Model HQ
DocumentationVision & Media — Model HQ Client SDK
Model HQ supports multimodal inference for image analysis, image generation, and text-to-speech. All media endpoints accept prompts and return file paths or streamed text.
Prerequisites
This guide assumes the SDK is installed and importable. If you haven't set that up yet, follow the Hello World prerequisites first.
Image analysis
Non-streaming
Upload an image and ask a question about it:
from modelhq.client import LLMWareClient
client = LLMWareClient(api_endpoint="http://localhost:8088", api_key="")
response = client.vision(
image_fp="path/to/image.jpg",
prompt="Describe what is shown in this image"
)
print(response)Streaming
Stream the analysis token-by-token. There is an initial delay of 10-15 seconds while the image is encoded, then generation is fast:
for token in client.vision_stream(
image_fp="path/to/image.jpg",
prompt="Describe what is shown in this image"
):
print(token, end="")Image generation
Generate an image from a text prompt. The result is saved to disk and the file path is returned:
save_path = client.generate_image(
prompt="A watercolour painting of a mountain landscape at sunset",
file_path="output/landscape.bmp" # optional — defaults to tmp folder
)
print("image saved to:", save_path)Text-to-speech
Convert text to speech audio. The result is saved as a .wav file:
save_path = client.generate_speech(
prompt="Welcome to Model HQ. Let me walk you through the key features.",
file_path="output/intro.wav" # optional — defaults to tmp folder
)
print("audio saved to:", save_path)Web search
Search the web using a configured provider (tavily, serp_api, news_api_org, or wikipedia). Requires a provider API key stored as a credential:
# Store the provider API key
client.add_credential({"tavily_api_key": "tvly-..."})
# Run a search
results = client.web_search(
query="What is quantum gravity?",
engine="tavily",
result_count=5
)
print(results)Next steps
- RAG — combine vision with retrieval for document-heavy workflows
- Agents — agents can use vision and search as steps in a pipeline
- API Reference — full endpoint specifications
For further assistance or to share feedback, please contact us at support@aibloks.com
