from huggingface_hub import InferenceClient, get_inference_endpoint
import json

# Get endpoint and create client
MODEL_NAME = "YOUR_MODEL_NAME_OR_ENDPOINT_NAME"
NAMESPACE = "YOUR_NAMESPACE"
endpoint = get_inference_endpoint(MODEL_NAME, namespace=NAMESPACE)
client = InferenceClient(endpoint.url, timeout=10)

# Test data
query = "What is the capital of France?"
document = "Paris is the capital of France."
sentence_ranking_style_inputs = [[query, document]]
text_classification_style_inputs = [{"text": query, "text_pair": document}]

# 1. Using post method
response_bytes = client.post(json={"inputs": sentence_ranking_style_inputs})
print(json.loads(response_bytes))
# Problem: post method has deprecation warning

# 2. Using text_classification task
try:
    result = client.text_classification(text_classification_style_inputs) # There's no way to inject the inputs format that would have worked on this task for reranking
    print(result)
except Exception as e:
    print(f"text_classification error: {e}")
# Problem: text_classification doesn't properly support text pairs format needed for reranking/cross-encoding

# 3. Using sentence_similarity task
try:
    result = client.sentence_similarity(sentence_ranking_style_inputs) # There's no direct way to inject the inputs format that would have worked on this task for reranking
    print(result)
except Exception as e:
    print(f"sentence_similarity error: {e}")
# Problem: No direct support for sentence ranking despite endpoint supporting this task