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import os
from typing import Any
from vlm.vlm_interface import VLMIterface
import google.generativeai as genai
# Fetch Google API key from environment variables
API = os.getenv("GOOGLE_API_KEY")
NAME = "gemini-1.5-flash"
class VLM(VLMIterface):
"""
This class implements the interface for a Visual Language Model (VLM) using Google's generative AI API.
It inherits from the VLMInterface and configures the Google API to interact with the generative model.
"""
def __init__(self) -> None:
"""
Initialize the VLM object by configuring the Google generative AI model using the provided API key.
"""
super().__init__()
# Configure the generative AI model with the provided API key
genai.configure(api_key=API)
# Initialize the model (Gemini 1.5 Flash) from Google's generative AI
self.vlm = genai.GenerativeModel(NAME)
def execution(self) -> Any | None:
"""
Execute the VLM model and return the model object.
If there is an error (e.g., invalid API key or connection issue), handle the exception gracefully.
"""
try:
return self.vlm
except Exception as e:
print(f"Something went wrong with the API: {e}")
return None
def model_name(self) -> str:
return NAME
def __str__(self) -> str:
"""
Return a human-readable string representation of the VLM object.
Useful for informal descriptions or when printing the object.
"""
return f"VLM Model: {self.vlm.model_name}"
def __repr__(self) -> str:
"""
Return an official string representation of the VLM object.
This should ideally be a valid Python expression that can recreate the object.
"""
return f"VLM(api_key='****', model_name='{self.vlm.model_name}')" |