| name | gemini-video |
| description | Invoke Google Gemini for video understanding and analysis using the Python google-genai SDK. Supports gemini-3-pro-preview and gemini-2.5-flash for video analysis, transcription, and content extraction. |
Gemini Video Skill
Invoke Google Gemini models for video understanding, analysis, transcription, and content extraction using the Python google-genai SDK.
Available Models
| Model ID | Description | Best For |
|---|
gemini-3-pro-preview | Best multimodal understanding | Complex video analysis, detailed descriptions |
gemini-2.5-pro | Advanced reasoning | Deep video analysis with reasoning |
gemini-2.5-flash | Fast processing | Quick video summaries, high throughput |
Configuration
API Key: Use environment variable GEMINI_API_KEY
Usage
Video Analysis (Local File)
For local video files, use the File API to upload first:
python -c "
from google import genai
from google.genai import types
import time
client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))
# Upload video file
video_file = client.files.upload(file='VIDEO_PATH')
print(f'Uploaded file: {video_file.name}')
# Wait for processing
while video_file.state.name == 'PROCESSING':
print('Processing video...')
time.sleep(5)
video_file = client.files.get(name=video_file.name)
if video_file.state.name == 'FAILED':
raise ValueError('Video processing failed')
# Analyze video
response = client.models.generate_content(
model='gemini-3-pro-preview',
contents=[
types.Content(parts=[
types.Part(text='Describe what happens in this video'),
types.Part(file_data=types.FileData(file_uri=video_file.uri, mime_type=video_file.mime_type))
])
]
)
print(response.text)
"
Video Analysis (From URL)
python -c "
from google import genai
from google.genai import types
client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))
# For publicly accessible video URLs
video_url = 'VIDEO_URL_HERE'
response = client.models.generate_content(
model='gemini-3-pro-preview',
contents=[
types.Content(parts=[
types.Part(text='Analyze this video and provide a detailed summary'),
types.Part(file_data=types.FileData(file_uri=video_url, mime_type='video/mp4'))
])
]
)
print(response.text)
"
Video Transcription
python -c "
from google import genai
from google.genai import types
import time
client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))
# Upload video
video_file = client.files.upload(file='VIDEO_PATH')
while video_file.state.name == 'PROCESSING':
time.sleep(5)
video_file = client.files.get(name=video_file.name)
# Transcribe
response = client.models.generate_content(
model='gemini-3-pro-preview',
contents=[
types.Content(parts=[
types.Part(text='Transcribe all spoken words in this video. Include timestamps if possible.'),
types.Part(file_data=types.FileData(file_uri=video_file.uri, mime_type=video_file.mime_type))
])
]
)
print(response.text)
"
Workflow
When this skill is invoked:
-
Determine the task type:
- Video Summary: Generate overview of video content
- Transcription: Extract spoken words
- Visual Analysis: Describe visual elements, scenes, actions
- Content Extraction: Pull specific information from video
- Q&A: Answer questions about video content
-
Prepare the video:
- Local file → Upload via File API
- Remote URL → Use directly (if publicly accessible)
- Wait for processing if needed
-
Select the appropriate model:
- Complex analysis →
gemini-3-pro-preview
- Quick summaries →
gemini-2.5-flash
-
Execute and return results
Example Invocations
Summarize Meeting Recording
python -c "
from google import genai
from google.genai import types
import time
client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))
video_file = client.files.upload(file='meeting_recording.mp4')
while video_file.state.name == 'PROCESSING':
time.sleep(5)
video_file = client.files.get(name=video_file.name)
response = client.models.generate_content(
model='gemini-3-pro-preview',
contents=[
types.Content(parts=[
types.Part(text='''Summarize this meeting recording:
1. List all participants mentioned
2. Key discussion points
3. Action items and decisions made
4. Any deadlines mentioned'''),
types.Part(file_data=types.FileData(file_uri=video_file.uri, mime_type=video_file.mime_type))
])
]
)
print(response.text)
"
Analyze Tutorial Video
python -c "
from google import genai
from google.genai import types
import time
client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))
video_file = client.files.upload(file='tutorial.mp4')
while video_file.state.name == 'PROCESSING':
time.sleep(5)
video_file = client.files.get(name=video_file.name)
response = client.models.generate_content(
model='gemini-3-pro-preview',
contents=[
types.Content(parts=[
types.Part(text='''Analyze this tutorial video and create:
1. A step-by-step guide based on the content
2. Key concepts explained
3. Any tips or best practices mentioned
4. Prerequisites needed to follow along'''),
types.Part(file_data=types.FileData(file_uri=video_file.uri, mime_type=video_file.mime_type))
])
]
)
print(response.text)
"
Extract Code from Coding Video
python -c "
from google import genai
from google.genai import types
import time
client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))
video_file = client.files.upload(file='coding_session.mp4')
while video_file.state.name == 'PROCESSING':
time.sleep(5)
video_file = client.files.get(name=video_file.name)
response = client.models.generate_content(
model='gemini-3-pro-preview',
contents=[
types.Content(parts=[
types.Part(text='''Extract all code shown in this video:
1. Identify the programming language
2. Capture the complete code snippets
3. Note any explanations given for the code
4. List any libraries or dependencies mentioned'''),
types.Part(file_data=types.FileData(file_uri=video_file.uri, mime_type=video_file.mime_type))
])
]
)
print(response.text)
"
Timestamp-Based Analysis
python -c "
from google import genai
from google.genai import types
import time
client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))
video_file = client.files.upload(file='presentation.mp4')
while video_file.state.name == 'PROCESSING':
time.sleep(5)
video_file = client.files.get(name=video_file.name)
response = client.models.generate_content(
model='gemini-3-pro-preview',
contents=[
types.Content(parts=[
types.Part(text='''Create a timestamped outline of this video:
Format: [MM:SS] - Topic/Event
Include major topic changes, key points, and notable moments.'''),
types.Part(file_data=types.FileData(file_uri=video_file.uri, mime_type=video_file.mime_type))
])
]
)
print(response.text)
"
Q&A About Video
python -c "
from google import genai
from google.genai import types
import time
client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))
video_file = client.files.upload(file='lecture.mp4')
while video_file.state.name == 'PROCESSING':
time.sleep(5)
video_file = client.files.get(name=video_file.name)
response = client.models.generate_content(
model='gemini-3-pro-preview',
contents=[
types.Content(parts=[
types.Part(text='YOUR_QUESTION_ABOUT_VIDEO_HERE'),
types.Part(file_data=types.FileData(file_uri=video_file.uri, mime_type=video_file.mime_type))
])
]
)
print(response.text)
"
File Management
List Uploaded Files
python -c "
from google import genai
client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))
for f in client.files.list():
print(f'{f.name}: {f.state.name} ({f.mime_type})')
"
Delete Uploaded File
python -c "
from google import genai
client = genai.Client(api_key=os.environ.get('GEMINI_API_KEY'))
client.files.delete(name='files/FILE_ID_HERE')
print('File deleted')
"
Supported Video Formats
- MP4 (
video/mp4)
- MOV (
video/quicktime)
- AVI (
video/x-msvideo)
- FLV (
video/x-flv)
- MKV (
video/x-matroska)
- WebM (
video/webm)
- WMV (
video/x-ms-wmv)
- 3GPP (
video/3gpp)
Video Limitations
- Maximum file size: Check current API limits (typically 2GB)
- Maximum duration: Varies by model (typically up to 1 hour)
- Processing time: Longer videos take more time to process
- Quota: Video analysis consumes more tokens than text
Error Handling
Common errors and solutions:
- PROCESSING state stuck: Video may be too large or corrupted
- FAILED state: Unsupported format or processing error
- File not found: Upload before analysis
- Rate limiting: Implement retry with exponential backoff
Notes
- Videos must be uploaded via File API before analysis (no inline data like images)
- Processing time depends on video length and complexity
- Uploaded files are automatically deleted after 48 hours
- For very long videos, consider chunking or asking specific timestamp questions
- Gemini 3 Pro provides the most detailed video analysis
Tools to Use
- Bash: Execute Python commands
- Read: Load local video file paths
- Write: Save transcriptions or analysis to files
- Glob: Find video files in directories
