> ## 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.
# S3
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Batch process all your records to store structured outputs in an S3 bucket.
The requirements are as follows.
The following video shows how to fulfill the minimum set of Amazon S3 requirements:
The preceding video does not show how to create an AWS account; enable anonymous access to the bucket (which is supported but
not recommended); or generate an AWS STS session token for temporary access, if required by your organization's security
requirements. For more information about requirements, see the following:
* An AWS account. [Create an AWS account](https://aws.amazon.com/free).
* An S3 bucket. [Create an S3 bucket](https://docs.aws.amazon.com/AmazonS3/latest/userguide/creating-bucket.html).
Additional approaches are in the following video and in the how-to sections at the end of this page.
* Anonymous (supported but not recommended) or authenticated access to the bucket.
* [Enable anonymous bucket access](https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-bucket-policies.html#example-bucket-policies-anonymous-user).
* [Enable authenticated bucket access](https://docs.aws.amazon.com/AmazonS3/latest/userguide/walkthrough1.html).
* For authenticated bucket read access, the authenticated AWS IAM user must have at minimum the permissions of `s3:ListBucket` and `s3:GetObject` for that bucket. [Learn how](https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-policies-s3.html).
* For bucket write access, authenticated access to the bucket must be enabled (anonymous access must not be enabled), and the authenticated AWS IAM user must have at
minimum the permission of `s3:PutObject` for that bucket. [Learn how](https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-policies-s3.html).
* For authenticated access, an AWS access key and secret access key for the authenticated AWS IAM user in the account.
[Create an AWS access key and secret access key](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_access-keys.html#Using_CreateAccessKey).
* For authenticated access in untrusted environments or enhanced security scenarios, an AWS STS session token for temporary access, in addition to an AWS access key and secret access key. [Create a session token](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_request.html#api_getsessiontoken).
* If the target files are in the root of the bucket, the path to the bucket, formatted as `protocol://bucket/` (for example, `s3://my-bucket/`).
If the target files are in a folder, the path to the target folder in the S3 bucket, formatted as `protocol://bucket/path/to/folder/` (for example, `s3://my-bucket/my-folder/`).
* If the target files are in a folder, and authenticated bucket access is enabled, make sure the authenticated AWS IAM user has
authenticated access to the folder as well. [Enable authenticated folder access](https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-bucket-policies.html#example-bucket-policies-folders).
The S3 connector dependencies:
```bash CLI, Python theme={null}
pip install "unstructured-ingest[s3]"
```
You might also need to install additional dependencies, depending on your needs. [Learn more](/ingestion/ingest-dependencies).
The following environment variables:
* `AWS_S3_URL` - The path to the S3 bucket or folder, formatted as `s3://my-bucket/` (if the files are in the bucket's root) or `s3://my-bucket/my-folder/`.
* If the bucket does not have anonymous access enabled, provide the AWS credentials:
* `AWS_ACCESS_KEY_ID` - The AWS access key ID for the authenticated AWS IAM user, represented by `--key` (CLI) or `key` (Python).
* `AWS_SECRET_ACCESS_KEY` - The corresponding AWS secret access key, represented by `--secret` (CLI) or `secret` (Python).
* `AWS_TOKEN` - If required, the AWS STS session token for temporary access, represented by `--token` (CLI) or `token` (Python).
* If the bucket has anonymous access enabled for reading from the bucket, set `--anonymous` (CLI) or `anonymous=True` (Python) instead.
Now call the Unstructured Ingest CLI or the Unstructured Ingest Python library. The source connector can be any of the ones supported. This example uses the local source connector.
This example sends files to Unstructured for processing by default. To process files locally instead, see the instructions at the end of this page.
```bash CLI theme={null}
#!/usr/bin/env bash
# Chunking and embedding are optional.
unstructured-ingest \
local \
--input-path $LOCAL_FILE_INPUT_DIR \
--partition-by-api \
--api-key $UNSTRUCTURED_API_KEY \
--partition-endpoint $UNSTRUCTURED_API_URL \
--strategy hi_res \
--chunking-strategy by_title \
--embedding-provider huggingface \
--additional-partition-args="{\"split_pdf_page\":\"true\", \"split_pdf_allow_failed\":\"true\", \"split_pdf_concurrency_level\": 15}" \
s3 \
--remote-url $AWS_S3_URL \
--key $AWS_ACCESS_KEY_ID \
--secret $AWS_SECRET_ACCESS_KEY
```
```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.local import (
LocalIndexerConfig,
LocalDownloaderConfig,
LocalConnectionConfig
)
from unstructured_ingest.processes.partitioner import PartitionerConfig
from unstructured_ingest.processes.chunker import ChunkerConfig
from unstructured_ingest.processes.embedder import EmbedderConfig
from unstructured_ingest.processes.connectors.fsspec.s3 import (
S3ConnectionConfig,
S3AccessConfig,
S3UploaderConfig
)
# Chunking and embedding are optional.
if __name__ == "__main__":
Pipeline.from_configs(
context=ProcessorConfig(),
indexer_config=LocalIndexerConfig(input_path=os.getenv("LOCAL_FILE_INPUT_DIR")),
downloader_config=LocalDownloaderConfig(),
source_connection_config=LocalConnectionConfig(),
partitioner_config=PartitionerConfig(
partition_by_api=True,
api_key=os.getenv("UNSTRUCTURED_API_KEY"),
partition_endpoint=os.getenv("UNSTRUCTURED_API_URL"),
strategy="hi_res",
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=S3ConnectionConfig(
access_config=S3AccessConfig(
key=os.getenv("AWS_ACCESS_KEY_ID"),
secret=os.getenv("AWS_SECRET_ACCESS_KEY")
)
),
uploader_config=S3UploaderConfig(remote_url=os.getenv("AWS_S3_URL"))
).run()
```
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.
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).
## Add an access policy to an existing bucket
To use the Amazon S3 console to add an access policy that allows all authenticated AWS IAM users in the
corresponding AWS account to read and write to an existing S3 bucket, do the following.
Your organization might have stricter bucket policy requirements. Check with your AWS account
administrator if you are unsure.
1. Sign in to the [AWS Management Console](https://console.aws.amazon.com/).
2. Open the [Amazon S3 Console](https://console.aws.amazon.com/s3/home).
3. Browse to the existing bucket and open it.
4. Click the **Permissions** tab.
5. In the **Bucket policy** area, click **Edit**.
6. In the **Policy** text area, copy the following JSON-formatted policy.
To change the following policy to restrict it to a specific user in the AWS account, change `root` to that
specific username.
In this policy, replace the following:
* Replace `` with your AWS account ID.
* Replace `` in two places with the name of your bucket.
```json theme={null}
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "AllowAuthenticatedUsersInAccountReadWrite",
"Effect": "Allow",
"Principal": {
"AWS": "arn:aws:iam:::root"
},
"Action": [
"s3:GetObject",
"s3:PutObject",
"s3:ListBucket",
"s3:DeleteObject"
],
"Resource": [
"arn:aws:s3:::",
"arn:aws:s3:::/*"
],
"Condition": {
"StringEquals": {
"aws:PrincipalType": "IAMUser"
}
}
}
]
}
```
7. Click **Save changes**.
## Create a bucket with the AWS CLI
To use the AWS CLI to create an Amazon S3 bucket that allows all authenticated AWS IAM users in the
corresponding AWS account to read and write to the bucket, do the following.
Your organization might have stricter bucket policy requirements. Check with your AWS account
administrator if you are unsure.
1. [Install the AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html).
2. [Set up the AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-quickstart.html).
3. Copy the following script to a file on your local machine, for example a file named `create-s3-bucket.sh`.
To change the following bucket policy to restrict it to a specific user in the AWS account, change `root` to that
specific username.
In this script, replace the following:
* Replace `` with your AWS account ID.
* Replace `` with the name of your bucket.
* Replace `` with your AWS Region.
```bash theme={null}
#!/bin/bash
# Set variables for the AWS account ID, Amazon S3 bucket name, and AWS Region.
ACCOUNT_ID=""
BUCKET_NAME=""
REGION=""
# Temporary filename for the bucket policy.
# Do not change this variable.
POLICY_FILE="bucket_policy.json"
# Create the bucket.
aws s3api create-bucket --bucket $BUCKET_NAME --region $REGION
# Wait for the bucket to exist.
echo "Waiting for bucket '$BUCKET_NAME' to be fully created..."
aws s3api wait bucket-exists --bucket $BUCKET_NAME
# Check if the wait command was successful.
if [ $? -eq 0 ]; then
echo "The bucket '$BUCKET_NAME' has been fully created."
else
echo "Error: Timed out waiting for bucket '$BUCKET_NAME' to be created."
exit 1
fi
# Remove the "block public policy" bucket access setting.
aws s3api put-public-access-block \
--bucket $BUCKET_NAME \
--public-access-block-configuration \
'{"BlockPublicPolicy": false, "IgnorePublicAcls": false, "BlockPublicAcls": false, "RestrictPublicBuckets": false}'
# Check if the operation was successful.
if [ $? -eq 0 ]; then
echo "The block public policy access setting was removed from '$BUCKET_NAME'."
else
echo "Error: Failed to remove the block public policy access setting from '$BUCKET_NAME'."
exit 1
fi
# Create the bucket policy.
cat << EOF > $POLICY_FILE
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "AllowAuthenticatedUsersInAccountReadWrite",
"Effect": "Allow",
"Principal": {
"AWS": "arn:aws:iam::$ACCOUNT_ID:root"
},
"Action": [
"s3:GetObject",
"s3:PutObject",
"s3:ListBucket",
"s3:DeleteObject"
],
"Resource": [
"arn:aws:s3:::$BUCKET_NAME",
"arn:aws:s3:::$BUCKET_NAME/*"
],
"Condition": {
"StringEquals": {
"aws:PrincipalType": "IAMUser"
}
}
}
]
}
EOF
# Apply the bucket policy.
aws s3api put-bucket-policy --bucket $BUCKET_NAME --policy file://$POLICY_FILE
# Check if the policy application was successful.
if [ $? -eq 0 ]; then
echo "The bucket policy was applied to '$BUCKET_NAME'."
else
echo "Error: Failed to apply the bucket policy to '$BUCKET_NAME'."
exit 1
fi
# Verify the applied policy.
echo "Verifying the applied policy:"
aws s3api get-bucket-policy --bucket $BUCKET_NAME --query Policy --output text
# Remove the temporary bucket policy file.
rm $POLICY_FILE
```
4. Run the script, for example:
```bash theme={null}
sh create-s3-bucket.sh
```
5. After the bucket is created, you can delete the script file, if you want.
## Create a bucket with AWS CloudFormation
To use the AWS CloudFormation console to create an Amazon S3 bucket that allows all authenticated AWS IAM users
in the corresponding AWS account to read and write to the bucket, do the following.
Your organization might have stricter bucket policy requirements. Check with your AWS account
administrator if you are unsure.
1. Save the following YAML to a file on your local machine, for example `create-s3-bucket.yaml`. To change
the following bucket policy to restrict it to a specific user in the AWS account, change `root` to that
specific username.
```yaml theme={null}
AWSTemplateFormatVersion: '2010-09-09'
Description: 'CloudFormation template to create an S3 bucket with specific permissions for account users.'
Parameters:
BucketName:
Type: String
Description: 'Name of the S3 bucket to create'
Resources:
MyS3Bucket:
Type: 'AWS::S3::Bucket'
Properties:
BucketName: !Ref BucketName
PublicAccessBlockConfiguration:
BlockPublicAcls: true
BlockPublicPolicy: false
IgnorePublicAcls: true
RestrictPublicBuckets: true
BucketPolicy:
Type: 'AWS::S3::BucketPolicy'
Properties:
Bucket: !Ref MyS3Bucket
PolicyDocument:
Version: '2012-10-17'
Statement:
- Sid: AllowAllAuthenticatedUsersInAccount
Effect: Allow
Principal:
AWS: !Sub 'arn:aws:iam::${AWS::AccountId}:root'
Action:
- 's3:GetObject'
- 's3:PutObject'
- 's3:ListBucket'
- 's3:DeleteObject'
Resource:
- !Sub 'arn:aws:s3:::${BucketName}'
- !Sub 'arn:aws:s3:::${BucketName}/*'
Outputs:
BucketName:
Description: 'Name of the created S3 bucket'
Value: !Ref MyS3Bucket
```
2. Sign in to the [AWS Management Console](https://console.aws.amazon.com/).
3. Open the [AWS CloudFormation Console](https://console.aws.amazon.com/cloudformation/home).
4. Click **Create stack > With new resources (standard)**.
5. On the **Create stack** page, with **Choose an existing template** already selected, select **Upload a template file**.
6. Click **Choose file**, and browse to and select the YAML file from your local machine.
7. Click **Next**.
8. Enter a unique **Stack name** and **BucketName**.
9. Click **Next** two times.
10. Click **Submit**.
11. Wait until the **Status** changes to **CREATE\_COMPLETE**.
12. After the bucket is created, you can delete the YAML file, if you want.
* [Enable authenticated bucket access](https://docs.aws.amazon.com/AmazonS3/latest/userguide/walkthrough1.html).
* For authenticated bucket read access, the authenticated AWS IAM user must have at minimum the permissions of `s3:ListBucket` and `s3:GetObject` for that bucket. [Learn how](https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-policies-s3.html).
* For bucket write access, authenticated access to the bucket must be enabled (anonymous access must not be enabled), and the authenticated AWS IAM user must have at
minimum the permission of `s3:PutObject` for that bucket. [Learn how](https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-policies-s3.html).
* For authenticated access, an AWS access key and secret access key for the authenticated AWS IAM user in the account.
[Create an AWS access key and secret access key](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_access-keys.html#Using_CreateAccessKey).
* For authenticated access in untrusted environments or enhanced security scenarios, an AWS STS session token for temporary access, in addition to an AWS access key and secret access key. [Create a session token](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_request.html#api_getsessiontoken).
* If the target files are in the root of the bucket, the path to the bucket, formatted as `protocol://bucket/` (for example, `s3://my-bucket/`).
If the target files are in a folder, the path to the target folder in the S3 bucket, formatted as `protocol://bucket/path/to/folder/` (for example, `s3://my-bucket/my-folder/`).
* If the target files are in a folder, and authenticated bucket access is enabled, make sure the authenticated AWS IAM user has
authenticated access to the folder as well. [Enable authenticated folder access](https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-bucket-policies.html#example-bucket-policies-folders).
The S3 connector dependencies:
```bash CLI, Python theme={null}
pip install "unstructured-ingest[s3]"
```
You might also need to install additional dependencies, depending on your needs. [Learn more](/ingestion/ingest-dependencies).
The following environment variables:
* `AWS_S3_URL` - The path to the S3 bucket or folder, formatted as `s3://my-bucket/` (if the files are in the bucket's root) or `s3://my-bucket/my-folder/`.
* If the bucket does not have anonymous access enabled, provide the AWS credentials:
* `AWS_ACCESS_KEY_ID` - The AWS access key ID for the authenticated AWS IAM user, represented by `--key` (CLI) or `key` (Python).
* `AWS_SECRET_ACCESS_KEY` - The corresponding AWS secret access key, represented by `--secret` (CLI) or `secret` (Python).
* `AWS_TOKEN` - If required, the AWS STS session token for temporary access, represented by `--token` (CLI) or `token` (Python).
* If the bucket has anonymous access enabled for reading from the bucket, set `--anonymous` (CLI) or `anonymous=True` (Python) instead.
Now call the Unstructured Ingest CLI or the Unstructured Ingest Python library. The source connector can be any of the ones supported. This example uses the local source connector.
This example sends files to Unstructured for processing by default. To process files locally instead, see the instructions at the end of this page.