58 lines
2.0 KiB
Python
58 lines
2.0 KiB
Python
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"""Examples Python client Score for Cross Encoder Models
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"""
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import argparse
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import json
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import pprint
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import requests
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def post_http_request(prompt: json, api_url: str) -> requests.Response:
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headers = {"User-Agent": "Test Client"}
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response = requests.post(api_url, headers=headers, json=prompt)
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return response
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--host", type=str, default="localhost")
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parser.add_argument("--port", type=int, default=8000)
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parser.add_argument("--model", type=str, default="BAAI/bge-reranker-v2-m3")
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args = parser.parse_args()
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api_url = f"http://{args.host}:{args.port}/v1/score"
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model_name = args.model
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text_1 = "What is the capital of France?"
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text_2 = [
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"The capital of Brazil is Brasilia.", "The capital of France is Paris."
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]
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prompt = {"model": model_name, "text_1": text_1, "text_2": text_2}
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score_response = post_http_request(prompt=prompt, api_url=api_url)
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print("Prompt for text_1 is string and text_2 is a list:")
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pprint.pprint(prompt)
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print("Score Response:")
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pprint.pprint(score_response.data)
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text_1 = [
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"What is the capital of Brazil?", "What is the capital of France?"
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]
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text_2 = [
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"The capital of Brazil is Brasilia.", "The capital of France is Paris."
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]
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prompt = {"model": model_name, "text_1": text_1, "text_2": text_2}
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score_response = post_http_request(prompt=prompt, api_url=api_url)
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print("Prompt for text_1 and text_2 are lists:")
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pprint.pprint(prompt)
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print("Score Response:")
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pprint.pprint(score_response.data)
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text_1 = "What is the capital of Brazil?"
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text_2 = "The capital of Brazil is Brasilia."
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prompt = {"model": model_name, "text_1": text_1, "text_2": text_2}
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score_response = post_http_request(prompt=prompt, api_url=api_url)
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print("Prompt for text_1 and text_2 are strings:")
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pprint.pprint(prompt)
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print("Score Response:")
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pprint.pprint(score_response.data)
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