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Add examples for Text Generation
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‎python/text_generation.py

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# -*- coding: utf-8 -*-
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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from absl.testing import absltest
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import pathlib
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media = pathlib.Path(__file__).parents[1] / "third_party"
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class UnitTests(absltest.TestCase):
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def test_text_gen_text_only_prompt(self):
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# [START text_gen_text_only_prompt]
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from google import genai
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client = genai.Client()
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response = client.models.generate_content(
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model="gemini-2.0-flash",
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contents="Write a story about a magic backpack."
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)
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print(response.text)
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# [END text_gen_text_only_prompt]
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def test_text_gen_text_only_prompt_streaming(self):
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# [START text_gen_text_only_prompt_streaming]
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from google import genai
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client = genai.Client()
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response = client.models.generate_content_stream(
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model="gemini-2.0-flash",
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contents="Write a story about a magic backpack."
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)
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for chunk in response:
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print(chunk.text)
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print("_" * 80)
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# [END text_gen_text_only_prompt_streaming]
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def test_text_gen_multimodal_one_image_prompt(self):
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# [START text_gen_multimodal_one_image_prompt]
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from google import genai
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import PIL.Image
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client = genai.Client()
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organ = PIL.Image.open(media / "organ.jpg")
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response = client.models.generate_content(
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model="gemini-2.0-flash",
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contents=["Tell me about this instrument", organ]
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)
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print(response.text)
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# [END text_gen_multimodal_one_image_prompt]
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def test_text_gen_multimodal_one_image_prompt_streaming(self):
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# [START text_gen_multimodal_one_image_prompt_streaming]
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from google import genai
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import PIL.Image
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client = genai.Client()
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organ = PIL.Image.open(media / "organ.jpg")
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response = client.models.generate_content_stream(
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model="gemini-2.0-flash",
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contents=["Tell me about this instrument", organ]
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)
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for chunk in response:
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print(chunk.text)
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print("_" * 80)
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# [END text_gen_multimodal_one_image_prompt_streaming]
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def test_text_gen_multimodal_multi_image_prompt(self):
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# [START text_gen_multimodal_multi_image_prompt]
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from google import genai
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import PIL.Image
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client = genai.Client()
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organ = PIL.Image.open(media / "organ.jpg")
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cajun_instrument = PIL.Image.open(media / "Cajun_instruments.jpg")
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response = client.models.generate_content(
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model="gemini-2.0-flash",
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contents=["What is the difference between both of these instruments?", organ, cajun_instrument]
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)
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print(response.text)
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# [END text_gen_multimodal_multi_image_prompt]
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def test_text_gen_multimodal_multi_image_prompt_streaming(self):
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# [START text_gen_multimodal_multi_image_prompt_streaming]
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from google import genai
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import PIL.Image
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client = genai.Client()
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organ = PIL.Image.open(media / "organ.jpg")
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cajun_instrument = PIL.Image.open(media / "Cajun_instruments.jpg")
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response = client.models.generate_content_stream(
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model="gemini-2.0-flash",
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contents=["What is the difference between both of these instruments?", organ, cajun_instrument]
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)
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for chunk in response:
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print(chunk.text)
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print("_" * 80)
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# [END text_gen_multimodal_multi_image_prompt_streaming]
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def test_text_gen_multimodal_audio(self):
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# [START text_gen_multimodal_audio]
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from google import genai
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client = genai.Client()
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sample_audio = client.files.upload(file=media / "sample.mp3")
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response = client.models.generate_content(
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model="gemini-2.0-flash",
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contents=["Give me a summary of this audio file.", sample_audio]
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)
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print(response.text)
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# [END text_gen_multimodal_audio]
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def test_text_gen_multimodal_audio_streaming(self):
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# [START text_gen_multimodal_audio_streaming]
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from google import genai
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client = genai.Client()
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sample_audio = client.files.upload(file=media / "sample.mp3")
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response = client.models.generate_content_stream(
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model="gemini-2.0-flash",
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contents=["Give me a summary of this audio file.", sample_audio]
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)
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for chunk in response:
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print(chunk.text)
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print("_" * 80)
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# [END text_gen_multimodal_audio_streaming]
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def test_text_gen_multimodal_video_prompt(self):
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# [START text_gen_multimodal_video_prompt]
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from google import genai
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import time
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client = genai.Client()
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# Video clip (CC BY 3.0) from https://peach.blender.org/download/
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myfile = client.files.upload(file=media / "Big_Buck_Bunny.mp4")
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print(f"{myfile=}")
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# Videos need to be processed before you can use them.
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while myfile.state.name == "PROCESSING":
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print("processing video...")
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time.sleep(5)
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myfile = client.files.get(name=myfile.name)
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response = client.models.generate_content(
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model="gemini-2.0-flash",
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contents=[myfile, "Describe this video clip"]
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)
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print(f"{response.text=}")
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# [END text_gen_multimodal_video_prompt]
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def test_text_gen_multimodal_video_prompt_streaming(self):
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# [START text_gen_multimodal_video_prompt_streaming]
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from google import genai
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import time
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client = genai.Client()
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# Video clip (CC BY 3.0) from https://peach.blender.org/download/
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myfile = client.files.upload(file=media / "Big_Buck_Bunny.mp4")
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print(f"{myfile=}")
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# Videos need to be processed before you can use them.
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while myfile.state.name == "PROCESSING":
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print("processing video...")
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time.sleep(5)
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myfile = client.files.get(name=myfile.name)
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response = client.models.generate_content_stream(
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model="gemini-2.0-flash",
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contents=[myfile, "Describe this video clip"]
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)
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for chunk in response:
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print(chunk.text)
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print("_" * 80)
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# [END text_gen_multimodal_video_prompt_streaming]
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def test_text_gen_multimodal_pdf(self):
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# [START text_gen_multimodal_pdf]
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from google import genai
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client = genai.Client()
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sample_pdf = client.files.upload(file=media / "test.pdf")
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response = client.models.generate_content(
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model="gemini-2.0-flash",
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contents=["Give me a summary of this document:", sample_pdf]
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)
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print(f"{response.text=}")
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# [END text_gen_multimodal_pdf]
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def test_text_gen_multimodal_pdf_streaming(self):
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# [START text_gen_multimodal_pdf_streaming]
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from google import genai
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client = genai.Client()
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sample_pdf = client.files.upload(file=media / "test.pdf")
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response = client.models.generate_content_stream(
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model="gemini-2.0-flash",
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contents=["Give me a summary of this document:", sample_pdf]
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)
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for chunk in response:
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print(chunk.text)
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print("_" * 80)
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# [END text_gen_multimodal_pdf_streaming]
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if __name__ == "__main__":
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absltest.main()

‎third_party/Big_Buck_Bunny.mp4

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‎third_party/Cajun_instruments.jpg

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‎third_party/LICENSE.txt

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* a11.txt
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* This is an apollo 11 transcript.
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* This file is in the public domain in the United States because it was solely created by NASA
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* Big_Buck_Bunny.mp4:
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* This is a clip from https://peach.blender.org/download/
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* License CC-BY 3.0 (Attribution)
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* poem.txt:
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* This is the first paragraph from Shakespeare's "spring", public domain.
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* Cajun_instruments.jpg
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* This image is from Wikimedia Commons, a public domain (https://commons.wikimedia.org/wiki/Category:Musical_instruments#/media/File:Cajun_instruments.jpg).
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* test.pdf
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* This is the first 2 pages of https://arxiv.org/abs/2403.05530 by Google Gemini Team.
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* License: CC-BY 4.0

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