Create app.py

app.py

@@ -0,0 +1,75 @@
+import os
+import time
+import openai
+from dotenv import load_dotenv
+import requests
+import schedule
+from rich import print
+
+load_dotenv()
+
+# Load environment variables
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+OPENAI_BASE_URL = os.getenv("OPENAI_BASE_URL", "https://api.helpingai.co/v1")
+
+if not OPENAI_API_KEY:
+    raise ValueError("OPENAI_API_KEY must be set in .env file")
+
+
+# Initialize OpenAI client
+client = openai.OpenAI(
+    api_key=OPENAI_API_KEY,
+    base_url=OPENAI_BASE_URL
+)
+
+
+# Hardcoded list of models
+MODELS = [
+    "HelpingAI2.5-10B",
+    "HelpingAI2.5-2B",
+    "HelpingAI2.5-5B",
+    "HelpingAI-flash",
+    "HelpingAI2-9B",
+    "HelpingAI2-6B",
+    "HelpingAI-15B",
+    "HELVETE",
+    "HELVETE-X",
+    "Priya-3B",
+    "HelpingAI2.5-10B-1M",
+    "Cipher-20B",
+    "HelpingAI2-3B"
+]
+
+
+# Function to make a request to a model with retry mechanism
+def make_request(model_name):
+    max_retries = 3
+    retry_delay = 10  # seconds
+    for attempt in range(max_retries):
+        try:
+            print(f"Requesting model: {model_name}")
+            response = client.chat.completions.create(
+                model=model_name,
+                messages=[{"role": "user", "content": "Hello, how are you?"}]
+            )
+            print(f"Response from {model_name}: {response.choices[0].message.content}\n")
+            break # Break if successful
+        except Exception as e:
+            print(f"Error with model {model_name}: {e}")
+            if attempt < max_retries - 1:
+                print(f"Retrying in {retry_delay} seconds...")
+                time.sleep(retry_delay)
+            else:
+                print("Max retries reached. Could not get a response.")
+
+
+def job():
+    for model in MODELS:
+        make_request(model)
+
+
+if __name__ == "__main__":
+    schedule.every(5).minutes.do(job)
+    while True:
+        schedule.run_pending()
+        time.sleep(1)