Gemini
Notes of the course Pair Programming with a LLM from DeepLearning.AI. Check it out here
Things needed
An API key, you can get one here
Generative AI Libraries
Basic python skills
from utils import get_api_key
import os
import google.generativeai as genai
from google.api_core import client_options as client_options_lib
genai.configure(
api_key=get_api_key(),
transport="rest",
client_options=client_options_lib.ClientOptions(
api_endpoint=os.getenv("GOOGLE_API_BASE"),
)
)
# Explore the available models
for m in genai.list_models():
print(f"name: {m.name}")
print(f"description: {m.description}")
print(f"generation methods:{m.supported_generation_methods}\n")
models = [m for m in genai.list_models()
if 'generateText'
in m.supported_generation_methods]
models
# Set the model to connect to the Gemini API
model_flash = genai.GenerativeModel(model_name='gemini-1.5-flash')
# Helper with Gemini API
def generate_text(prompt,
model=model_flash,
temperature=0.0):
return model_flash.generate_content(prompt,
generation_config={'temperature':temperature})
# Ask the LLM how to write some code
prompt = "Show me how to iterate across a list in Python."
# Generate the text
completion = generate_text(prompt)
print(completion.text)
# Ask it to write code right away instead of giving code along with explainations
prompt = "write code to iterate across a list in Python"
completion = generate_text(prompt)
print(completion.text)Using a String Template
Pair programming scenarios
Improve existing code
Simplify code
Write test cases
Make code more efficient
Debug your code
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