsyncClient()
+        close_http_client = True
+
+    try:
+        # Determine file_name
+        if file_name is None:
+            file_name = _default_file_name(content_type)
+        # Determine content_type
+        mime_type = content_type or mimetypes.guess_type(file_name)[0] or "application/octet-stream"
+        headers = {"Content-Type": mime_type}
+
+        upload_resp = await client.files.create(files=[{"local_file_path": file_name}])
+        file_info = upload_resp.files[0]
+        if not file_info.file_url:
+            raise RuntimeError("No presigned file_url returned for upload.")
+
+        if isinstance(file_content, Path):
+            async with aiofiles.open(str(file_content), mode="rb") as f:
+                put_resp = await http_client.put(file_info.file_url, content=f, headers=headers)
+                if put_resp.status_code != 200:
+                    raise RuntimeError(f"Failed to upload file: {put_resp.status_code}")
+        elif isinstance(file_content, bytes):
+            put_resp = await http_client.put(file_info.file_url, content=file_content, headers=headers)
+            if put_resp.status_code != 200:
+                raise RuntimeError(f"Failed to upload file: {put_resp.status_code}")
+        else:
+            raise ValueError("Unsupported file_content type for upload.")
+        return FileReference(remote_file_path=file_info.remote_file_path)
+    finally:
+        if close_http_client:
+            await http_client.aclose()

Original file line number	Diff line number	Diff line change
`@@ -1,3 +1,3 @@`
`1`	`1`	`{`
`2`		`- ".": "1.0.0-alpha.12"`
	`2`	`+ ".": "1.0.0-alpha.13"`
`3`	`3`	`}`