43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
import os
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import requests
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def send_messages(payload):
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# URL to your proxy for calling LLMs
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proxy_url = ""
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api_key = os.getenv("SERVICE_KEY")
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# Can be directly replaced with code for calling Azure endpoint as in:
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#.env config example :
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# AZURE_OPENAI_API_BASE=YOUR_API_BASE
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# AZURE_OPENAI_DEPLOYMENT=YOUR_DEPLOYMENT
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# AZURE_OPENAI_API_VERSION=YOUR_API_VERSION
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# AZURE_OPENAI_MODEL=gpt-4o-mini
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# AZURE_OPENAI_API_KEY={{YOUR_API_KEY}}
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# AZURE_OPENAI_ENDPOINT=${AZURE_OPENAI_API_BASE}/openai/deployments/${AZURE_OPENAI_DEPLOYMENT}/chat/completions?api-version=${AZURE_OPENAI_API_VERSION}
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# Load environment variables
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# load_dotenv()
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# api_key = os.getenv('AZURE_OPENAI_API_KEY')
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# openai_endpoint = os.getenv('AZURE_OPENAI_ENDPOINT')
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# #logger.info("Openai endpoint: %s", openai_endpoint)
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# headers = {
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# "Content-Type": "application/json",
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# "api-key": api_key
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# }
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# response = requests.post(
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# openai_endpoint,
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# headers=headers,
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# json=payload
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# )
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headers = {
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"Content-Type": "application/json",
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"X-API-KEY": api_key
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}
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retries = 3
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for attempt in range(retries):
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response = requests.post(proxy_url, headers=headers, json=payload)
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if response.status_code == 200:
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return response.text
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return None |