interfaze 1.0.1

Official Interfaze SDK.

interfaze-python

The official Interfaze SDK for Python.

• Familiar chat surface - chat.completions, streaming, tools, and structured output.
• Typed Interfaze extras - precontext (internal tool output), reasoning, and vcache (semantic-cache hit) on every response.
• One-line task helpers - OCR, web search, scraping, speech-to-text, translation, object/GUI detection, forecasting.
• Multimodal inputs - images, PDFs, audio, video, and CSV, by URL or base64.
• Sync and async, fully typed.

Learn more

• interfaze.ai - dashboard and API keys.
• TypeScript / JavaScript SDK.

Capabilities

Category	Capabilities
Chat & text	Chat completions, structured output, tools, reasoning
Vision & OCR	tasks.ocr - text and structured data from images and PDFs
Web	tasks.web_search, tasks.scrape
Audio	tasks.transcribe - speech-to-text
Detection	tasks.object_detection, tasks.gui_detection
Translation	tasks.translate
Forecasting	tasks.forecast - time-series prediction

Install

pip install interfaze

Setup

Get an API key from the Interfaze dashboard, then:

from interfaze import Interfaze

interfaze = Interfaze(api_key="sk_...")  # or set INTERFAZE_API_KEY and call Interfaze()

Async is identical via AsyncInterfaze (every call becomes await-able).

Usage

Chat completion:

res = interfaze.chat.completions.create(
    messages=[{"role": "user", "content": "Write a haiku about deterministic AI."}],
)
print(res.choices[0].message.content)
print("cache hit:", res.vcache)          # typed Interfaze extra

Task helpers - each returns the extracted result directly (a dict/list/str, not a completion):

interfaze.tasks.ocr("https://example.com/receipt.jpg")
interfaze.tasks.web_search("latest AI agent news")
interfaze.tasks.transcribe("https://example.com/audio.wav")
interfaze.tasks.scrape("https://example.com/product")
interfaze.tasks.translate("Hello", to="French")
interfaze.tasks.object_detection("https://example.com/photo.jpg")
interfaze.tasks.gui_detection("https://example.com/screenshot.png")
interfaze.tasks.forecast("https://example.com/series.csv", periods=30)

Structured output:

from interfaze import response_format

res = interfaze.chat.completions.create(
    messages=[{"role": "user", "content": "Weather in Tokyo?"}],
    response_format=response_format({
        "type": "object",
        "properties": {"city": {"type": "string"}, "temp_c": {"type": "number"}},
        "required": ["city", "temp_c"],
    }),
)

Streaming - .stream() yields typed events, with the inline <think>/<precontext> side-channels stripped from the content events:

stream = interfaze.chat.completions.stream(
    messages=[{"role": "user", "content": "Tell me a story."}],
)
for event in stream:
    if event.type == "content.delta":
        print(event.delta, end="")
final = stream.get_final_completion()

stream.text_deltas() yields clean visible text only; create(stream=True) returns the raw chunk iterator (side-channel tags not stripped).

Inputs

from interfaze import inputs

inputs.image("https://…/a.png")             # image_url part
inputs.file("https://…/doc.pdf")            # file part (pdf/csv/xml/json/text/video…)
inputs.audio("https://…/a.wav")             # input_audio part
inputs.data_url(raw_bytes, "image/png")     # base64 data URI
inputs.from_path("./doc.pdf")               # read a local file

URLs and base64 both work; image/gif and image/avif are rejected client-side.

Interfaze extras

• res.precontext - raw outputs of any internal tools that ran (OCR/web/scrape/STT/forecast/…).
• res.reasoning - reasoning text (with reasoning_effort="high" and no schema).
• res.vcache - whether the semantic cache was hit.
• reasoning_effort also accepts "on"/"off"/"auto".
• Guardrails: create(guard=["S1", "S12_IMAGE"], …).
• Control options: Interfaze(show_additional_info=..., bypass_moe=..., bypass_cache=..., admin_key=...).

LangChain

pip install interfaze[langchain] adds a chat model pointed at Interfaze that keeps the extras a stock ChatOpenAI drops:

from interfaze.langchain import ChatInterfaze

llm = ChatInterfaze()  # reads INTERFAZE_API_KEY
res = llm.invoke("Summarize the latest AI news")
print(res.response_metadata.get("precontext"), res.response_metadata.get("vcache"))

precontext/reasoning/vcache land on response_metadata, {"type": "video", ...} content blocks are accepted, and inline side-channel tags are stripped.

License

MIT