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94 lines
2.8 KiB
Python
94 lines
2.8 KiB
Python
import os
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import json
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import pandas as pd
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import gradio as gr
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import logging
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel, Field
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from enum import Enum
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from typing import List, Optional, Tuple
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from slack_sdk import WebClient
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from slack_sdk.errors import SlackApiError
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from openai import OpenAI
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app = FastAPI()
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workforce_data_df = None
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with open("workforce_data.json") as file:
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workforce_data = json.load(file)
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workforce_data_df = pd.json_normalize(
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workforce_data,
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record_path=["regions"],
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meta=["data_snapshot_days_ago", "satisfaction"],
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)
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# Define the request model
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class WorkforceRequest(BaseModel):
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region: str
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staffing_type: str
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data_snapshot_days_ago: Optional[int] = None
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class SlackRequest(BaseModel):
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slack_message: str
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class WorkforceResponse(BaseModel):
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region: str
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staffing_type: str
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headcount: int
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satisfaction: float
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@app.post("/agent/slack_message")
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def send_slack_message(request: SlackRequest):
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"""
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Endpoint that sends slack message
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"""
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slack_message = request.slack_message
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# Load the bot token from an environment variable or replace it directly
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slack_token = os.getenv(
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"SLACK_BOT_TOKEN"
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) # Replace with your token if needed: 'xoxb-your-token'
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if slack_token is None:
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print(f"Message for slack: {slack_message}")
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else:
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client = WebClient(token=slack_token)
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channel = "hr_agent_demo"
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try:
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# Send the message
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response = client.chat_postMessage(channel=channel, text=slack_message)
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return f"Message sent to {channel}: {response['message']['text']}"
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except SlackApiError as e:
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print(f"Error sending message: {e.response['error']}")
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# Post method for device summary
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@app.post("/agent/workforce")
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def get_workforce(request: WorkforceRequest):
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"""
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Endpoint to workforce data by region, staffing type at a given point in time.
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"""
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region = request.region.lower()
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staffing_type = request.staffing_type.lower()
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data_snapshot_days_ago = (
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request.data_snapshot_days_ago
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if request.data_snapshot_days_ago
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else 0 # this param is not required.
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)
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response = {
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"region": region,
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"staffing_type": f"Staffing agency: {staffing_type}",
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"headcount": f"Headcount: {int(workforce_data_df[(workforce_data_df['region']==region) & (workforce_data_df['data_snapshot_days_ago']==data_snapshot_days_ago)][staffing_type].values[0])}",
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"satisfaction": f"Satisfaction: {float(workforce_data_df[(workforce_data_df['region']==region) & (workforce_data_df['data_snapshot_days_ago']==data_snapshot_days_ago)]['satisfaction'].values[0])}",
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}
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return response
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if __name__ == "__main__":
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app.run(debug=True)
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