llama-index-readers-maps


Namellama-index-readers-maps JSON
Version 0.1.2 PyPI version JSON
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Summaryllama-index readers maps integration
upload_time2024-02-13 21:14:06
maintainercarrotpy
docs_urlNone
authorYour Name
requires_python>=3.8.1,<3.12
licenseMIT
keywords geo maps open maps open street maps overpass api
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            # **_Osmmap Loader_**

The Osmmap Loader will fetch map data from the [Overpass](https://wiki.openstreetmap.org/wiki/Main_Page) api for a certain place or area. Version **Overpass API 0.7.60** is used by this loader.

The api will provide you with all the **nodes, relations, and ways** for the particular region when you request data for a region or location.

## **Functions of the loader**

- To start, it first filters out those nodes that are already tagged, leaving just those nodes that are within 2 kilometres of the target location. The following keys are removed during filtering:["nodes," "geometry," "members"] from each node. The response we received is based on the tags and values we provided, so be sure to do that. The actions are covered below.

## **Steps to find the suitable tag and values**

1. Visit [Taginfo](taginfo.openstreetmap.org/tags). In essence, this website has all conceivable tags and values.
2. Perform a search for the feature you're looking for, for instance, "hospital" will return three results: "hospital" as an amenity, "hospital" as a structure, and "hospital" as a healthcare facility.
3. We may infer from the outcome that tag=amenity and value=hospital.
4. Leave the values parameter to their default value if you do not need to filter.

## **Usage**

The use case is here.

Let's meet **Jayasree**, who is extracting map features from her neighbourhood using the OSM map loader.
She requires all the nodes, routes, and relations within a five-kilometer radius of her locale (Guduvanchery).

- She must use the following arguments in order to accomplish the aforementioned. Localarea = "Guduvanchery" (the location she wants to seek), local_area_buffer = 5000 (5 km).

### And the code snippet looks like

```python
from llama_index import download_loader

MapReader = download_loader("OpenMap")

loader = MapReader()
documents = loader.load_data(
    localarea="Guduvanchery",
    search_tag="",
    tag_only=True,
    local_area_buffer=5000,
    tag_values=[""],
)
```

### Now she wants only the list hospitals around the location

- so she search for hospital tag in the [Taginfo](https://taginfo.openstreetmap.org/tags) and she got

```python
from llama_index import download_loader

MapReader = download_loader("OpenMap")

loader = MapReader()
documents = loader.load_data(
    localarea="Guduvanchery",
    search_tag="amenity",
    tag_only=True,
    local_area_buffer=5000,
    tag_values=["hospital", "clinic"],
)
```

This loader is designed to be used as a way to load data into [LlamaIndex](https://github.com/run-llama/llama_index/tree/main/llama_index) and/or subsequently used as a Tool in a [LangChain](https://github.com/hwchase17/langchain) Agent. See [here](https://github.com/emptycrown/llama-hub/tree/main) for examples.

            

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    "description": "# **_Osmmap Loader_**\n\nThe Osmmap Loader will fetch map data from the [Overpass](https://wiki.openstreetmap.org/wiki/Main_Page) api for a certain place or area. Version **Overpass API 0.7.60** is used by this loader.\n\nThe api will provide you with all the **nodes, relations, and ways** for the particular region when you request data for a region or location.\n\n## **Functions of the loader**\n\n- To start, it first filters out those nodes that are already tagged, leaving just those nodes that are within 2 kilometres of the target location. The following keys are removed during filtering:[\"nodes,\" \"geometry,\" \"members\"] from each node. The response we received is based on the tags and values we provided, so be sure to do that. The actions are covered below.\n\n## **Steps to find the suitable tag and values**\n\n1. Visit [Taginfo](taginfo.openstreetmap.org/tags). In essence, this website has all conceivable tags and values.\n2. Perform a search for the feature you're looking for, for instance, \"hospital\" will return three results: \"hospital\" as an amenity, \"hospital\" as a structure, and \"hospital\" as a healthcare facility.\n3. We may infer from the outcome that tag=amenity and value=hospital.\n4. Leave the values parameter to their default value if you do not need to filter.\n\n## **Usage**\n\nThe use case is here.\n\nLet's meet **Jayasree**, who is extracting map features from her neighbourhood using the OSM map loader.\nShe requires all the nodes, routes, and relations within a five-kilometer radius of her locale (Guduvanchery).\n\n- She must use the following arguments in order to accomplish the aforementioned. Localarea = \"Guduvanchery\" (the location she wants to seek), local_area_buffer = 5000 (5 km).\n\n### And the code snippet looks like\n\n```python\nfrom llama_index import download_loader\n\nMapReader = download_loader(\"OpenMap\")\n\nloader = MapReader()\ndocuments = loader.load_data(\n    localarea=\"Guduvanchery\",\n    search_tag=\"\",\n    tag_only=True,\n    local_area_buffer=5000,\n    tag_values=[\"\"],\n)\n```\n\n### Now she wants only the list hospitals around the location\n\n- so she search for hospital tag in the [Taginfo](https://taginfo.openstreetmap.org/tags) and she got\n\n```python\nfrom llama_index import download_loader\n\nMapReader = download_loader(\"OpenMap\")\n\nloader = MapReader()\ndocuments = loader.load_data(\n    localarea=\"Guduvanchery\",\n    search_tag=\"amenity\",\n    tag_only=True,\n    local_area_buffer=5000,\n    tag_values=[\"hospital\", \"clinic\"],\n)\n```\n\nThis loader is designed to be used as a way to load data into [LlamaIndex](https://github.com/run-llama/llama_index/tree/main/llama_index) and/or subsequently used as a Tool in a [LangChain](https://github.com/hwchase17/langchain) Agent. See [here](https://github.com/emptycrown/llama-hub/tree/main) for examples.\n",
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