fix import errors

Author: iamlemec

oneping/curl.py

@@ -222,7 +222,7 @@ async def stream_async(query, provider=DEFAULT_PROVIDER, history=None, prefill=N
 ## embeddings
 ##
 
-def embed(text, provider=DEFAULT_PROVIDER, base_url=None, path=None, api_key=None, model=None, **kwargs):
+def embed(text, provider=DEFAULT_PROVIDER, base_url=None, path=None, api_key=None, model=None, timeout=None, **kwargs):
     # get provider details
     prov = get_provider(provider)
     url = prepare_url(prov, f'embed_path', base_url=base_url, path=path)
@@ -240,7 +240,7 @@ def embed(text, provider=DEFAULT_PROVIDER, base_url=None, path=None, api_key=Non
     payload = {**payload_model, **payload_message, **kwargs}
 
     # make the request
-    response = requests.post(url, headers=headers, data=json.dumps(payload))
+    response = requests.post(url, headers=headers, data=json.dumps(payload), timeout=timeout)
     response.raise_for_status()
 
     # extract result
@@ -250,7 +250,7 @@ def embed(text, provider=DEFAULT_PROVIDER, base_url=None, path=None, api_key=Non
     # return result
     return result
 
-def tokenize(text, provider=DEFAULT_PROVIDER, base_url=None, path=None, api_key=None, model=None, **kwargs):
+def tokenize(text, provider=DEFAULT_PROVIDER, base_url=None, path=None, api_key=None, model=None, timeout=None, **kwargs):
     # get provider details
     prov = get_provider(provider)
     url = prepare_url(prov, 'tokenize_path', base_url=base_url, path=path)
@@ -268,7 +268,7 @@ def tokenize(text, provider=DEFAULT_PROVIDER, base_url=None, path=None, api_key=
     payload = {**payload_model, **payload_message, **kwargs}
 
     # make the request
-    response = requests.post(url, headers=headers, data=json.dumps(payload))
+    response = requests.post(url, headers=headers, data=json.dumps(payload), timeout=timeout)
     response.raise_for_status()
 
     # extract result

oneping/native/azure.py

@@ -7,7 +7,7 @@
     DEFAULT_SYSTEM, OPENAI_MODEL, OPENAI_EMBED, OPENAI_TRANSCRIBE, AZURE_API_VERSION, AZURE_KEYENV,
     content_openai, convert_history, payload_openai,
     response_openai_native, stream_openai_native,
-    embed_openai, transcribe_openai
+    embed_response_openai, transcribe_response_openai
 )
 
 ##
@@ -71,11 +71,11 @@ def embed(
 ):
     client = make_client(azure_endpoint, azure_deployment=azure_deployment, api_version=api_version, api_key=api_key)
     response = client.embeddings.create(model=model, **kwargs)
-    return embed_openai(response)
+    return embed_response_openai(response)
 
 def transcribe(
     audio, model=OPENAI_TRANSCRIBE, azure_endpoint=None, azure_deployment=None, api_version=AZURE_API_VERSION, api_key=None, **kwargs
 ):
     client = make_client(azure_endpoint, azure_deployment=azure_deployment, api_version=api_version, api_key=api_key)
     response = client.audio.transcriptions.create(model=model, file=audio, **kwargs)
-    return transcribe_openai(response)
+    return transcribe_response_openai(response)

oneping/native/openai.py

@@ -7,7 +7,7 @@
     DEFAULT_SYSTEM, OPENAI_MODEL, OPENAI_EMBED, OPENAI_TRANSCRIBE, OPENAI_KEYENV,
     content_openai, convert_history, payload_openai,
     response_openai_native, stream_openai_native,
-    embed_openai, transcribe_openai
+    embed_response_openai, transcribe_response_openai
 )
 
 ##
@@ -23,10 +23,10 @@ def make_payload(query, image=None, prediction=None, system=None, history=None):
 ## common interface
 ##
 
-def make_client(api_key=None, async_client=False):
+def make_client(api_key=None, async_client=False, base_url=None):
     api_key = api_key if api_key is not None else os.environ.get(OPENAI_KEYENV)
     client_class = openai.AsyncOpenAI if async_client else openai.OpenAI
-    return client_class(api_key=api_key)
+    return client_class(api_key=api_key, base_url=base_url)
 
 def reply(query, image=None, history=None, prefill=None, prediction=None, system=DEFAULT_SYSTEM, api_key=None, model=OPENAI_MODEL, max_tokens=None, base_url=None, **kwargs):
     client = make_client(api_key=api_key, base_url=base_url)
@@ -57,9 +57,9 @@ async def stream_async(query, image=None, history=None, prefill=None, prediction
 def embed(query, model=OPENAI_EMBED, api_key=None, base_url=None, **kwargs):
     client = make_client(api_key=api_key, base_url=base_url)
     response = client.embeddings.create(query, model=model, **kwargs)
-    return embed_openai(response)
+    return embed_response_openai(response)
 
 def transcribe(audio, model=OPENAI_TRANSCRIBE, api_key=None, base_url=None, **kwargs):
     client = make_client(api_key=api_key, base_url=base_url)
     response = client.audio.transcriptions.create(audio, model=model, **kwargs)
-    return transcribe_openai(response)
+    return transcribe_response_openai(response)

oneping/providers.py

@@ -15,10 +15,10 @@
 ## models
 ##
 
-OPENAI_MODEL = 'gpt-4o'
+OPENAI_MODEL = 'gpt-5'
 OPENAI_EMBED = 'text-embedding-3-large'
-OPENAI_TRANSCRIBE = 'gpt-4o-transcribe'
-ANTHROPIC_MODEL = 'claude-3-7-sonnet-latest'
+OPENAI_TRANSCRIBE = 'gpt-5-transcribe'
+ANTHROPIC_MODEL = 'claude-opus-4-1-20250805'
 FIREWORKS_MODEL = 'accounts/fireworks/models/llama-v3p3-70b-instruct'
 GROQ_MODEL = 'llama-3.3-70b-versatile'
 DEEPSEEK_MODEL = 'deepseek-chat'
@@ -212,7 +212,9 @@ def embed_payload_openai(text):
     return {'input': text}
 
 def embed_response_openai(reply):
-    return reply['data'][0]['embedding']
+    return [
+        item['embedding'] for item in reply['data']
+    ]
 
 def embed_payload_tei(text):
     return {'inputs': text}
@@ -248,7 +250,7 @@ def tokenize_response_vllm(reply):
 ## transcribe handlers
 ##
 
-def transcribe_openai(audio):
+def transcribe_response_openai(audio):
     return audio.text
 
 ##