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| import requests, base64 | |
| import os | |
| import json | |
| def vision_inference(image_name): | |
| try: | |
| invoke_url = "https://ai.api.nvidia.com/v1/gr/meta/llama-3.2-11b-vision-instruct/chat/completions" | |
| stream = False | |
| with open(image_name, "rb") as f: | |
| image_b64 = base64.b64encode(f.read()).decode() | |
| #assert len(image_b64) < 180_000, \ | |
| # "To upload larger images, use the assets API (see docs)" | |
| api_key = os.environ["NIM_API_KEY"] | |
| headers = { | |
| "Authorization": f"Bearer {api_key}", | |
| "Accept": "text/event-stream" if stream else "application/json" | |
| } | |
| payload = { | |
| "model": 'meta/llama-3.2-11b-vision-instruct', | |
| "messages": [ | |
| { | |
| "role": "user", | |
| "content": f'What is in this image? <img src="data:image/png;base64,{image_b64}" />' | |
| } | |
| ], | |
| "max_tokens": 512, | |
| "temperature": 1.00, | |
| "top_p": 1.00, | |
| "stream": stream | |
| } | |
| response = requests.post(invoke_url, headers=headers, json=payload) | |
| if stream: | |
| for line in response.iter_lines(): | |
| if line: | |
| #print(line.decode("utf-8")) | |
| data = line.decode("utf-8") | |
| #content = json.loads(data)['choices'][0]['delta'].get('content', '') | |
| else: | |
| #print(response.json()) | |
| data = response.json() | |
| content = data['choices'][0]['message']['content'] | |
| #print(content) | |
| return content | |
| except Exception as e: # Added general exception handling | |
| print(f"Error: {e}") | |
| return None | |
| #image_name = "/home/gaganyatri/Pictures/hackathon/eat-health/fruit-stall-1.jpg" | |
| #content = vision_inference(image_name) | |
| #print(content) |