### Python Example: Process File Event and Notify Service
Source: https://developers.hrflow.ai/docs/workflows
Illustrates a complete Python workflow implementation. This example sets up an `Hrflow` client using credentials from `settings`, retrieves a file from a URL provided in `_request`, adds it to the HrFlow profile database, notifies another internal service, and constructs a custom HTTP 201 JSON response.
```Python
import json
import requests
from hrflow import Hrflow
def workflow(_request, settings):
client = Hrflow(api_secret=settings["API_KEY"], api_user=settings["USER_EMAIL"])
file_url = _request["file_url"]
file_content = requests.get(file_url, allow_redirects=True).content
client.profile.parsing.add_file(
source_key=settings["SOURCE_KEY"],
profile_file=file_content,
profile_content_type="application/pdf",
reference="profile_reference"
)
id = requests.post(settings["OTHER_SERVICE_URL"], data={"key": "value"}).json()["id"]
return dict(
status_code=201,
headers={"Content-Type": "application/json"},
body=json.dumps({"id": id})
)
```
--------------------------------
### HRFlow.ai Job Asking API: Parameter and Usage Guide
Source: https://developers.hrflow.ai/docs/jobs-asking
This snippet provides a detailed guide for using the HRFlow.ai Job Asking API, focusing on the 'questions' parameter, its expected format, and examples. It also outlines the response structure and offers best practices for question formulation, including tips for clarity, handling closed-ended questions, setting default values, and requesting specific output formats.
```APIDOC
Endpoint: Ask a question to Job in a Board
Parameters:
questions:
Type: List[str]
Description: MANDATORY. A list of questions you wish to pose to the job.
Examples:
- Single question: ["What is the start date for this job? (DD-MM-YYYY)"]
- Multi questions: ["Summarize the job", "Is there a start date for this position?"]
Response Structure:
data:
Type: List[str]
Description: A list of answers, corresponding to the order of questions asked.
Best Practices & Capabilities:
- Formulate clear and precise inquiries.
- Model has the capability to comprehensively analyze all fields within a Job.
- Model is trained to respond in the active voice; however, responses may be inconsistent or incorrect, so validation is advisable.
- For closed-ended questions expecting a binary response (yes/no), specify choices within the question (e.g., "Is there a start date for this position? (yes/no)").
- For some specific closed-ended questions, consider using the Tagging API (e.g., "What is the typical work space in the company (fast, moderate, flexible)?").
- Set default values if the answer may not be found within the job (e.g., "Exact address of the job (default: n/a)"). If unsure and no default is specified, the model may respond with "N/A" or "null."
- To receive responses in a specific format (e.g., JSON list), structure your question accordingly (e.g., "Among the following options, which best matches the job (returns a JSON list): Full-time, Permanent, Temporary, Part-time, Fixed-term contract, Internship, Apprenticeship, Freelance, Civic service"). A valid response can be expressed as a string like `["Full-time", "Permanent"]`.
- Model is multilingual and will respond in the same language in which the question was posed.
```
--------------------------------
### Python Example for Profile Asking API
Source: https://developers.hrflow.ai/docs/profiles-asking
This Python example demonstrates how to use the HRFlow.ai Profile Asking API to submit questions about a candidate's profile. It uses the `requests` module to send a GET request with specified source, profile keys, and a list of questions. Remember to replace placeholder values for `source_key`, `key`, `X-USER-EMAIL`, and `X-API-KEY`.
```Python
import requests
import json
url = "https://api.hrflow.ai/v1/profile/asking"
questions = [
"What is the position of the candidate who is not in an internship and for whom this is their first job?",
"Are the skills listed in this profile consistent?"
]
payload = {
"source_key": "FILL_WITH_SOURCE_KEY",
"key": "FILL_WITH_PROFILE_KEY",
"questions": json.dumps(questions)
}
headers = {
'X-USER-EMAIL': 'FILL THIS',
'X-API-KEY': 'FILL THIS',
'Content-Type': 'application/json'
}
response = requests.request("GET", url, headers=headers, data=payload)
print(response.json())
```
--------------------------------
### Python Example: Asking Job Data via HRFlow.ai API
Source: https://developers.hrflow.ai/docs/jobs-asking
This Python snippet demonstrates how to query the HRFlow.ai Job Asking API. It uses the 'requests' library to send a GET request with a 'board_key', 'job_key', and a JSON-encoded list of questions to retrieve specific job details.
```Python
import requests
import json
url = "https://api.hrflow.ai/v1/job/asking"
questions = [
"What is the start date for this job? (DD-MM-YYYY)",
"Is language training offered to employees?"
]
payload = {
"board_key": "FILL_WITH_BOARD_KEY",
"key": "FILL_WITH_JOB_KEY",
"questions": json.dumps(questions)
}
headers = {
'X-USER-EMAIL': 'FILL THIS',
'X-API-KEY': 'FILL THIS',
'Content-Type': 'application/json'
}
response = requests.request("GET", url, headers=headers, data=payload)
print(response.json())
```
--------------------------------
### Curl Example: Test Catch Workflow with POST Request
Source: https://developers.hrflow.ai/docs/workflows
Demonstrates how to test a deployed Catch workflow URL using a `curl` command. It sends a POST request with `application/json` content type and a sample JSON body containing a `file_url` to trigger the workflow execution.
```Curl
curl -X POST https://api-workflows.hrflow.ai/teams/XXX/YYY/python3.6/ZZZ \
-H Content-Type:application/json \
-d '{"file_url": "https://company.storage.fr/file/profile_1.doc"}'
```
--------------------------------
### Display HrFlow.ai Profile Search Results on a Web Page
Source: https://developers.hrflow.ai/docs/searching-api
This comprehensive example demonstrates how to fetch and display HrFlow.ai profile search results on a web page. It includes the foundational HTML structure, detailed CSS for styling the profile cards and layout, and JavaScript logic to interact with the HrFlow.ai API, build search queries, and dynamically render the fetched profiles. It uses Axios for API calls and assumes a basic understanding of web development.
```HTML