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import google.generativeai as genai
import os
from dotenv import load_dotenv
from typing import Optional
generation_config=genai.types.GenerationConfig(
# Only one candidate for now.
#candidate_count=1,
#stop_sequences=['x'],
max_output_tokens=4096,
temperature=0.1
)
class GeminiModel:
"""
This class is used to interact with the Google LLM models for text generation.
Args:
model: The name of the model to be used. Defaults to 'gemini-pro'.
max_output_tokens: The maximum number of tokens to generate. Defaults to 1024.
top_p: The probability of generating the next token. Defaults to 1.0.
temperature: The temperature of the model. Defaults to 0.0.
top_k: The number of top tokens to consider. Defaults to 5.
"""
def __init__(self,
model_name: Optional[str] = 'gemini-pro',
):
load_dotenv()
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
self.model = genai.GenerativeModel(model_name) # type: ignore
def execute(self, prompt: str) -> str:
try:
total_tokens = self.model.count_tokens(prompt).total_tokens
print(f"Input tokens: {total_tokens}")
response = self.model.generate_content(prompt, generation_config=generation_config)
output_tokens = self.model.count_tokens(response.text).total_tokens
print(f"Output tokens: {output_tokens}")
return response.text
except Exception as e:
return f"An error occurred: {e}" |