HR agent demo (#206)

* commiting my hr_agent branch

* updating the HR agent config

* pushing to remote

* fix hr agent

* committing to merge with main

* updating to merge from main

* updating the demo and model-server-tests to pull from poetry

* updating the poetry.lock files

* updating based on feedback

* updated sysmte prompt for hr_agent

---------

Co-authored-by: Salman Paracha <salmanparacha@MacBook-Pro-261.local>
Co-authored-by: Adil Hafeez <adil@katanemo.com>

demos/hr_agent/main.py

@@ -0,0 +1,106 @@
+import os
+import json
+import pandas as pd
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel, Field
+from typing import Optional
+from enum import Enum
+from slack_sdk import WebClient
+from slack_sdk.errors import SlackApiError
+
+app = FastAPI()
+workforce_data_df = None
+
+with open("workforce_data.json") as file:
+    workforce_data = json.load(file)
+    workforce_data_df = pd.json_normalize(
+        workforce_data, record_path=["regions"], meta=["point_in_time", "satisfaction"]
+    )
+
+
+# Define the request model
+class WorkforceRequset(BaseModel):
+    region: str
+    staffing_type: str
+    point_in_time: Optional[int] = None
+
+
+class SlackRequest(BaseModel):
+    slack_message: str
+
+
+class WorkforceResponse(BaseModel):
+    region: str
+    staffing_type: str
+    headcount: int
+    satisfaction: float
+
+
+# Post method for device summary
+@app.post("/agent/workforce")
+def get_workforce(request: WorkforceRequset):
+    """
+    Endpoint to workforce data by region, staffing type at a given point in time.
+    """
+    region = request.region.lower()
+    staffing_type = request.staffing_type.lower()
+    point_in_time = request.point_in_time if request.point_in_time else 0
+
+    response = {
+        "region": region,
+        "staffing_type": f"Staffing agency: {staffing_type}",
+        "headcount": f"Headcount: {int(workforce_data_df[(workforce_data_df['region']==region) & (workforce_data_df['point_in_time']==point_in_time)][staffing_type].values[0])}",
+        "satisfaction": f"Satisifaction: {float(workforce_data_df[(workforce_data_df['region']==region) & (workforce_data_df['point_in_time']==point_in_time)]['satisfaction'].values[0])}",
+    }
+    return response
+
+
+@app.post("/agent/slack_message")
+def send_slack_message(request: SlackRequest):
+    """
+    Endpoint that sends slack message
+    """
+    slack_message = request.slack_message
+
+    # Load the bot token from an environment variable or replace it directly
+    slack_token = os.getenv(
+        "SLACK_BOT_TOKEN"
+    )  # Replace with your token if needed: 'xoxb-your-token'
+
+    if slack_token is None:
+        print(f"Message for slack: {slack_message}")
+    else:
+        client = WebClient(token=slack_token)
+        channel = "hr_agent_demo"
+        try:
+            # Send the message
+            response = client.chat_postMessage(channel=channel, text=slack_message)
+            return f"Message sent to {channel}: {response['message']['text']}"
+        except SlackApiError as e:
+            print(f"Error sending message: {e.response['error']}")
+
+
+@app.post("/agent/hr_qa")
+async def general_hr_qa():
+    """
+    This method handles Q/A related to general issues in HR.
+    It forwards the conversation to the OpenAI client via a local proxy and returns the response.
+    """
+    return {
+        "choices": [
+            {
+                "message": {
+                    "role": "assistant",
+                    "content": "I am a helpful HR agent, and I can help you plan for workforce related questions",
+                },
+                "finish_reason": "completed",
+                "index": 0,
+            }
+        ],
+        "model": "hr_agent",
+        "usage": {"completion_tokens": 0},
+    }
+
+
+if __name__ == "__main__":
+    app.run(debug=True)