langchain-sibfly
LangChain integration for SibFly — measured ground motion for any US address.
Give it a US address (or lat/lon) and it tells your agent how fast the ground is sinking or rising, in mm/year, measured from NASA OPERA Sentinel-1 satellite radar (InSAR) — measured, not modeled. Negative mm/year = sinking.
Agent-friendly pricing: $0.40 per covered report, and misses are free
(out-of-coverage, no-data, too-stale, and low-confidence results all cost $0).
Use dry_run=True for a free coverage + price check first.
Install
pip install -U langchain-sibfly
export SIBFLY_API_KEY="sf_live_..."
Get a key with free starter credits at sibfly.com. Agents
can self-register with no human step:
POST https://sibfly.com/api/v1/autonomous/register.
Usage
from langchain_sibfly import SibflyGroundMotion
motion = SibflyGroundMotion() # reads SIBFLY_API_KEY
# By address
print(motion.invoke({"address": "1100 Congress Ave, Austin, TX"}))
# By coordinates, free preview (no charge)
print(motion.invoke({"lat": 30.3244, "lon": -97.8102, "dry_run": True}))
Example result:
{
"status": "ok",
"velocity_vertical_mm_yr": -6.0,
"velocity_uncertainty_mm_yr": 1.5,
"assessment_code": "notable_subsidence",
"confidence": 0.86,
"data_age_days": 73,
"cost_usd": 0.4,
"credits_remaining_usd": 0.6,
}
Route logic on assessment_code — one of rapid_subsidence,
notable_subsidence, stable, mild_uplift, strong_uplift — not on the
human-readable assessment string.
Free gates (avoid paying for data you'd reject)
dry_run=True— free coverage +would_cost_usd, no reading, no charge.max_age_days=N— if the newest data is older than N days, returns a freestale_dataresult instead of billing.min_confidence=0.0..1.0— below this pixel confidence, returns a freelow_confidenceresult instead of billing.
Use it in an agent
from langchain_sibfly import SibflyGroundMotion
from langgraph.prebuilt import create_react_agent
from langchain_anthropic import ChatAnthropic
agent = create_react_agent(
ChatAnthropic(model="claude-sonnet-5"),
tools=[SibflyGroundMotion()],
)
agent.invoke({"messages": [("user", "Is the ground sinking at 1100 Congress Ave, Austin TX?")]})
Links
- API: https://sibfly.com · Docs: https://sibfly.com/docs · Agent docs: https://sibfly.com/llms.txt
- OpenAPI: https://sibfly.com/openapi.json · Machine schema: https://sibfly.com/api/v1/schema
- MCP server:
https://sibfly.com/mcp(also in the official MCP registry ascom.sibfly/ground-motion)
License
MIT
Metadata
Release files for langchain-sibfly 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| langchain_sibfly-0.1.0.tar.gz | 7.6 kB | Without provenance | Details for langchain_sibfly-0.1.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| langchain_sibfly-0.1.0-py3-none-any.whl | Python 3 | none | any | Details for langchain_sibfly-0.1.0-py3-none-any.whl |
Total release size: 15.4 kB
Release files / langchain_sibfly-0.1.0.tar.gz
| Download URL | langchain_sibfly-0.1.0.tar.gz |
|---|---|
| Size | 7.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d246a1bd54aaf0cd66f9b0e27d38772c757f551eb70b27f3bb4937aabac5d4c1
|
|
BLAKE2b-256 checksum How to use checksums |
08b5c194c606c75992a362562f2d6a79f627b187007d792d9ff0ca0233834235
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.12
|
Release files / langchain_sibfly-0.1.0-py3-none-any.whl
| Download URL | langchain_sibfly-0.1.0-py3-none-any.whl |
|---|---|
| Size | 7.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
771e87db02a5da472c0cf3672354901809076cd44b5a72ab46634e72c4a5f605
|
|
BLAKE2b-256 checksum How to use checksums |
4ceb2615e16cc456f58fd0d7da8f7c65b737b5297c412c81128ab352b4b44917
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.12
|
Security for langchain-sibfly 0.1.0
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.