adding support for timeouts

predictionguard/client.py

@@ -1,7 +1,7 @@
 import os
 
 import requests
-from typing import Optional
+from typing import Optional, Union
 
 from .src.audio import Audio
 from .src.chat import Chat
@@ -30,11 +30,15 @@ class PredictionGuard:
     """PredictionGuard provides access the Prediction Guard API."""
 
     def __init__(
-        self, api_key: Optional[str] = None, url: Optional[str] = None
+        self,
+        api_key: Optional[str] = None,
+        url: Optional[str] = None,
+        timeout: Optional[Union[int, float]] = None
     ) -> None:
         """
         :param api_key: api_key represents PG api key.
         :param url: url represents the transport and domain:port
+        :param timeout: request timeout in seconds.
         """
 
         # Get the access api_key.
@@ -56,50 +60,67 @@ def __init__(
             url = "https://api.predictionguard.com"
         self.url = url
 
+        if not timeout:
+            timeout = os.environ.get("TIMEOUT")
+        if not timeout:
+            timeout = None
+        if timeout:
+            try:
+                timeout = float(timeout)
+            except ValueError:
+                raise ValueError(
+                    "Timeout must be of type integer or float, not %s." % (type(timeout).__name__,)
+                )
+            except TypeError:
+                raise TypeError(
+                    "Timeout should be of type integer or float, not %s." % (type(timeout).__name__,)
+                )
+        self.timeout = timeout
+
         # Connect to Prediction Guard and set the access api_key.
         self._connect_client()
 
         # Pass Prediction Guard class variables to inner classes
-        self.chat: Chat = Chat(self.api_key, self.url)
+        self.chat: Chat = Chat(self.api_key, self.url, self.timeout)
         """Chat generates chat completions based on a conversation history"""
 
-        self.completions: Completions = Completions(self.api_key, self.url)
+        self.completions: Completions = Completions(self.api_key, self.url, self.timeout)
         """Completions generates text completions based on the provided input"""
 
-        self.embeddings: Embeddings = Embeddings(self.api_key, self.url)
+        self.embeddings: Embeddings = Embeddings(self.api_key, self.url, self.timeout)
         """Embedding generates chat completions based on a conversation history."""
 
-        self.audio: Audio = Audio(self.api_key, self.url)
+        self.audio: Audio = Audio(self.api_key, self.url, self.timeout)
         """Audio allows for the transcription of audio files."""
 
-        self.documents: Documents = Documents(self.api_key, self.url)
+        self.documents: Documents = Documents(self.api_key, self.url, self.timeout)
         """Documents allows you to extract text from various document file types."""
 
-        self.rerank: Rerank = Rerank(self.api_key, self.url)
+        self.rerank: Rerank = Rerank(self.api_key, self.url, self.timeout)
         """Rerank sorts text inputs by semantic relevance to a specified query."""
 
-        self.translate: Translate = Translate(self.api_key, self.url)
+        self.translate: Translate = Translate(self.api_key, self.url, self.timeout)
         """Translate converts text from one language to another."""
 
-        self.factuality: Factuality = Factuality(self.api_key, self.url)
+        self.factuality: Factuality = Factuality(self.api_key, self.url, self.timeout)
         """Factuality checks the factuality of a given text compared to a reference."""
 
-        self.toxicity: Toxicity = Toxicity(self.api_key, self.url)
+        self.toxicity: Toxicity = Toxicity(self.api_key, self.url, self.timeout)
         """Toxicity checks the toxicity of a given text."""
 
-        self.pii: Pii = Pii(self.api_key, self.url)
+        self.pii: Pii = Pii(self.api_key, self.url, self.timeout)
         """Pii replaces personal information such as names, SSNs, and emails in a given text."""
 
-        self.injection: Injection = Injection(self.api_key, self.url)
+        self.injection: Injection = Injection(self.api_key, self.url, self.timeout)
         """Injection detects potential prompt injection attacks in a given prompt."""
 
-        self.tokenize: Tokenize = Tokenize(self.api_key, self.url)
+        self.tokenize: Tokenize = Tokenize(self.api_key, self.url, self.timeout)
         """Tokenize generates tokens for input text."""
 
-        self.detokenize: Detokenize = Detokenize(self.api_key, self.url)
+        self.detokenize: Detokenize = Detokenize(self.api_key, self.url, self.timeout)
         """Detokenizes generates text for input tokens."""
 
-        self.models: Models = Models(self.api_key, self.url)
+        self.models: Models = Models(self.api_key, self.url, self.timeout)
         """Models lists all of the models available in the Prediction Guard API."""
 
     def _connect_client(self) -> None:
@@ -112,7 +133,7 @@ def _connect_client(self) -> None:
         }
 
         # Try listing models to make sure we can connect.
-        response = requests.request("GET", self.url + "/completions", headers=headers)
+        response = requests.request("GET", self.url + "/completions", headers=headers, timeout=self.timeout)
 
         # If the connection was unsuccessful, raise an exception.
         if response.status_code == 200:

predictionguard/src/audio.py

@@ -39,16 +39,18 @@ class Audio:
         ))
     """
 
-    def __init__(self, api_key, url):
+    def __init__(self, api_key, url, timeout):
         self.api_key = api_key
         self.url = url
+        self.timeout = timeout
 
-        self.transcriptions: AudioTranscriptions = AudioTranscriptions(self.api_key, self.url)
+        self.transcriptions: AudioTranscriptions = AudioTranscriptions(self.api_key, self.url, self.timeout)
 
 class AudioTranscriptions:
-    def __init__(self, api_key, url):
+    def __init__(self, api_key, url, timeout):
         self.api_key = api_key
         self.url = url
+        self.timeout = timeout
 
     def create(
         self,
@@ -164,7 +166,7 @@ def _transcribe_audio(
             }
 
             response = requests.request(
-                "POST", self.url + "/audio/transcriptions", headers=headers, files=files, data=data
+                "POST", self.url + "/audio/transcriptions", headers=headers, files=files, data=data, timeout=self.timeout
             )
 
         # If the request was successful, print the proxies.

predictionguard/src/chat.py

@@ -66,17 +66,19 @@ class Chat:
         ))
     """
 
-    def __init__(self, api_key, url):
+    def __init__(self, api_key, url, timeout):
         self.api_key = api_key
         self.url = url
+        self.timeout = timeout
 
-        self.completions: ChatCompletions = ChatCompletions(self.api_key, self.url)
+        self.completions: ChatCompletions = ChatCompletions(self.api_key, self.url, self.timeout)
 
 
 class ChatCompletions:
-    def __init__(self, api_key, url):
+    def __init__(self, api_key, url, timeout):
         self.api_key = api_key
         self.url = url
+        self.timeout = timeout
 
     def create(
         self,
@@ -192,9 +194,9 @@ def _generate_chat(
         Function to generate a single chat response.
         """
 
-        def return_dict(url, headers, payload):
+        def return_dict(url, headers, payload, timeout):
             response = requests.request(
-                "POST", url + "/chat/completions", headers=headers, data=payload
+                "POST", url + "/chat/completions", headers=headers, data=payload, timeout=timeout
             )
             # If the request was successful, print the proxies.
             if response.status_code == 200:
@@ -215,12 +217,13 @@ def return_dict(url, headers, payload):
                     pass
                 raise ValueError("Could not make prediction. " + err)
 
-        def stream_generator(url, headers, payload, stream):
+        def stream_generator(url, headers, payload, stream, timeout):
             with requests.post(
                 url + "/chat/completions",
                 headers=headers,
                 data=payload,
                 stream=stream,
+                timeout=timeout,
             ) as response:
                 response.raise_for_status()
 
@@ -356,10 +359,10 @@ def stream_generator(url, headers, payload, stream):
         payload = json.dumps(payload_dict)
 
         if stream:
-            return stream_generator(self.url, headers, payload, stream)
+            return stream_generator(self.url, headers, payload, stream, self.timeout)
 
         else:
-            return return_dict(self.url, headers, payload)
+            return return_dict(self.url, headers, payload, self.timeout)
 
     def list_models(self, capability: Optional[str] = "chat-completion") -> List[str]:
         # Get the list of current models.
@@ -376,7 +379,7 @@ def list_models(self, capability: Optional[str] = "chat-completion") -> List[str
         else:
             model_path = "/models/" + capability
 
-        response = requests.request("GET", self.url + model_path, headers=headers)
+        response = requests.request("GET", self.url + model_path, headers=headers, timeout=self.timeout)
 
         response_list = []
         for model in response.json()["data"]:

predictionguard/src/completions.py

@@ -41,9 +41,10 @@ class Completions:
         ))
     """
 
-    def __init__(self, api_key, url):
+    def __init__(self, api_key, url, timeout):
         self.api_key = api_key
         self.url = url
+        self.timeout = timeout
 
     def create(
         self,
@@ -132,9 +133,9 @@ def _generate_completion(
         Function to generate a single completion.
         """
 
-        def return_dict(url, headers, payload):
+        def return_dict(url, headers, payload, timeout):
             response = requests.request(
-                "POST", url + "/completions", headers=headers, data=payload
+                "POST", url + "/completions", headers=headers, data=payload, timeout=timeout
             )
             # If the request was successful, print the proxies.
             if response.status_code == 200:
@@ -155,12 +156,13 @@ def return_dict(url, headers, payload):
                     pass
                 raise ValueError("Could not make prediction. " + err)
 
-        def stream_generator(url, headers, payload, stream):
+        def stream_generator(url, headers, payload, stream, timeout):
             with requests.post(
                 url + "/completions",
                 headers=headers,
                 data=payload,
                 stream=stream,
+                timeout=timeout
             ) as response:
                 response.raise_for_status()
 
@@ -215,10 +217,10 @@ def stream_generator(url, headers, payload, stream):
         payload = json.dumps(payload_dict)
 
         if stream:
-            return stream_generator(self.url, headers, payload, stream)
+            return stream_generator(self.url, headers, payload, stream, self.timeout)
 
         else:
-            return return_dict(self.url, headers, payload)
+            return return_dict(self.url, headers, payload, self.timeout)
 
     def list_models(self) -> List[str]:
         # Get the list of current models.
@@ -228,7 +230,7 @@ def list_models(self) -> List[str]:
             "User-Agent": "Prediction Guard Python Client: " + __version__,
         }
 
-        response = requests.request("GET", self.url + "/models/completion", headers=headers)
+        response = requests.request("GET", self.url + "/models/completion", headers=headers, timeout=self.timeout)
 
         response_list = []
         for model in response.json()["data"]:

predictionguard/src/detokenize.py

@@ -41,9 +41,10 @@ class Detokenize:
         """
 
 
-    def __init__(self, api_key, url):
+    def __init__(self, api_key, url, timeout):
         self.api_key = api_key
         self.url = url
+        self.timeout = timeout
 
     def create(self, model: str, tokens: List[int]) -> Dict[str, Any]:
         """
@@ -85,7 +86,7 @@ def _create_tokens(self, model, tokens):
         payload = json.dumps(payload)
 
         response = requests.request(
-            "POST", self.url + "/detokenize", headers=headers, data=payload
+            "POST", self.url + "/detokenize", headers=headers, data=payload, timeout=self.timeout
         )
 
         if response.status_code == 200:
@@ -114,7 +115,7 @@ def list_models(self):
                 "User-Agent": "Prediction Guard Python Client: " + __version__
                 }
 
-        response = requests.request("GET", self.url + "/models/detokenize", headers=headers)
+        response = requests.request("GET", self.url + "/models/detokenize", headers=headers, timeout=self.timeout)
 
         response_list = []
         for model in response.json()["data"]:

predictionguard/src/documents.py

@@ -37,16 +37,18 @@ class Documents:
         ))
     """
 
-    def __init__(self, api_key, url):
+    def __init__(self, api_key, url, timeout):
         self.api_key = api_key
         self.url = url
+        self.timeout = timeout
 
-        self.extract: DocumentsExtract = DocumentsExtract(self.api_key, self.url)
+        self.extract: DocumentsExtract = DocumentsExtract(self.api_key, self.url, self.timeout)
 
 class DocumentsExtract:
-    def __init__(self, api_key, url):
+    def __init__(self, api_key, url, timeout):
         self.api_key = api_key
         self.url = url
+        self.timeout = timeout
 
     def create(
         self,
@@ -117,7 +119,7 @@ def _extract_documents(
 
             response = requests.request(
                 "POST", self.url + "/documents/extract",
-                headers=headers, files=files, data=data
+                headers=headers, files=files, data=data, timeout=self.timeout
             )
 
         # If the request was successful, print the proxies.

predictionguard/src/embeddings.py

@@ -46,9 +46,10 @@ class Embeddings:
         ))
     """
 
-    def __init__(self, api_key, url):
+    def __init__(self, api_key, url, timeout):
         self.api_key = api_key
         self.url = url
+        self.timeout = timeout
 
     def create(
         self,
@@ -166,7 +167,7 @@ def _generate_embeddings(self, model, input, truncate, truncation_direction):
 
         payload = json.dumps(payload_dict)
         response = requests.request(
-            "POST", self.url + "/embeddings", headers=headers, data=payload
+            "POST", self.url + "/embeddings", headers=headers, data=payload, timeout=self.timeout
         )
 
         # If the request was successful, print the proxies.
@@ -204,7 +205,7 @@ def list_models(self, capability: Optional[str] = "embedding") -> List[str]:
         else:
             model_path = "/models/" + capability
 
-        response = requests.request("GET", self.url + model_path, headers=headers)
+        response = requests.request("GET", self.url + model_path, headers=headers, timeout=self.timeout)
 
         response_list = []
         for model in response.json()["data"]:

predictionguard/src/factuality.py

@@ -41,9 +41,10 @@ class Factuality:
         ))
     """
 
-    def __init__(self, api_key, url):
+    def __init__(self, api_key, url, timeout):
         self.api_key = api_key
         self.url = url
+        self.timeout = timeout
 
     def check(self, reference: str, text: str) -> Dict[str, Any]:
         """
@@ -72,7 +73,7 @@ def _generate_score(self, reference, text):
         payload_dict = {"reference": reference, "text": text}
         payload = json.dumps(payload_dict)
         response = requests.request(
-            "POST", self.url + "/factuality", headers=headers, data=payload
+            "POST", self.url + "/factuality", headers=headers, data=payload, timeout=self.timeout
         )
 
         # If the request was successful, print the proxies.