forked from phoenix/litellm-mirror
fix import baseten + petals test
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3e09743173
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2 changed files with 25 additions and 26 deletions
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@ -432,7 +432,6 @@ def completion(
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# assume all responses are streamed
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return generator
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elif custom_llm_provider == "baseten" or litellm.api_base=="https://app.baseten.co":
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install_and_import("baseten")
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import baseten
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base_ten_key = get_secret('BASETEN_API_KEY')
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baseten.login(base_ten_key)
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@ -457,36 +456,25 @@ def completion(
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model_response["model"] = model
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response = model_response
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elif custom_llm_provider == "petals":
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install_and_import("transformers")
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from transformers import AutoTokenizer
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from petals import AutoDistributedModelForCausalLM
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elif custom_llm_provider == "petals" or "chat.petals.dev" in litellm.api_base:
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url = "https://chat.petals.dev/api/v1/generate"
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import requests
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prompt = " ".join([message["content"] for message in messages])
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response = requests.post(url, data={"inputs": prompt, "max_new_tokens": 100, "model": model})
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tokenizer = AutoTokenizer.from_pretrained(model)
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model = AutoDistributedModelForCausalLM.from_pretrained(model)
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## LOGGING
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#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)
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print("got model", model)
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#response.text
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print("got response", response.json())
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print("got response text", response.text)
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# Embeddings & prompts are on your device, transformer blocks are distributed across the Internet
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inputs = tokenizer(prompt, return_tensors="pt")["input_ids"]
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outputs = model.generate(
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inputs=inputs,
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max_new_tokens=5
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)
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print("got output", outputs)
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completion_response = tokenizer.decode(outputs[0])
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print("got output text", completion_response)
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## LOGGING
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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)
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## RESPONSE OBJECT
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model_response["choices"][0]["message"]["content"] = completion_response
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model_response["created"] = time.time()
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model_response["model"] = model
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response = model_response
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# model_response["choices"][0]["message"]["content"] = completion_response
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# model_response["created"] = time.time()
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# model_response["model"] = model
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# response = model_response
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else:
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## LOGGING
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logging(model=model, input=messages, custom_llm_provider=custom_llm_provider, logger_fn=logger_fn)
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@ -213,6 +213,17 @@ def test_completion_together_ai_stream():
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# def test_petals():
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# model_name = "stabilityai/StableBeluga2"
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# try:
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# response = completion(model=model_name, messages=messages, custom_llm_provider="petals")
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# # Add any assertions here to check the response
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# print(response)
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# # test_petals()
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# def test_baseten_falcon_7bcompletion():
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# model_name = "qvv0xeq"
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# try:
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