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text_generation.py
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text_generation.py
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# -*- coding: utf-8 -*-
# Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from absl.testing import absltest
import google.generativeai as genai
import pathlib
media = pathlib.Path(__file__).parents[1] / "third_party"
class UnitTests(absltest.TestCase):
def test_text_gen_text_only_prompt(self):
# [START text_gen_text_only_prompt]
model = genai.GenerativeModel("gemini-1.5-flash")
response = model.generate_content("Write a story about a magic backpack.")
print(response.text)
# [END text_gen_text_only_prompt]
def test_text_gen_text_only_prompt_streaming(self):
# [START text_gen_text_only_prompt_streaming]
model = genai.GenerativeModel("gemini-1.5-flash")
response = model.generate_content("Write a story about a magic backpack.", stream=True)
for chunk in response:
print(chunk.text)
print("_" * 80)
# [END text_gen_text_only_prompt_streaming]
def test_text_gen_multimodal_one_image_prompt(self):
# [START text_gen_multimodal_one_image_prompt]
import PIL.Image
model = genai.GenerativeModel("gemini-1.5-flash")
organ = PIL.Image.open(media / "organ.jpg")
response = model.generate_content(["Tell me about this instrument", organ])
print(response.text)
# [END text_gen_multimodal_one_image_prompt]
def test_text_gen_multimodal_one_image_prompt_streaming(self):
# [START text_gen_multimodal_one_image_prompt_streaming]
import PIL.Image
model = genai.GenerativeModel("gemini-1.5-flash")
organ = PIL.Image.open(media / "organ.jpg")
response = model.generate_content(["Tell me about this instrument", organ], stream=True)
for chunk in response:
print(chunk.text)
print("_" * 80)
# [END text_gen_multimodal_one_image_prompt_streaming]
def test_text_gen_multimodal_multi_image_prompt(self):
# [START text_gen_multimodal_multi_image_prompt]
import PIL.Image
model = genai.GenerativeModel("gemini-1.5-flash")
organ = PIL.Image.open(media / "organ.jpg")
cajun_instrument = PIL.Image.open(media / "Cajun_instruments.jpg")
response = model.generate_content(
["What is the difference between both of these instruments?", organ, cajun_instrument]
)
print(response.text)
# [END text_gen_multimodal_multi_image_prompt]
def test_text_gen_multimodal_multi_image_prompt_streaming(self):
# [START text_gen_multimodal_multi_image_prompt_streaming]
import PIL.Image
model = genai.GenerativeModel("gemini-1.5-flash")
organ = PIL.Image.open(media / "organ.jpg")
cajun_instrument = PIL.Image.open(media / "Cajun_instruments.jpg")
response = model.generate_content(
["What is the difference between both of these instruments?", organ, cajun_instrument],
stream=True,
)
for chunk in response:
print(chunk.text)
print("_" * 80)
# [END text_gen_multimodal_multi_image_prompt_streaming]
def test_text_gen_multimodal_audio(self):
# [START text_gen_multimodal_audio]
model = genai.GenerativeModel("gemini-1.5-flash")
sample_audio = genai.upload_file(media / "sample.mp3")
response = model.generate_content(["Give me a summary of this audio file.", sample_audio])
print(response.text)
# [END text_gen_multimodal_audio]
def test_text_gen_multimodal_audio_streaming(self):
# [START text_gen_multimodal_audio_streaming]
model = genai.GenerativeModel("gemini-1.5-flash")
sample_audio = genai.upload_file(media / "sample.mp3")
response = model.generate_content(["Give me a summary of this audio file.", sample_audio])
for chunk in response:
print(chunk.text)
print("_" * 80)
# [END text_gen_multimodal_audio_streaming]
def test_text_gen_multimodal_video_prompt(self):
# [START text_gen_multimodal_video_prompt]
import time
# Video clip (CC BY 3.0) from https://peach.blender.org/download/
myfile = genai.upload_file(media / "Big_Buck_Bunny.mp4")
print(f"{myfile=}")
# Videos need to be processed before you can use them.
while myfile.state.name == "PROCESSING":
print("processing video...")
time.sleep(5)
myfile = genai.get_file(myfile.name)
model = genai.GenerativeModel("gemini-1.5-flash")
response = model.generate_content([myfile, "Describe this video clip"])
print(f"{response.text=}")
# [END text_gen_multimodal_video_prompt]
def test_text_gen_multimodal_video_prompt_streaming(self):
# [START text_gen_multimodal_video_prompt_streaming]
import time
# Video clip (CC BY 3.0) from https://peach.blender.org/download/
myfile = genai.upload_file(media / "Big_Buck_Bunny.mp4")
print(f"{myfile=}")
# Videos need to be processed before you can use them.
while myfile.state.name == "PROCESSING":
print("processing video...")
time.sleep(5)
myfile = genai.get_file(myfile.name)
model = genai.GenerativeModel("gemini-1.5-flash")
response = model.generate_content([myfile, "Describe this video clip"])
for chunk in response:
print(chunk.text)
print("_" * 80)
# [END text_gen_multimodal_video_prompt_streaming]
def test_text_gen_multimodal_pdf(self):
# [START text_gen_multimodal_pdf]
model = genai.GenerativeModel("gemini-1.5-flash")
sample_pdf = genai.upload_file(media / "test.pdf")
response = model.generate_content(["Give me a summary of this document:", sample_pdf])
print(f"{response.text=}")
# [END text_gen_multimodal_pdf]
def test_text_gen_multimodal_pdf_streaming(self):
# [START text_gen_multimodal_pdf_streaming]
model = genai.GenerativeModel("gemini-1.5-flash")
sample_pdf = genai.upload_file(media / "test.pdf")
response = model.generate_content(["Give me a summary of this document:", sample_pdf])
for chunk in response:
print(chunk.text)
print("_" * 80)
# [END text_gen_multimodal_pdf_streaming]
if __name__ == "__main__":
absltest.main()