Demonstrates the use of Google's Gemini 2.0 Flash model with "thinking" output enabled, showing how the model reveals its thought process while solving a simple math problem.

gemini_ops.md

File: gemini_thinking_deep.py

from google import genai
import os
os.environ['GEMINI_API_KEY'] = '<KEY>'

client = genai.Client(
    api_key=os.environ['GEMINI_API_KEY'],
    http_options={
        'api_version': 'v1alpha',
    })

stream = client.models.generate_content_stream(
    model='gemini-2.0-flash-thinking-exp-1219', 
    contents=f"""What is 2*2-1*4^4"""
)
thinking = True
print("****** Start thinking... ******")
for chunk in stream:
    for candidate in chunk.candidates:
        for part in candidate.content.parts:
            if part.thought:
                is_thinking = True
            elif is_thinking:  # prints "Finished thinking" when transitioning from thinking to not thinking
                is_thinking = False
                print("\n")
                print("****** Finished thinking... ******")
                print("\n")
        
            print(part.text, end="", flush=True)

File: gemini_gradio.py

import os
os.environ['GEMINI_API_KEY'] = 'AIzaSyAkTenlT1rs8KnV0YBNgTFOToFepPZNfW0'
import gradio as gr
import gemini_gradio

gr.load(
    name='gemini-2.0-flash-exp',
    src=gemini_gradio.registry,
    enable_voice=False,
    title='Gemini 2.0 Flash',
    description='Gemini 2.0 Flash is a model that can understand and generate text, images, and code. It is a large language model trained by Google DeepMind.'
).launch(share=True)

File: gemini_thinking.py

from google import genai
import os
os.environ['GEMINI_API_KEY'] = 'AIzaSyAkTenlT1rs8KnV0YBNgTFOToFepPZNfW0'

# create client
client = genai.Client(api_key=os.environ['GEMINI_API_KEY'])

# use Gemini 2.0 with Flash Thinking 
stream = client.models.generate_content_stream(
    model='gemini-2.0-flash-thinking-exp-1219', 
    contents=f"""Can you crack the code? 
9 2 8 5 (One number is correct but in the wrong position) 
1 9 3 7 (Two numbers are correct but in the wrong positions) 
5 2 0 1 (one number is correct and in the right position) 
6 5 0 7 (nothing is correct) 
8 5 24 (two numbers are correct but in the wrong"""
)
for chunk in stream:
    print(chunk.text, end="", flush=True)

File: pyproject.toml

[project]
name = "gdata"
version = "0.1.0"
description = "Add your description here"
readme = "README.md"
requires-python = ">=3.10"
dependencies = [
    "gemini-gradio>=0.0.3",
    "google-genai>=0.3.0",
]

How to use these in gist.github.com:

1. Go to gist.github.com.
2. You don't need to be logged in to create a public gist, or if you login it can be private.
3. For each file:
   • Copy the entire code block for the given file.
   • Paste it into the gist editor.
   • Give the file a name that matches the .py or .toml file name (e.g., gemini_thinking_deep.py , pyproject.toml)
4. Add a description for each gist if required
5. Click "Create public gist" or "Create secret gist".

Now you have your gists hosted on GitHub!

llama_agents_with_ollama.ipynb