Extracting a single measurement

We’ve shown that Gemini can read and understand a document, but can it extract data from it? Let’s start with a simple query: “What is the rainfall for January 5th?”.

The code is simple: we load the image, ask the question, and print the answer.

#!/usr/bin/env python3

# Basic test of the Gemini API - get one observation.

import os
import PIL.Image
import google.generativeai as genai

# You will need an API key get it from https://ai.google.dev/gemini-api/docs/api-key

# I keep my API key in the .gemini_api file in my home directory.
with open("%s/.gemini_api" % os.getenv("HOME"), "r") as file:
    api_key = file.read().strip()

# Default protocol is 'GRPC' - but that is blocked by the Office firewall.
#  Use 'REST' instead.
genai.configure(api_key=api_key, transport="rest")

# Load the sample image
img = PIL.Image.open(
    "../../images/jpgs_300dpi/Devon_1941-1950_RainNos_1651-1689-293.jpg"
)

# Pick an AI to use - this one is the latest as of 2025-01-29
model = genai.GenerativeModel("gemini-2.0-flash-exp")

# Ask a question about the image
result = model.generate_content([img, "\n\n", "What was the rainfall on January 5th?"])
with open("result.txt", "w") as file:
    file.write(str(result))

# print(result)

I chose January 5th because the page is very messy in that region, and I wanted to see how well Gemini could extract data from a difficult area. It works perfectly.

response:
GenerateContentResponse(
    done=True,
    iterator=None,
    result=protos.GenerateContentResponse({
      "candidates": [
        {
          "content": {
            "parts": [
              {
                "text": "The rainfall on January 5th was 1.03 inches."
              }
            ],
            "role": "model"
          },
          "finish_reason": "STOP",
          "safety_ratings": [
            {
              "category": "HARM_CATEGORY_HATE_SPEECH",
              "probability": "NEGLIGIBLE"
            },
            {
              "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
              "probability": "NEGLIGIBLE"
            },
            {
              "category": "HARM_CATEGORY_HARASSMENT",
              "probability": "NEGLIGIBLE"
            },
            {
              "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
              "probability": "NEGLIGIBLE"
            }
          ],
          "avg_logprobs": -0.024279586474100747
        }
      ],
      "usage_metadata": {
        "prompt_token_count": 270,
        "candidates_token_count": 15,
        "total_token_count": 285
      },
      "model_version": "gemini-2.0-flash-exp"
    }),
)

The answer is correct: (Compare a section cropped out of the image - below).