A newer version of the Gradio SDK is available:
5.42.0
Shasha AI — API Reference
This document describes the public interfaces provided by each module.
hf_client.py
get_inference_client(model_id: str, provider: str = "auto") → InferenceClient
Creates and configures a Hugging Face Hub client for chat completions.
- model_id: HF model ID or external provider prefix (e.g.
"openai/gpt-4"
,"gemini/pro"
,"moonshotai/Kimi-K2-Instruct"
). - provider: Override provider; one of
auto
,groq
,openai
,gemini
,fireworks
. - Returns:
InferenceClient
instance with proper API key & billing target.
models.py
ModelInfo
Dataclass representing model metadata.
- name: Human‑readable model name.
- id: Model identifier for API calls.
- description: Short description.
- default_provider: Preferred inference provider.
AVAILABLE_MODELS: List[ModelInfo]
Registry of all supported models.
find_model(identifier: str) → Optional[ModelInfo]
Lookup model by name (case‑insensitive) or ID.
inference.py
chat_completion(model_id: str, messages: List[Dict[str, str]], provider: str = None, max_tokens: int = 4096) → str
Synchronously sends a chat completion request.
- messages: List of
{"role": "...", "content": "..."}
- provider: Optional override; defaults to model’s
default_provider
. - Returns: Response content string.
stream_chat_completion(model_id: str, messages: List[Dict[str, str]], provider: str = None, max_tokens: int = 4096) → Generator[str]
Streams a chat completion, yielding incremental content chunks.
utils.py
history_to_messages(history: History, system: str) → List[Dict]
Converts internal history list to OpenAI‑style messages.
remove_code_block(text: str) → str
Strips markdown code fences from AI output and returns raw code.
parse_transformers_js_output(text: str) → Dict[str, str]
Extracts index.html
, index.js
, style.css
from a multi‑file markdown output.
format_transformers_js_output(files: Dict[str, str]) → str
Formats a dict of file contents into a single combined string with section headers.
(Other utilities: multimodal image processing, search/replace, history rendering)
deploy.py
send_to_sandbox(code: str) → str
Wraps HTML code in a base64 data‑URI iframe for live preview.
load_project_from_url(url: str) → Tuple[str, str]
Fetches app.py
or index.html
from a public HF Space URL.
(Also: HF Spaces deploy helpers: deploy_to_spaces()
, deploy_to_spaces_static()
, deploy_to_user_space()
)
app.py
generation_code(query, image, file, website_url, _setting, _history, _current_model, enable_search, language, provider) → Tuple[str, History, str, List[Dict]]
Main generation handler bound to the “Generate” button.
- Returns:
code_str
: Generated (or edited) source codenew_history
: Updated prompt/response historysandbox_html
: Live preview HTML iframe stringchat_msgs
: Chatbot‑style history for the UI
For more examples, see the Jupyter notebooks in notebooks/
and the quick‑start guide in QUICKSTART.md
.