| Name | unstract-client JSON |
| Version |
1.1.0
JSON |
| download |
| home_page | None |
| Summary | Python client for the Unstract LLM-powered structured data extraction platform |
| upload_time | 2024-11-11 12:20:18 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.11 |
| license | MIT |
| keywords |
unstract
cli
apps
sdk
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# unstract-python-client
[](https://pypi.org/project/unstract-client/)
[
](https://pypi.org/project/unstract-client/)
[](https://pypi.org/project/unstract-client/)
Python client for the Unstract LLM-powered structured data extraction platform
## Installation
You can install the Unstract Python Client using pip:
```bash
pip install unstract-client
```
## Usage
First, import the `APIDeploymentsClient` from the `client` module:
```python
from unstract.api_deployments.client import APIDeploymentsClient
```
Then, create an instance of the `APIDeploymentsClient`:
```python
client = APIDeploymentsClient(api_url="url", api_key="your_api_key")
```
Now, you can use the client to interact with the Unstract API deployments API:
```python
try:
adc = APIDeploymentsClient(
api_url=os.getenv("UNSTRACT_API_URL"),
api_key=os.getenv("UNSTRACT_API_DEPLOYMENT_KEY"),
api_timeout=10,
logging_level="DEBUG",
include_metadata=False # optional
)
# Replace files with pdfs
response = adc.structure_file(
["<files>"]
)
print(response)
if response["pending"]:
while True:
p_response = adc.check_execution_status(
response["status_check_api_endpoint"]
)
print(p_response)
if not p_response["pending"]:
break
print("Sleeping and checking again in 5 seconds..")
time.sleep(5)
except APIDeploymentsClientException as e:
print(e)
```
## Parameter Details
`api_timeout`: Set a timeout for API requests, e.g., `api_timeout=10`.
`logging_level`: Set logging verbosity (e.g., "`DEBUG`").
`include_metadata`: If set to `True`, the response will include additional metadata (cost, tokens consumed and context) for each call made by the Prompt Studio exported tool.
## Questions and Feedback
On Slack, [join great conversations](https://join-slack.unstract.com/) around LLMs, their ecosystem and leveraging them to automate the previously unautomatable!
[Unstract Cloud](https://unstract.com/): Signup and Try!
[Unstract developer documentation](https://docs.unstract.com/): Learn more about Unstract and its API.
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