59 lines
1.3 KiB
Python
59 lines
1.3 KiB
Python
import json
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import os
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import requests
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import base64
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import time
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def model_infer(vlm_url, messages):
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try:
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param_dict = {
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"model": "vlm",
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"messages": messages
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}
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start_time = time.time()
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response = requests.post(vlm_url, json=param_dict, timeout=300)
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end_time = time.time()
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response = response.json()
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response_content = response['choices'][0]['message']['content']
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return {
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"vlm_url": vlm_url,
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"data": response_content,
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"elapsed": end_time - start_time
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}
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except Exception as e:
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return {"error": str(e), "vlm_url": vlm_url}
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def bench_one_image(image_path):
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with open(image_path, "rb") as f:
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image_base64 = base64.b64encode(f.read()).decode()
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question = "图片有什么？一句话描述"
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messages = [
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{
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"role": "user",
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"content": [
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{
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"type": "image_url",
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"image_url": {"url": f"data:image/jpeg;base64,{image_base64}"},
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},
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{"type": "text", "text": question},
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],
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}
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]
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result = model_infer("http://localhost:8080/generate", messages)
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print (result)
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return result
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def main():
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bench_one_image('./cars.jpg')
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if __name__ == "__main__":
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main()
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