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Pocketgroq
PocketGroq is a powerful Python library that simplifies integration with the Groq API, offering adva
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About
PocketGroq v0.5.6: Vision and Speech Processing Meets Autonomous Agents!
What's New in v0.5.6
Vision Capabilities
PocketGroq now includes powerful vision analysis capabilities, allowing you to process both images and screen content:
from pocketgroq import GroqProvider
groq = GroqProvider()
# Analyze an image from URL
image_url = "https://example.com/image.jpg"
response = groq.process_image(
prompt="What do you see in this image?",
image_source=image_url
)
print(f"Analysis: {response}")
# Analyze your screen
screen_analysis = groq.process_image_desktop(
prompt="What applications are open on my screen?"
)
print(f"Screen analysis: {screen_analysis}")
# Analyze specific screen region
region_analysis = groq.process_image_desktop_region(
prompt="What's in this part of the screen?",
x1=0, # Top-left corner
y1=0, # Top-left corner
x2=400, # Width
y2=300 # Height
)
print(f"Region analysis: {region_analysis}")You can also have multi-turn conversations about images:
# Start a conversation about an image
messages = [
{
"role": "user",
"content": [
{
"type": "text",
"text": "What do you see in this image?"
},
{
"type": "image_url",
"image_url": {"url": "https://example.com/image.jpg"}
}
]
}
]
response1 = groq.process_image_conversation(messages=messages)
print(f"First response: {response1}")
# Add follow-up question
messages.append({
"role": "assistant",
"content": response1
})
messages.append({
"role": "user",
"content": "What colors are most prominent?"
})
response2 = groq.process_image_conversation(messages=messages)
print(f"Second response: {response2}")Speech Processing
PocketGroq now supports advanced speech processing with transcription and translation capabilities:
from pocketgroq import GroqProvider
groq = GroqProvider()
# Transcribe audio
response = groq.transcribe_audio(
audio_file="recording.wav",
language="en",
model="distil-whisper-large-v3-en" # Fastest for English
)
print(f"Transcription: {response}")
# Translate audio to English
translation = groq.translate_audio(
audio_file="french_speech.wav",
model="whisper-large-v3", # Required for translation
prompt="This is a French conversation about cooking."
)
print(f"Translation: {translation}")Speech Model Selection
PocketGroq offers three Whisper models with different capabilities:
whisper-large-v3: Best for multilingual tasks and translation ($0.111/hour)whisper-large-v3-turbo: Fast multilingual transcription without translation ($0.04/hour)distil-whisper-large-v3-en: Fastest English-only transcription ($0.02/hour)
Don't lose this
Three weeks from now, you'll want Pocketgroq again. Will you remember where to find it?
Save it to your library and the next time you need Pocketgroq, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
⚡ Pro tip for geeks: add a-gnt 🤵🏻♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
PocketGroq is a powerful Python library that simplifies integration with the Groq API, offering adva. Best for anyone looking to make their AI assistant more capable in search & web. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.
Tips for getting started
Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.
Heads up: this needs an API key to work. You'll get one from the service's website (usually free). The setup guide tells you exactly where.
What's New
Imported from GitHub
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