Notte LLM

LLM-based structured data extraction for Notte. It provides LlmExtractor, the default implementation of the notte_core.extraction.StructuredExtractor protocol that local sessions use for scrape(instructions=..., response_format=...). Cloud sessions run extraction server side and don't need it.

pip install 'notte[llm]'  # or: pip install notte-llm

from notte_browser.session import NotteSession
from notte_llm import LlmExtractor
from pydantic import BaseModel


class Title(BaseModel):
    title: str


with NotteSession(headless=True, extractor=LlmExtractor()) as session:
    _ = session.execute(type="goto", url="https://www.notte.cc")
    data = session.scrape(response_format=Title)

When notte-llm is installed and no extractor is passed, sessions use LlmExtractor() automatically.

Set OPENROUTER_API_KEY to use OpenRouter with google/gemini-3.5-flash-lite by default. For another OpenAI-compatible endpoint, set all three of NOTTE_LLM_BASE_URL, NOTTE_LLM_API_KEY, and NOTTE_LLM_MODEL (the endpoint's own model ID):

OpenAI: NOTTE_LLM_BASE_URL=https://api.openai.com/v1, NOTTE_LLM_MODEL=gpt-4o.
Gemini: NOTTE_LLM_BASE_URL=https://generativelanguage.googleapis.com/v1beta/openai, NOTTE_LLM_MODEL=gemini-3.5-flash-lite.
Ollama/custom: NOTTE_LLM_BASE_URL=http://localhost:11434/v1, your local model ID, and NOTTE_LLM_API_KEY=ollama for an unauthenticated local server. Ollama has not been live-tested.

NOTTE_LLM_API_KEY overrides OPENROUTER_API_KEY. The latter is used only at the default OpenRouter URL, so it is never sent to a custom endpoint. The per-call model= argument selects a model at the configured endpoint without translating its ID.

Variable	Default
`NOTTE_LLM_BASE_URL`	`https://openrouter.ai/api/v1`
`NOTTE_LLM_API_KEY`	`OPENROUTER_API_KEY` at the default URL; required elsewhere
`NOTTE_LLM_MODEL`	`google/gemini-3.5-flash-lite` at the default URL; required elsewhere
`NOTTE_LLM_TEMPERATURE`	`0.0`
`NOTTE_LLM_NB_RETRIES_STRUCTURED_OUTPUT`	`2`
`NOTTE_LLM_CONTEXT_TOKENS`	`128000` (document clipping estimates four characters per token)

The async client posts Chat Completions through httpx with a 60-second timeout per attempt (LLMEngine(timeout=...)), retrying transient errors after 2 and 5 seconds. Typed extraction tries strict json_schema output; when a provider rejects it, the client retries with json_object and the schema in the prompt. If the endpoint also rejects json_object, it uses the schema in the prompt alone. Every answer is still validated with Pydantic, with JSON repair and parsing feedback on retries. Instructions-only extraction starts with json_object because it has no fixed data schema.

OpenRouter receives model fallbacks (google/gemini-3.8-flash, openai/gpt-4.1-mini). LLMEngine(provider_order=[...], reasoning={...}) can also pass OpenRouter routing and reasoning options. These extras are sent only when the configured hostname is openrouter.ai. A provider's content-policy refusal (an OpenRouter, OpenAI or Azure content-filter error, or a content_filter finish reason with no content) raises ContentFilterError naming the model, not InvalidAPIKeyError. For Vertex or other token-based endpoints, mint the access token outside the library and pass it as NOTTE_LLM_API_KEY; refresh it before it expires.

For endpoint-specific request options, pass extra_body to LlmExtractor.extract (or to LLMEngine's constructor). These explicit fields override request defaults for that call; None removes a default field. For example, pin Together without model or provider fallbacks and use its advertised output-token limit:

result = await LlmExtractor(model="meta-llama/llama-3.3-70b-instruct").extract(
    url="https://example.com",
    document="# Example page",
    response_format=Title,
    instructions="Extract the title",
    extra_body={
        "models": None,
        "provider": {"order": ["together"], "allow_fallbacks": False},
        "max_completion_tokens": 2048,
    },
)

Explicit extras are forwarded to any configured endpoint, so use only fields that endpoint supports. The library does not discover provider limits or automatically lower its default 8192 completion tokens. Set max_completion_tokens to your endpoint's limit when it is lower. Overrides do not persist to subsequent calls.

Metadata

Release files for notte-llm 1.10.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for notte-llm 1.10.0
File	Size	Uploaded	Provenance
notte_llm-1.10.0.tar.gz	17.5 kB	Oct 23, 2026	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for notte-llm 1.10.0
File	Interpreter	ABI	Platform	Reset
notte_llm-1.10.0-py3-none-any.whl 20.0 kB Oct 23, 2026 Without provenance	Python 3	none	any	Details

Total release size: 37.5 kB

Release files / notte_llm-1.10.0.tar.gz

Download URL	notte_llm-1.10.0.tar.gz
Size	17.5 kB
Tags	Source
SHA-256 checksum How to use checksums	`992401319e3567e88ed219fa24a8d81bd02a0f3f525aee5567e5b137ea78bbb1`
BLAKE2b-256 checksum How to use checksums	`d45e6bcb460417da7d76f1fd133f5a5186b5c15d8d6af126b8c69fa83c1cb888`
Upload date	Oct 23, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`uv/0.13.5 {"installer":{"name":"uv","version":"0.13.5","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}`

Release files / notte_llm-1.10.0-py3-none-any.whl

Download URL	notte_llm-1.10.0-py3-none-any.whl
Size	20.0 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`ab0112e02235d30b895e2f1de90c6d36c637c76da548348f03398793ba4f138a`
BLAKE2b-256 checksum How to use checksums	`d922d8e8cd6d5982d8a92b30a2abf378fe37a69f5feb382fb497c508b8c236dc`
Upload date	Oct 23, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`uv/0.13.5 {"installer":{"name":"uv","version":"0.13.5","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}`

Security for notte-llm 1.10.0

Report project as malware

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.