Rozpoznawanie filmów

from google import genai

client = genai.Client()

myfile = client.files.upload(file="path/to/sample.mp4")

response = client.models.generate_content(
    model="gemini-3-flash-preview", contents=[myfile, "Summarize this video. Then create a quiz with an answer key based on the information in this video."]
)

print(response.text)

import {
  GoogleGenAI,
  createUserContent,
  createPartFromUri,
} from "@google/genai";

const ai = new GoogleGenAI({});

async function main() {
  const myfile = await ai.files.upload({
    file: "path/to/sample.mp4",
    config: { mimeType: "video/mp4" },
  });

  const response = await ai.models.generateContent({
    model: "gemini-3-flash-preview",
    contents: createUserContent([
      createPartFromUri(myfile.uri, myfile.mimeType),
      "Summarize this video. Then create a quiz with an answer key based on the information in this video.",
    ]),
  });
  console.log(response.text);
}

await main();

uploadedFile, _ := client.Files.UploadFromPath(ctx, "path/to/sample.mp4", nil)

parts := []*genai.Part{
    genai.NewPartFromText("Summarize this video. Then create a quiz with an answer key based on the information in this video."),
    genai.NewPartFromURI(uploadedFile.URI, uploadedFile.MIMEType),
}

contents := []*genai.Content{
    genai.NewContentFromParts(parts, genai.RoleUser),
}

result, _ := client.Models.GenerateContent(
    ctx,
    "gemini-3-flash-preview",
    contents,
    nil,
)

fmt.Println(result.Text())

VIDEO_PATH="path/to/sample.mp4"
MIME_TYPE=$(file -b --mime-type "${VIDEO_PATH}")
NUM_BYTES=$(wc -c < "${VIDEO_PATH}")
DISPLAY_NAME=VIDEO

tmp_header_file=upload-header.tmp

echo "Starting file upload..."
curl "https://generativelanguage.googleapis.com/upload/v1beta/files" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -D ${tmp_header_file} \
  -H "X-Goog-Upload-Protocol: resumable" \
  -H "X-Goog-Upload-Command: start" \
  -H "X-Goog-Upload-Header-Content-Length: ${NUM_BYTES}" \
  -H "X-Goog-Upload-Header-Content-Type: ${MIME_TYPE}" \
  -H "Content-Type: application/json" \
  -d "{'file': {'display_name': '${DISPLAY_NAME}'}}" 2> /dev/null

upload_url=$(grep -i "x-goog-upload-url: " "${tmp_header_file}" | cut -d" " -f2 | tr -d "\r")
rm "${tmp_header_file}"

echo "Uploading video data..."
curl "${upload_url}" \
  -H "Content-Length: ${NUM_BYTES}" \
  -H "X-Goog-Upload-Offset: 0" \
  -H "X-Goog-Upload-Command: upload, finalize" \
  --data-binary "@${VIDEO_PATH}" 2> /dev/null > file_info.json

file_uri=$(jq -r ".file.uri" file_info.json)
echo file_uri=$file_uri

echo "File uploaded successfully. File URI: ${file_uri}"

# --- 3. Generate content using the uploaded video file ---
echo "Generating content from video..."
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-3-flash-preview:generateContent" \
    -H "x-goog-api-key: $GEMINI_API_KEY" \
    -H 'Content-Type: application/json' \
    -X POST \
    -d '{
      "contents": [{
        "parts":[
          {"file_data":{"mime_type": "'"${MIME_TYPE}"'", "file_uri": "'"${file_uri}"'"}},
          {"text": "Summarize this video. Then create a quiz with an answer key based on the information in this video."}]
        }]
      }' 2> /dev/null > response.json

jq -r ".candidates[].content.parts[].text" response.json

from google import genai
from google.genai import types

# Only for videos of size <20Mb
video_file_name = "/path/to/your/video.mp4"
video_bytes = open(video_file_name, 'rb').read()

client = genai.Client()
response = client.models.generate_content(
    model='gemini-3-flash-preview',
    contents=types.Content(
        parts=[
            types.Part(
                inline_data=types.Blob(data=video_bytes, mime_type='video/mp4')
            ),
            types.Part(text='Please summarize the video in 3 sentences.')
        ]
    )
)
print(response.text)

import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";

const ai = new GoogleGenAI({});
const base64VideoFile = fs.readFileSync("path/to/small-sample.mp4", {
  encoding: "base64",
});

const contents = [
  {
    inlineData: {
      mimeType: "video/mp4",
      data: base64VideoFile,
    },
  },
  { text: "Please summarize the video in 3 sentences." }
];

const response = await ai.models.generateContent({
  model: "gemini-3-flash-preview",
  contents: contents,
});
console.log(response.text);

VIDEO_PATH=/path/to/your/video.mp4

if [[ "$(base64 --version 2>&1)" = *"FreeBSD"* ]]; then
  B64FLAGS="--input"
else
  B64FLAGS="-w0"
fi

curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-3-flash-preview:generateContent" \
    -H "x-goog-api-key: $GEMINI_API_KEY" \
    -H 'Content-Type: application/json' \
    -X POST \
    -d '{
      "contents": [{
        "parts":[
            {
              "inline_data": {
                "mime_type":"video/mp4",
                "data": "'$(base64 $B64FLAGS $VIDEO_PATH)'"
              }
            },
            {"text": "Please summarize the video in 3 sentences."}
        ]
      }]
    }' 2> /dev/null

from google import genai
from google.genai import types

client = genai.Client()
response = client.models.generate_content(
    model='gemini-3-flash-preview',
    contents=types.Content(
        parts=[
            types.Part(
                file_data=types.FileData(file_uri='https://www.youtube.com/watch?v=9hE5-98ZeCg')
            ),
            types.Part(text='Please summarize the video in 3 sentences.')
        ]
    )
)
print(response.text)

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

const contents = [
  {
    fileData: {
      fileUri: "https://www.youtube.com/watch?v=9hE5-98ZeCg",
    },
  },
  { text: "Please summarize the video in 3 sentences." }
];

const response = await ai.models.generateContent({
  model: "gemini-3-flash-preview",
  contents: contents,
});
console.log(response.text);

package main

import (
  "context"
  "fmt"
  "os"
  "google.golang.org/genai"
)

func main() {
  ctx := context.Background()
  client, err := genai.NewClient(ctx, nil)
  if err != nil {
      log.Fatal(err)
  }

  parts := []*genai.Part{
      genai.NewPartFromText("Please summarize the video in 3 sentences."),
      genai.NewPartFromURI("https://www.youtube.com/watch?v=9hE5-98ZeCg","video/mp4"),
  }

  contents := []*genai.Content{
      genai.NewContentFromParts(parts, genai.RoleUser),
  }

  result, _ := client.Models.GenerateContent(
      ctx,
      "gemini-3-flash-preview",
      contents,
      nil,
  )

  fmt.Println(result.Text())
}

curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-3-flash-preview:generateContent" \
    -H "x-goog-api-key: $GEMINI_API_KEY" \
    -H 'Content-Type: application/json' \
    -X POST \
    -d '{
      "contents": [{
        "parts":[
            {"text": "Please summarize the video in 3 sentences."},
            {
              "file_data": {
                "file_uri": "https://www.youtube.com/watch?v=9hE5-98ZeCg"
              }
            }
        ]
      }]
    }' 2> /dev/null

prompt = "What are the examples given at 00:05 and 00:10 supposed to show us?" # Adjusted timestamps for the NASA video

const prompt = "What are the examples given at 00:05 and 00:10 supposed to show us?";

    prompt := []*genai.Part{
        genai.NewPartFromURI(currentVideoFile.URI, currentVideoFile.MIMEType),
         // Adjusted timestamps for the NASA video
        genai.NewPartFromText("What are the examples given at 00:05 and " +
            "00:10 supposed to show us?"),
    }

PROMPT="What are the examples given at 00:05 and 00:10 supposed to show us?"

prompt = "Describe the key events in this video, providing both audio and visual details. Include timestamps for salient moments."

const prompt = "Describe the key events in this video, providing both audio and visual details. Include timestamps for salient moments.";

    prompt := []*genai.Part{
        genai.NewPartFromURI(currentVideoFile.URI, currentVideoFile.MIMEType),
        genai.NewPartFromText("Describe the key events in this video, providing both audio and visual details. " +
      "Include timestamps for salient moments."),
    }

PROMPT="Describe the key events in this video, providing both audio and visual details. Include timestamps for salient moments."

from google import genai
from google.genai import types

client = genai.Client()
response = client.models.generate_content(
    model='models/gemini-3-flash-preview',
    contents=types.Content(
        parts=[
            types.Part(
                file_data=types.FileData(file_uri='https://www.youtube.com/watch?v=XEzRZ35urlk'),
                video_metadata=types.VideoMetadata(
                    start_offset='1250s',
                    end_offset='1570s'
                )
            ),
            types.Part(text='Please summarize the video in 3 sentences.')
        ]
    )
)

import { GoogleGenAI } from '@google/genai';
const ai = new GoogleGenAI({});
const model = 'gemini-3-flash-preview';

async function main() {
const contents = [
  {
    role: 'user',
    parts: [
      {
        fileData: {
          fileUri: 'https://www.youtube.com/watch?v=9hE5-98ZeCg',
          mimeType: 'video/*',
        },
        videoMetadata: {
          startOffset: '40s',
          endOffset: '80s',
        }
      },
      {
        text: 'Please summarize the video in 3 sentences.',
      },
    ],
  },
];

const response = await ai.models.generateContent({
  model,
  contents,
});

console.log(response.text)

}

await main();

from google import genai
from google.genai import types

# Only for videos of size <20Mb
video_file_name = "/path/to/your/video.mp4"
video_bytes = open(video_file_name, 'rb').read()

client = genai.Client()
response = client.models.generate_content(
    model='models/gemini-3-flash-preview',
    contents=types.Content(
        parts=[
            types.Part(
                inline_data=types.Blob(
                    data=video_bytes,
                    mime_type='video/mp4'),
                video_metadata=types.VideoMetadata(fps=5)
            ),
            types.Part(text='Please summarize the video in 3 sentences.')
        ]
    )
)