litellmlope / litellm /tests /test_hf_prompt_templates.py
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import sys, os
import traceback
from dotenv import load_dotenv
load_dotenv()
import os
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
import pytest
from litellm.llms.prompt_templates.factory import prompt_factory
def test_prompt_formatting():
try:
prompt = prompt_factory(
model="mistralai/Mistral-7B-Instruct-v0.1",
messages=[
{"role": "system", "content": "Be a good bot"},
{"role": "user", "content": "Hello world"},
],
)
assert (
prompt == "<s>[INST] Be a good bot [/INST]</s> [INST] Hello world [/INST]"
)
except Exception as e:
pytest.fail(f"An exception occurred: {str(e)}")
def test_prompt_formatting_custom_model():
try:
prompt = prompt_factory(
model="ehartford/dolphin-2.5-mixtral-8x7b",
messages=[
{"role": "system", "content": "Be a good bot"},
{"role": "user", "content": "Hello world"},
],
custom_llm_provider="huggingface",
)
print(f"prompt: {prompt}")
except Exception as e:
pytest.fail(f"An exception occurred: {str(e)}")
# test_prompt_formatting_custom_model()
# def logger_fn(user_model_dict):
# return
# print(f"user_model_dict: {user_model_dict}")
# messages=[{"role": "user", "content": "Write me a function to print hello world"}]
# # test if the first-party prompt templates work
# def test_huggingface_supported_models():
# model = "huggingface/WizardLM/WizardCoder-Python-34B-V1.0"
# response = completion(model=model, messages=messages, max_tokens=256, api_base="https://ji16r2iys9a8rjk2.us-east-1.aws.endpoints.huggingface.cloud", logger_fn=logger_fn)
# print(response['choices'][0]['message']['content'])
# return response
# test_huggingface_supported_models()
# # test if a custom prompt template works
# litellm.register_prompt_template(
# model="togethercomputer/LLaMA-2-7B-32K",
# roles={"system":"", "assistant":"Assistant:", "user":"User:"},
# pre_message_sep= "\n",
# post_message_sep= "\n"
# )
# def test_huggingface_custom_model():
# model = "huggingface/togethercomputer/LLaMA-2-7B-32K"
# response = completion(model=model, messages=messages, api_base="https://ecd4sb5n09bo4ei2.us-east-1.aws.endpoints.huggingface.cloud", logger_fn=logger_fn)
# print(response['choices'][0]['message']['content'])
# return response
# test_huggingface_custom_model()