GeoAgent 1.4.0

Centralized AI agent framework for Open Geospatial Python packages and QGIS plugins (Strands Agents)

GeoAgent

GeoAgent is a shared AI agent layer for geospatial Python packages, live map widgets, and QGIS plugins. It gives projects such as leafmap, anymap, geoai, geemap, STAC workflows, NASA Earthdata workflows, and QGIS plugins one consistent way to expose geospatial tools to large language models.

GeoAgent is built on Strands Agents. It wraps Strands with geospatial context, tool metadata, optional package adapters, provider configuration, and confirmation hooks for operations that should not run silently.

Why GeoAgent?

Many geospatial libraries need the same agent features:

• bind an agent to a live map, QGIS session, dataset, or workflow object;
• expose package functions as structured tools with docstrings and metadata;
• support OpenAI, ChatGPT/Codex OAuth, Anthropic, Google Gemini, Bedrock, LiteLLM, and local Ollama models;
• keep optional geospatial stacks optional;
• ask for confirmation before deleting layers, saving files, or running expensive processing jobs;
• support multimodal plugin workflows such as pasted images and screenshots when the selected model provider supports vision;
• provide a stable integration point for downstream packages and plugins.

GeoAgent centralizes that layer so each package does not need to maintain its own agent framework.

Core Concepts

Concept	Purpose
GeoAgent	High-level facade around a Strands Agent.
GeoAgentConfig	Provider, model, temperature, token, and client settings.
GeoAgentContext	Runtime objects bound to the agent, such as a map or QGIS iface.
@geo_tool	Decorator that turns a Python function into a Strands tool with GeoAgent metadata.
GeoToolRegistry	Registry for tool metadata, safety flags, categories, and fast-mode filtering.
for_leafmap	Factory that binds tools to a leafmap.Map-compatible object.
for_anymap	Factory that binds tools to an anymap.Map-compatible object.
for_qgis	Factory that binds tools to qgis.utils.iface and an optional QgsProject.
for_nasa_opera	Factory that binds NASA OPERA search/display tools plus QGIS tools.
for_stac	Factory that binds STAC catalog search/asset tools plus optional QGIS loading.
create_agent	Factory for custom tools or package-specific integrations.

Installation

Install the core package:

pip install GeoAgent

Core installs only the agent framework dependencies, mainly strands-agents and pydantic. Geospatial packages and provider clients are optional extras:

Extra	Purpose
GeoAgent[openai]	OpenAI model support through Strands.
GeoAgent[anthropic]	Anthropic Claude model support through Strands.
GeoAgent[gemini]	Google Gemini model support through Strands.
GeoAgent[ollama]	Local Ollama model support.
GeoAgent[litellm]	LiteLLM model support for many hosted and proxy providers.
GeoAgent[leafmap]	leafmap live map integration.
GeoAgent[anymap]	anymap live map integration.
GeoAgent[stac]	STAC client dependencies.
GeoAgent[earthdata]	NASA Earthdata dependencies.
GeoAgent[nasa-opera]	NASA OPERA search dependencies.
GeoAgent[geoai]	geoai integration dependencies.
GeoAgent[earthengine]	Google Earth Engine dependencies.
GeoAgent[ui]	Solara UI dependencies.
GeoAgent[providers]	OpenAI, Anthropic, Gemini, Ollama, and LiteLLM provider clients.
GeoAgent[all]	Most optional integrations. QGIS itself remains system-installed.

Examples:

pip install "GeoAgent[leafmap,openai]"
pip install "GeoAgent[anymap,anthropic]"
pip install "GeoAgent[stac,earthdata,openai]"

For QGIS, install GeoAgent in the Python environment used by QGIS. The GeoAgent[qgis] extra is a marker extra; QGIS is provided by the desktop application or system package manager.

Provider Configuration

GeoAgent selects a provider from environment variables when no provider is specified:

Provider	Environment
OpenAI	OPENAI_API_KEY, optional OPENAI_MODEL
ChatGPT/Codex OAuth	OPENAI_CODEX_ACCESS_TOKEN, optional OPENAI_CODEX_MODEL
Anthropic	ANTHROPIC_API_KEY, optional ANTHROPIC_MODEL
Google Gemini	GEMINI_API_KEY or GOOGLE_API_KEY, optional GEMINI_MODEL
LiteLLM	LITELLM_API_KEY, optional LITELLM_MODEL and LITELLM_BASE_URL
Ollama	OLLAMA_HOST or USE_OLLAMA=1, optional OLLAMA_MODEL
Bedrock	AWS credential chain and model access, optional BEDROCK_MODEL

ChatGPT/Codex OAuth uses the Codex browser login flow and the Codex Responses backend.

For notebooks and Python scripts, log in once with the CLI:

geoagent codex login

or from Python/Jupyter:

from geoagent import login_openai_codex

login_openai_codex()

GeoAgent stores the refresh token in your user config directory and exports OPENAI_CODEX_ACCESS_TOKEN for the current Python process. Later sessions can reuse the stored login automatically, or explicitly call:

from geoagent import ensure_openai_codex_environment

ensure_openai_codex_environment()

You can also configure providers explicitly:

from geoagent import GeoAgentConfig, for_leafmap

agent = for_leafmap(
    m,
    config=GeoAgentConfig(
        provider="openai",
        model="gpt-5.5",
        temperature=0,
        max_tokens=4096,
    ),
)

Factories also accept provider= and model_id= shortcuts:

agent = for_leafmap(m, provider="gemini", model_id="gemini-3.1-pro-preview")

Quickstart

Use GeoAgent directly when you do not need a map or package-specific toolset:

from geoagent import GeoAgent, GeoAgentConfig

agent = GeoAgent(config=GeoAgentConfig(provider="openai", model="gpt-5.5"))
resp = agent.chat("Explain STAC in two sentences.")
print(resp.answer_text)

Stream model output as it is generated:

import asyncio
from geoagent import GeoAgent

agent = GeoAgent()

async def main():
    async for event in agent.stream_chat("Explain STAC in two sentences."):
        if "data" in event:
            print(event["data"], end="", flush=True)

asyncio.run(main())

Bind an agent to a live leafmap map:

import leafmap
from geoagent import for_leafmap

m = leafmap.Map()
agent = for_leafmap(m)

resp = agent.chat("Add a marker for Knoxville and zoom to it.")
print(resp.answer_text)
m

Bind an agent to an anymap map:

import anymap
from geoagent import for_anymap

m = anymap.Map()
agent = for_anymap(m)
agent.chat("Change the basemap and list the current layers.")

Use GeoAgent inside QGIS:

from qgis.utils import iface
from geoagent import for_qgis

agent = for_qgis(iface)
resp = agent.chat("Summarize the project layers and zoom to the active layer.")
print(resp.answer_text)

geoagent.tools.qgis is import-safe outside QGIS. It imports QGIS classes only inside tool bodies, so tests and non-QGIS environments can import the module.

The OpenGeoAgent QGIS plugin adds a dockable chat UI on top of this factory. It supports provider and model controls, streaming responses, pasted image attachments, screenshot capture from the map canvas, QGIS window, or selected screen regions, image preview and save actions, Markdown transcript copying, and copying the PyQGIS script used for an executed result.

QGIS Plugin

OpenGeoAgent is the QGIS plugin interface for GeoAgent. It adds a dockable AI assistant to QGIS so you can inspect projects, navigate the map canvas, load data, run processing workflows, style layers, and execute confirmation-gated PyQGIS scripts from natural language.

Key plugin features:

• provider and model controls for Bedrock, OpenAI, ChatGPT/Codex OAuth, Anthropic, Google Gemini, Ollama, and LiteLLM;
• project-aware QGIS tools for layers, selections, map navigation, processing, project saving, and attribute table actions;
• image-aware chat with clipboard paste and screenshot attachments for models that support vision inputs;
• screenshot capture from the map canvas, selected map regions, the QGIS window, and selected screen regions;
• image preview and save/export actions, plus inline rendering of image outputs returned by multimodal models;
• direct image generation with the generate_image tool when OPENAI_API_KEY is configured;
• copy Markdown transcript and copy executed PyQGIS script actions;
• confirmation-gated run_pyqgis_script fallback when a task needs QGIS API operations that are not covered by a dedicated tool;
• lazy dependency checks so opening the chat dock stays responsive.

See the QGIS plugin documentation for setup and usage.

Built-In Tool Surfaces

leafmap and anymap

for_leafmap(m) and for_anymap(m) expose a shared map-control surface:

• inspect state and layers: get_map_state, list_layers;
• navigate: set_center, fly_to, set_zoom, zoom_in, zoom_out, zoom_to_bounds, zoom_to_layer;
• manage layers: add_layer, remove_layer, clear_layers, set_layer_visibility, set_layer_opacity;
• add data: add_vector_data, add_geojson_data, add_raster_data, add_cog_layer, add_stac_layer, add_xyz_tile_layer, add_pmtiles_layer, add_marker;
• change basemaps and export maps: change_basemap, save_map.

Layer lookup accepts exact names or a unique case-insensitive substring for operations such as remove_layer, zoom_to_layer, set_layer_visibility, and set_layer_opacity.

QGIS

for_qgis(iface, project=None) exposes tools that run through a Qt GUI-thread marshaller:

• inspect project and layer state: list_project_layers, get_active_layer, get_project_state, get_layer_summary, inspect_layer_fields, get_selected_features;
• navigate: zoom_in, zoom_out, zoom_to_layer, zoom_to_extent, zoom_to_selected, set_center, set_scale, refresh_canvas;
• manage layers and data: add_vector_layer, add_raster_layer, add_xyz_tile_layer, remove_layer, set_layer_visibility, set_layer_opacity;
• select and process: select_features_by_expression, clear_selection, run_processing_algorithm;
• open QGIS UI and save: open_attribute_table, save_project;
• run confirmation-gated PyQGIS fallback scripts with run_pyqgis_script when a task requires QGIS API operations that are not covered by a dedicated tool.

QGIS chat uses a sequential tool executor and GUI-thread marshalling so map canvas and layer-tree calls are routed safely. The PyQGIS fallback receives the current iface, project, canvas, and active_layer, making it useful for actions such as raster band renderer changes, labeling tweaks, layer tree updates, and other QGIS API operations.

NASA OPERA

for_nasa_opera(iface, project=None) exposes NASA OPERA product tools and the standard QGIS tool surface:

• inspect OPERA products: get_available_datasets, get_dataset_info;
• search Earthdata granules: search_opera_data;
• display results: display_footprints, display_raster, create_mosaic.

The OPERA integration is implemented as native GeoAgent tools and does not wrap the NASA OPERA plugin's legacy nasa_opera.ai.tools registry.

When adding OPERA capabilities, implement the reusable tool logic in geoagent/tools/nasa_opera.py. Keep the NASA OPERA QGIS plugin focused on UI, settings, provider selection, progress display, and compatibility aliases. The plugin consumes GeoAgent tool metadata automatically, so new GeoAgent OPERA tools are available to the plugin AI Assistant without duplicating tool logic.

Use it from the QGIS Python console or from plugin code. For direct tool testing, use submit_nasa_opera_search_task(...); this avoids LLM/provider initialization and reports progress in QGIS's message bar and Log Messages panel:

from geoagent.tools.nasa_opera import submit_nasa_opera_search_task

task = submit_nasa_opera_search_task(
    iface,
    dataset="OPERA_L3_DSWX-HLS_V1",
    bbox="-95.5,29.5,-95.0,30.0",
    start_date="2024-01-01",
    end_date="2024-01-31",
    max_results=5,
    display_footprints=True,
)

For a longer QGIS-console script, see examples/nasa_opera_qgis.py.

Natural-language OPERA chat is intentionally disabled inside QGIS for now. Use direct tools or submit_nasa_opera_search_task(...) so QGIS task/thread ownership remains explicit.

Vantor Open Data

for_vantor(iface, project=None, plugin=None) exposes native tools for the QGIS Vantor plugin's public Open Data STAC catalog:

• browse event collections: list_vantor_events, get_vantor_event_info;
• search imagery: get_current_vantor_search_extent, search_vantor_items;
• display results in QGIS: display_vantor_footprints, load_vantor_cog;
• open the plugin UI when a plugin instance is supplied: open_vantor_panel.

Footprint display and COG loading are confirmation-gated because they add layers to the current QGIS project.

Direct Tool Calls

Every GeoAgent exposes the underlying Strands tool caller. This is useful for tests, notebooks, and plugin UI actions:

agent = for_leafmap(m)
agent.tool.add_marker(lat=35.9606, lon=-83.9207, name="Knoxville")
agent.tool.list_layers()

You can inspect registered tool names and metadata:

agent.tool_names
agent.tool_registry.get_all_tools_config()

Safety and Confirmation

Tools carry metadata such as requires_confirmation, destructive, and long_running. Confirmation is enforced by a Strands hook before gated tools run.

By default, confirmation-required tools are denied unless you pass a confirmation callback:

from geoagent import auto_approve_all, for_leafmap

agent = for_leafmap(m, confirm=auto_approve_all)

For real applications, pass a callback that opens a Qt dialog, notebook modal, web UI prompt, or CLI prompt. Use confirmation for operations that delete data, overwrite files, save projects, launch expensive jobs, or call external services with cost implications.

Custom Tools

Package integrations can expose their own functions with @geo_tool:

from geoagent import GeoAgentContext, create_agent, geo_tool

@geo_tool(category="demo")
def buffer_distance(layer_name: str, distance: float) -> str:
    """Buffer a named layer by a distance in map units."""
    return f"Buffered {layer_name} by {distance}."

agent = create_agent(
    context=GeoAgentContext(),
    tools=[buffer_distance],
)

For package-specific adapters, prefer a factory that binds live objects through closures, just like for_leafmap, for_anymap, and for_qgis. This keeps widgets, clients, credentials, and session objects out of the LLM-visible arguments.

Fast Mode

Pass fast=True to reduce the exposed tool surface and cap response tokens for lower-latency map control:

agent = for_leafmap(m, fast=True)

Fast mode keeps common inspection, navigation, and basemap tools, filters out heavier or more specialized tools, and limits model responses to short post-tool replies. The cap is conservative enough for tool calls while avoiding very long responses. The model call still dominates latency for local models, so small prompts may not show a large timing difference on every provider.

Examples

Runnable notebooks live under docs/examples/:

• docs/examples/intro.ipynb — basic GeoAgent usage.
• docs/examples/openai_codex.ipynb — ChatGPT/Codex OAuth in Python/Jupyter.
• docs/examples/stream_chat_openai_codex.ipynb — streamed ChatGPT/Codex output.
• docs/examples/live_mapping.ipynb — live map workflow.
• docs/examples/qgis_agent.ipynb — QGIS-oriented workflow using mocks.
• docs/examples/stac_workflow.ipynb — STAC catalog search and mock QGIS loading.
• examples/nasa_opera_qgis.py — NASA OPERA workflow for QGIS.

Prompt ideas:

• "List layers on the current map."
• "Add a marker for Seattle and zoom to it."
• "Show the QGIS project state and summarize each layer."
• "Select parcels where population is greater than 10000."
• "Add a STAC layer and set its opacity to 0.6."
• "Search for January 2024 OPERA surface water near Houston and display the footprints."

Development

git clone https://github.com/opengeos/GeoAgent.git
cd GeoAgent
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
pre-commit install

Run checks:

ruff check geoagent tests
pytest -q

See docs/contributing.md for guidance on adding new package and tool integrations.

License

GeoAgent is released under the MIT License. See LICENSE.

Links

• Documentation: https://geoagent.gishub.org
• Repository: https://github.com/opengeos/GeoAgent
• Issues: https://github.com/opengeos/GeoAgent/issues
• Strands Agents: https://strandsagents.com