Integrate your application with Gemini
Create an account + Generate an API Key
Set API keys as environment variables
export QUALIFIRE_API_KEY=<your API key>
Install necessary packages
pip install --upgrade google-cloud-aiplatform gcloud auth application-default login
Import VertexAI and configure the client
import vertexai from vertexai.generative_models import GenerativeModel LOCATION = "us-central1" vertexai.init( project="<PROJECT-ID>", location="<LOCATION>", api_transport="rest", api_endpoint="https://proxy.qualifire.ai/api/providers/google", request_metadata=[ ("X-Qualifire-Base-Url", f"https://{LOCATION}-aiplatform.googleapis.com"), ("X-Qualifire-API-Key", "<your API key>"), ], ) model = GenerativeModel( "gemini-1.5-flash-002", )
Call the API
def generate(): responses = model.generate_content( ["""tell me a joke about cats"""], generation_config=generation_config, stream=True, ) for response in responses: print(response.text, end="") generation_config = { "max_output_tokens": 8192, "temperature": 1, "top_p": 0.95, } generate()