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