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fix import baseten + petals test

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ishaan-jaff 2023-08-15 13:57:13 -07:00
parent 3e09743173
commit f336dafd04
2 changed files with 25 additions and 26 deletions
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40
litellm/main.py
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@ -432,7 +432,6 @@ def completion(
# assume all responses are streamed # assume all responses are streamed
return generator return generator
elif custom_llm_provider == "baseten" or litellm.api_base=="https://app.baseten.co": elif custom_llm_provider == "baseten" or litellm.api_base=="https://app.baseten.co":
install_and_import("baseten")
import baseten import baseten
base_ten_key = get_secret('BASETEN_API_KEY') base_ten_key = get_secret('BASETEN_API_KEY')
baseten.login(base_ten_key) baseten.login(base_ten_key)
@ -457,36 +456,25 @@ def completion(
model_response["model"] = model model_response["model"] = model
response = model_response response = model_response
elif custom_llm_provider == "petals": elif custom_llm_provider == "petals" or "chat.petals.dev" in litellm.api_base:
install_and_import("transformers") url = "https://chat.petals.dev/api/v1/generate"
from transformers import AutoTokenizer import requests
from petals import AutoDistributedModelForCausalLM prompt = " ".join([message["content"] for message in messages])
response = requests.post(url, data={"inputs": prompt, "max_new_tokens": 100, "model": model})
tokenizer = AutoTokenizer.from_pretrained(model) ## LOGGING
model = AutoDistributedModelForCausalLM.from_pretrained(model) #logging(model=model, input=prompt, custom_llm_provider=custom_llm_provider, additional_args={"max_tokens": max_tokens, "original_response": completion_response}, logger_fn=logger_fn)
print("got model", model) #response.text
print("got response", response.json())
print("got response text", response.text)
# Embeddings & prompts are on your device, transformer blocks are distributed across the Internet # Embeddings & prompts are on your device, transformer blocks are distributed across the Internet
inputs = tokenizer(prompt, return_tensors="pt")["input_ids"]
outputs = model.generate(
inputs=inputs,
max_new_tokens=5
)
print("got output", outputs)
completion_response = tokenizer.decode(outputs[0])
print("got output text", completion_response)
## LOGGING
logging(model=model, input=prompt, custom_llm_provider=custom_llm_provider, additional_args={"max_tokens": max_tokens, "original_response": completion_response}, logger_fn=logger_fn)
## RESPONSE OBJECT ## RESPONSE OBJECT
model_response["choices"][0]["message"]["content"] = completion_response # model_response["choices"][0]["message"]["content"] = completion_response
model_response["created"] = time.time() # model_response["created"] = time.time()
model_response["model"] = model # model_response["model"] = model
response = model_response # response = model_response
else: else:
## LOGGING ## LOGGING
logging(model=model, input=messages, custom_llm_provider=custom_llm_provider, logger_fn=logger_fn) logging(model=model, input=messages, custom_llm_provider=custom_llm_provider, logger_fn=logger_fn)

11
litellm/tests/test_completion.py
View file

@ -213,6 +213,17 @@ def test_completion_together_ai_stream():
except Exception as e: except Exception as e:
pytest.fail(f"Error occurred: {e}") pytest.fail(f"Error occurred: {e}")
# def test_petals():
# model_name = "stabilityai/StableBeluga2"
# try:
# response = completion(model=model_name, messages=messages, custom_llm_provider="petals")
# # Add any assertions here to check the response
# print(response)
# except Exception as e:
# pytest.fail(f"Error occurred: {e}")
# # test_petals()
# def test_baseten_falcon_7bcompletion(): # def test_baseten_falcon_7bcompletion():
# model_name = "qvv0xeq" # model_name = "qvv0xeq"
# try: # try: