Finalize automation of query testing

.github/workflows/send_performance_demo.yml

@@ -0,0 +1,39 @@
+name: Run Performance Test
+# NB This only works on the default (prod) branch 
+on:
+  workflow_dispatch:
+  # schedule:
+  #   - cron: '0 9 1-7 * 5'
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    environment: 
+      name: production
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+
+      - name: Configure SSH
+        run: |
+          mkdir -p ~/.ssh/
+          echo "$PROD_SSH_KEY" > ~/.ssh/hubgpt_prod.key
+          chmod 600 ~/.ssh/hubgpt_prod.key
+          cat >>~/.ssh/config <<END
+          Host prod
+            HostName $PROD_EC2_HOST_IP
+            User $PROD_EC2_USER
+            IdentityFile ~/.ssh/hubgpt_prod.key
+            StrictHostKeyChecking no
+          END
+        env:
+          PROD_EC2_USER: ${{ secrets.PROD_EC2_USER }}
+          PROD_SSH_KEY: ${{ secrets.PROD_SSH_KEY }}
+          PROD_EC2_HOST_IP: ${{ secrets.PROD_EC2_HOST_IP }}
+
+      - name: Trigger metric dispatch
+        run: |
+          ssh prod << 'EOF'
+          cd danswer
+          make send-slack-metrics
+          EOF

.gitignore

@@ -9,3 +9,4 @@ secrets.yaml
 deployment/data/nginx/app.conf
 /deployment/data/nginx/app.conf
 .vscode/launch.json
+*.csv

backend/scripts/hubgpt_eval_automation.py

@@ -3,17 +3,31 @@
 import datetime
 import json
 import os
+<<<<<<< Updated upstream
 
 import pandas as pd
 import requests
+=======
+import pandas as pd
+import requests
+
+>>>>>>> Stashed changes
 from slack_sdk import WebClient
 
 
 def create_new_chat_session(danswer_url: str, api_key: str | None) -> int:
     headers = {"Authorization": f"Bearer {api_key}"} if api_key else None
     session_endpoint = danswer_url + "/api/chat/create-chat-session"
 
+<<<<<<< Updated upstream
     response = requests.post(session_endpoint, headers=headers, json={"persona_id": 0})
+=======
+    response = requests.post(
+        session_endpoint,
+        headers=headers,
+        json={"persona_id": 0}
+        )
+>>>>>>> Stashed changes
     response.raise_for_status()
 
     new_session_id = response.json()["chat_session_id"]
@@ -57,8 +71,12 @@ def process_question(danswer_url: str, question: str, api_key: str | None) -> No
             if new_token:
                 response_str += new_token
         return response_str
+<<<<<<< Updated upstream
 
 
+=======
+
+>>>>>>> Stashed changes
 def upload_to_slack(filename, channel_id):
     slack_client = WebClient(token=os.environ.get("SLACK_BOT_TOKEN"))
     size = os.stat(filename).st_size
@@ -68,6 +86,7 @@ def upload_to_slack(filename, channel_id):
     post_response = requests.post(url=upload_url, data=open(filename, "rb"))
     if post_response.status_code == 200:
         upload_response = slack_client.files_completeUploadExternal(
+<<<<<<< Updated upstream
             files=[{"id": file_id, "title": "Monthly Performance Evaluation"}],
             channel_id=channel_id,
         )
@@ -94,6 +113,35 @@ def upload_to_slack(filename, channel_id):
 
     # Record + send info
     data.to_csv("hubgpt_eval_automated.csv", index=False)
+=======
+            files=[{"id": file_id, "title": "Monthly Performance Evaluation"}], channel_id=channel_id
+        )
+    return upload_response.status_code
+
+if __name__ == "__main__":
+
+    data = pd.read_csv("hubgpt_eval_automated.csv")
+
+    queries_list = data.Query.tolist()
+
+    responses = []
+
+    for num, query in enumerate(queries_list):
+        print(f"Query {num+1}/{len(queries_list)}: {query}")
+        # response = process_question(danswer_url="https://hubgpt-staging.idinsight.io", 
+                        #  question=query, 
+                        #  api_key=None)
+        response = 1
+        print(response)
+        responses.append(response)
+        print("\n ------------------- \n")
+
+    today_str = str(datetime.date.today())
+    data[today_str] = responses
+
+    # Record + send info
+    data.to_csv("hubgpt_eval_automated.csv", index = False)
+>>>>>>> Stashed changes
     print("Complete")
     CHANNEL_ID = os.environ.get("METRICS_CHANNEL_ID")
     upload_to_slack("hubgpt_eval_automated.csv", CHANNEL_ID)