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Gemini
Configure Google Gemini as an LLM provider in Solo Enterprise for agentgateway.
Before you begin
Set up an agentgateway proxy.
Set up access to Gemini
Save your Gemini API key as an environment variable. To retrieve your API key, log in to the Google AI Studio and select API Keys.
export GOOGLE_KEY=<your-api-key>Create a secret to authenticate to Google.
kubectl apply -f - <<EOF apiVersion: v1 kind: Secret metadata: name: google-secret namespace: gloo-system type: Opaque stringData: Authorization: $GOOGLE_KEY EOF
Send a request to the LLM provider API. Verify that the request succeeds and that you get back a response from the chat completion API.
Example output:
{"id":"aGLEaMjbLp6p_uMPopeAoAc", "choices": [{"index":0,"message":{ "content":"Imagine teaching a dog a trick. You show it what to do, reward it when it's right, and correct it when it's wrong. Eventually, the dog learns.\n\nAI is similar. We \"teach\" computers by showing them lots of examples. For example, to recognize cats in pictures, we show it thousands of pictures of cats, labeling each one \"cat.\" The AI learns patterns in these pictures – things like pointy ears, whiskers, and furry bodies – and eventually, it can identify a cat in a new picture it's never seen before.\n\nThis learning process uses math and algorithms (like a secret code of instructions) to find patterns and make predictions. Some AI is more like a dog learning tricks (learning from examples), and some is more like following a very detailed recipe (following pre-programmed rules).\n\nSo, in short: AI is about teaching computers to learn from data and make decisions or predictions, just like we teach dogs tricks.\n", "role":"assistant" }, "finish_reason":"stop" }], "created":1757700714, "model":"gemini-1.5-flash-latest", "object":"chat.completion", "usage":{ "prompt_tokens":8, "completion_tokens":205, "total_tokens":213 } }