ref(lint)

deepinfra/constants/client.py

@@ -3,7 +3,7 @@
 """
 
 MAX_RETRIES = 5
-INITIAL_BACKOFF = 5000
-SUBSEQUENT_BACKOFF = 2000
+INITIAL_BACKOFF = 5
+SUBSEQUENT_BACKOFF = 2
 USER_AGENT = "DeepInfra Python API Client"
 ROOT_URL = "https://api.deepinfra.com/v1/inference/"

deepinfra/models/base/automatic_speech_recognition.py

@@ -26,4 +26,4 @@ def generate(self, body) -> AutomaticSpeechRecognitionResponse:
         response = self.client.post(
             form_data, {"headers": {"content-type": form_data.content_type}}
         )
-        return response.json()
+        return AutomaticSpeechRecognitionResponse(**response.json())

deepinfra/models/base/embeddings.py

@@ -1,5 +1,6 @@
+import json
+
 from deepinfra.models.base import BaseModel
-from deepinfra.types.embeddings.request import EmbeddingsRequest
 from deepinfra.types.embeddings.response import EmbeddingsResponse
 
 
@@ -14,5 +15,5 @@ def generate(self, body) -> EmbeddingsResponse:
         :param body:
         :return:
         """
-        response = self.client.post(body)
-        return response.json()
+        response = self.client.post(json.dumps(body))
+        return EmbeddingsResponse(**response.json())

deepinfra/models/base/text_generation.py

@@ -3,6 +3,7 @@
     which is the base class for all text generation models.
 """
 
+import json
 from typing import Union
 
 from deepinfra.models.base import BaseModel
@@ -22,5 +23,5 @@ def generate(self, body: dict) -> TextGenerationResponse:
         :param body:
         :return:
         """
-        response = self.client.post(body)
-        return response.json()
+        response = self.client.post(json.dumps(body))
+        return TextGenerationResponse(**response.json())

deepinfra/models/base/text_to_image.py

@@ -1,3 +1,5 @@
+import json
+
 from deepinfra.models.base import BaseModel
 from deepinfra.types.text_to_image import TextToImageResponse
 
@@ -8,12 +10,12 @@ class TextToImage(BaseModel):
     @docs Check the available models at https://deepinfra.com/models/text-to-image
     """
 
-    def generate(self, input):
+    def generate(self, input) -> TextToImageResponse:
         """
         Generates an image.
         :param input:
         :return:
         """
         body = {"input": input}
-        response = self.client.post(body)
-        return response.json()
+        response = self.client.post(json.dumps(input))
+        return TextToImageResponse(**response.json())

deepinfra/types/text_generation/response.py

@@ -1,5 +1,5 @@
 from dataclasses import dataclass
-from typing import List
+from typing import List, Optional
 
 from deepinfra.types.common.inference_status import InferenceStatus
 
@@ -11,7 +11,6 @@ class GeneratedText:
 
 @dataclass
 class TextGenerationResponse:
-    request_id: str
     inference_status: InferenceStatus
     results: List[GeneratedText]
     num_tokens: int

deepinfra/types/text_to_image/response.py

@@ -13,16 +13,9 @@ class Metrics:
 class TextToImageResponse:
     request_id: str
     inference_status: InferenceStatus
-    input: Dict
-    output: List[str]
-    id: str
-    started_at: str
-    completed_at: str
-    logs: str
-    status: str
-    metrics: Metrics
-    webhook_events_filter: List[str]
-    output_file_prefix: str
+    images: List[str]
+    nsfw_content_detected: bool
+    seed: str
     version: Optional[str] = None
     created_at: Optional[str] = None
     error: Optional[str] = None

tests/test_automatic_speech_recognition.py

@@ -11,7 +11,15 @@ class TestAutomaticSpeechRecognition(unittest.TestCase):
     @patch("requests.post")
     def test_generate(self, mock_post):
         mock_post.return_value.status_code = 200
-        mock_post.return_value.json.return_value = {"text": "Hello, World!"}
+        mock_post.return_value.json.return_value = {
+            "text": "Hello, World!",
+            "segments": [{"start": 0, "end": 1, "text": "Hello"}],
+            "language": "en",
+            "input_length_ms": 1000,
+            "request_id": "123",
+            "inference_status": None,
+        }
+
         audio_data = b"audio data"
         asr = AutomaticSpeechRecognition(model_name, api_key)
         body = {"audio": audio_data}
@@ -24,4 +32,4 @@ def test_generate(self, mock_post):
         called_headers = called_kwargs["headers"]
         self.assertEqual(called_headers["Authorization"], f"Bearer {api_key}")
 
-        self.assertEqual(response["text"], "Hello, World!")
+        self.assertEqual(response.text, "Hello, World!")

tests/test_embeddings.py

@@ -11,7 +11,11 @@ class TestEmbeddings(unittest.TestCase):
     @patch("requests.post")
     def test_generate(self, mock_post):
         mock_post.return_value.status_code = 200
-        mock_post.return_value.json.return_value = {"embeddings": [1, 2, 3]}
+        mock_post.return_value.json.return_value = {
+            "embeddings": [1, 2, 3],
+            "input_tokens": 123,
+            "inference_status": None,
+        }
 
         embeddings = Embeddings(model_name, api_key)
         body = {"text": "Hello, World!"}
@@ -20,7 +24,9 @@ def test_generate(self, mock_post):
         called_args, called_kwargs = mock_post.call_args
         url = called_args[0]
         header = called_kwargs["headers"]
-        self.assertEqual(url, f"https://api.deepinfra.com/v1/inference/{model_name}")
+        body = called_kwargs["data"]
 
-        self.assertEqual(response["embeddings"], [1, 2, 3])
+        self.assertEqual(url, f"https://api.deepinfra.com/v1/inference/{model_name}")
+        self.assertEqual(body, '{"text": "Hello, World!"}')
+        self.assertEqual(response.embeddings, [1, 2, 3])
         self.assertEqual(header["Authorization"], f"Bearer {api_key}")

tests/test_text_generation.py

@@ -10,8 +10,14 @@
 class TestTextGeneration(unittest.TestCase):
     @patch("requests.post")
     def test_generate(self, mock_post):
+
         mock_post.return_value.status_code = 200
-        mock_post.return_value.json.return_value = {"text": "Hello, World!"}
+        mock_post.return_value.json.return_value = {
+            "results": [],
+            "num_tokens": 0,
+            "num_input_tokens": 0,
+            "inference_status": None,
+        }
 
         text_generation = TextGeneration(model_name, api_key)
         body = {"text": "Hello, World!"}
@@ -22,5 +28,5 @@ def test_generate(self, mock_post):
         header = called_kwargs["headers"]
         self.assertEqual(url, f"https://api.deepinfra.com/v1/inference/{model_name}")
 
-        self.assertEqual(response["text"], "Hello, World!")
+        self.assertEqual(response.results, [])
         self.assertEqual(header["Authorization"], f"Bearer {api_key}")

tests/test_text_to_image.py

@@ -11,7 +11,17 @@ class TestTextToImage(unittest.TestCase):
     @patch("requests.post")
     def test_generate(self, mock_post):
         mock_post.return_value.status_code = 200
-        mock_post.return_value.json.return_value = {"image": "image data"}
+        images = ["image data"]
+
+        mock_post.return_value.json.return_value = {
+            "request_id": "123",
+            "inference_status": None,
+            "images": images,
+            "nsfw_content_detected": False,
+            "seed": "seed",
+            "version": "1.0",
+            "created_at": "2022-01-01",
+        }
 
         text_to_image = TextToImage(model_name, api_key)
         body = {"text": "Hello, World!"}
@@ -22,5 +32,5 @@ def test_generate(self, mock_post):
         header = called_kwargs["headers"]
         self.assertEqual(url, f"https://api.deepinfra.com/v1/inference/{model_name}")
 
-        self.assertEqual(response["image"], "image data")
+        self.assertEqual(response.images, images)
         self.assertEqual(header["Authorization"], f"Bearer {api_key}")