> ## Documentation Index
> Fetch the complete documentation index at: https://unstructured-53-docs-243-plugins.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# MongoDB

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Connect MongoDB to your preprocessing pipeline, and use the Unstructured Ingest CLI or the Unstructured Ingest Python library to batch process all your documents and store structured outputs locally on your filesystem.

The requirements are as follows.

The MongoDB requirements for a MongoDB Atlas deployment include:

<iframe width="560" height="315" src="https://www.youtube.com/embed/g6qDfbg808M" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen />

* A MongoDB Atlas account. [Create an account](https://www.mongodb.com/cloud/atlas/register).

* A MongoDB Atlas cluster. [Create a cluster](https://www.mongodb.com/docs/atlas/tutorial/deploy-free-tier-cluster).

* The cluster must be reachable from your application environment. [Learn how](https://www.mongodb.com/docs/atlas/setup-cluster-security/#network-and-firewall-requirements).

* The cluster must be configured to allow IP address. [Learn how](https://www.mongodb.com/docs/atlas/setup-cluster-security/#ip-access-list).

  To get Unstructured's IP address ranges, go to
  [https://assets.p6m.u10d.net/publicitems/ip-prefixes.json](https://assets.p6m.u10d.net/publicitems/ip-prefixes.json)
  and allow all of the `ip_prefix` fields' values that are listed.

  <Note>These IP address ranges are subject to change. You can always find the latest ones in the preceding file.</Note>

* The cluster must have at least one database. [Create a database](https://www.mongodb.com/docs/compass/current/databases/#create-a-database).

* The database must have at least one user, and that user must have sufficient access to the database. [Create a database user](https://www.mongodb.com/docs/atlas/security-add-mongodb-users/#add-database-users). [Give the user database access](https://www.mongodb.com/docs/manual/core/authorization/).

* The database must have at least one collection. [Create a collection](https://www.mongodb.com/docs/compass/current/collections/#create-a-collection).

  <Note>
    For the destination connector, Unstructured recommends that all documents in the target collection have a field
    named `record_id` with a `String` data type.
    Unstructured can use this field to do intelligent document overwrites. Without this field, duplicate documents
    might be written to the collection or, in some cases, the operation could fail altogether.
  </Note>

* The connection string for the cluster. For MongoDB Atlas, this connection string must include the protocol, username, password, host, and cluster name. For example:

  ```text theme={null}
  mongodb+srv://<db_user>:<db_password>@<host>/?retryWrites=true&w=majority&appName=<cluster>
  ```

  To get the connection string in MongoDB Atlas, do the following:

  1. Log in to your MongoDB Atlas console.
  2. In the sidebar, under **Databases**, click **Clusters**.
  3. Click on the cluster you want to connect to.
  4. Click **Connect**, or click the **Cmd Line Tools** tab and then click **Connect Instructions**.
  5. Click **Drivers**.
  6. Under **Add your connection string into your application code**, copy the connection string.
     You can then close the **Connect** dialog in MongoDB Atlas.

     Before you use this connection string, be sure to fill in any placeholders in the string, such as your MongoDB Atlas database user's password value.

  [Learn more](https://www.mongodb.com/resources/products/fundamentals/mongodb-connection-string).

The MongoDB connector dependencies:

```bash CLI, Python theme={null}
pip install "unstructured-ingest[mongodb]"
```

You might also need to install additional dependencies, depending on your needs. [Learn more](/ingestion/ingest-dependencies).

For a MongoDB Atlas deployment, the following environment variables:

* `MONGODB_DATABASE` - The name of the database, represented by `--database` (CLI) or `database` (Python).

* `MONGODB_COLLECTION` - The name of the collection in the database, represented by `--collection` (CLI) or `collection` (Python).

* `MONGODB_URI` - The connection string for the cluster, represented by `--uri` (CLI) or `uri` (Python).

For a local MongoDB server, the following environment variables:

* `MONGODB_HOST` - The host for the local MongoDB server, represented by `--host` (CLI) or `host` (Python).

* `MONGODB_PORT` - The port for the local MongoDB server, represented by `--port` (CLI) or `port` (Python).

Now call the Unstructured Ingest CLI or the Unstructured Ingest Python library. The destination connector can be any of the ones supported. This example uses the local destination connector:

This example sends data to Unstructured for processing by default. To process data locally instead, see the instructions at the end of this page.

<CodeGroup>
  ```bash CLI theme={null}
  #!/usr/bin/env bash

  unstructured-ingest \
    mongodb \
      --metadata-exclude filename,file_directory,metadata.data_source.date_processed \
      --uri $MONGODB_URI \
      --database $MONGODB_DATABASE \
      --collection $MONGODB_COLLECTION \
      --output-dir $LOCAL_FILE_OUTPUT_DIR \
      --num-processes 2 \
      --partition-by-api \
      --api-key $UNSTRUCTURED_API_KEY \
      --partition-endpoint $UNSTRUCTURED_API_URL \
      --strategy hi_res \
      --additional-partition-args="{\"split_pdf_page\":\"true\", \"split_pdf_allow_failed\":\"true\", \"split_pdf_concurrency_level\": 15}" \
  ```

  ```python Python Ingest theme={null}
  import os

  from unstructured_ingest.pipeline.pipeline import Pipeline
  from unstructured_ingest.interfaces import ProcessorConfig

  from unstructured_ingest.processes.connectors.mongodb import (
      MongoDBAccessConfig,
      MongoDBConnectionConfig,
      MongoDBIndexerConfig,
      MongoDBDownloaderConfig
  )
  from unstructured_ingest.processes.connectors.local import LocalConnectionConfig
  from unstructured_ingest.processes.partitioner import PartitionerConfig
  from unstructured_ingest.processes.chunker import ChunkerConfig
  from unstructured_ingest.processes.embedder import EmbedderConfig

  # Chunking and embedding are optional.

  if __name__ == "__main__":
      Pipeline.from_configs(
          context=ProcessorConfig(),
          indexer_config=MongoDBIndexerConfig(batch_size=100),
          downloader_config=MongoDBDownloaderConfig(download_dir=os.getenv("LOCAL_FILE_DOWNLOAD_DIR")),
          source_connection_config=MongoDBConnectionConfig(
              access_config=MongoDBAccessConfig(uri=os.getenv("MONGODB_URI")),
              database=os.getenv("MONGODB_DATABASE"),
              collection=os.getenv("MONGODB_COLLECTION")
          ),
          partitioner_config=PartitionerConfig(
              partition_by_api=True,
              api_key=os.getenv("UNSTRUCTURED_API_KEY"),
              partition_endpoint=os.getenv("UNSTRUCTURED_API_URL"),
              additional_partition_args={
                  "split_pdf_page": True,
                  "split_pdf_allow_failed": True,
                  "split_pdf_concurrency_level": 15
              }
          ),
          chunker_config=ChunkerConfig(chunking_strategy="by_title"),
          embedder_config=EmbedderConfig(embedding_provider="huggingface"),
          destination_connection_config=LocalConnectionConfig()
      ).run()
  ```
</CodeGroup>

For the Unstructured Ingest CLI and the Unstructured Ingest Python library, you can use the `--partition-by-api` option (CLI) or `partition_by_api` (Python) parameter to specify where files are processed:

* To do local file processing, omit `--partition-by-api` (CLI) or `partition_by_api` (Python), or explicitly specify `partition_by_api=False` (Python).

  Local file processing does not use an Unstructured API key or API URL, so you can also omit the following, if they appear:

  * `--api-key $UNSTRUCTURED_API_KEY` (CLI) or `api_key=os.getenv("UNSTRUCTURED_API_KEY")` (Python)
  * `--partition-endpoint $UNSTRUCTURED_API_URL` (CLI) or `partition_endpoint=os.getenv("UNSTRUCTURED_API_URL")` (Python)
  * The environment variables `UNSTRUCTURED_API_KEY` and `UNSTRUCTURED_API_URL`

* To send files to the [Unstructured Partition Endpoint](/api-reference/partition/overview) for processing, specify `--partition-by-api` (CLI) or `partition_by_api=True` (Python).

  Unstructured also requires an Unstructured API key and API URL, by adding the following:

  * `--api-key $UNSTRUCTURED_API_KEY` (CLI) or `api_key=os.getenv("UNSTRUCTURED_API_KEY")` (Python)
  * `--partition-endpoint $UNSTRUCTURED_API_URL` (CLI) or `partition_endpoint=os.getenv("UNSTRUCTURED_API_URL")` (Python)
  * The environment variables `UNSTRUCTURED_API_KEY` and `UNSTRUCTURED_API_URL`, representing your API key and API URL, respectively.

  <Note>
    You must specify the API URL only if you are not using the default API URL for Unstructured Ingest, for example, if you are using a version of the Unstructured API that is hosted on your own compute infrastructure.

    The default API URL for Unstructured Ingest is `https://api.unstructuredapp.io/general/v0/general`, which is the API URL for the [Unstructured Partition Endpoint](/api-reference/partition/overview).

    If you do not have an API key, [get one now](/api-reference/partition/overview).

    If the Unstructured API is hosted on your own compute infrastructure, the process
    for generating Unstructured API keys, and the Unstructured API URL that you use, are different.
    For details, contact Unstructured Sales at
    [sales@unstructured.io](mailto:sales@unstructured.io).
  </Note>