Rename LLM_Evaluation.py to helpers.py

helpers.py

@@ -0,0 +1,34 @@
+import requests
+import os
+from groq import Groq
+#from dotenv import load_dotenv
+#load_dotenv()
+GROQ_API_KEY = "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"
+client = Groq(api_key="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",)
+#client = Groq(
+#    api_key=os.environ.get('GROQ_API_KEY'),
+#)
+
+
+def fetch_models():
+    exclude_models = ['distil-whisper-large-v3-en', 'whisper-large-v3','whisper-large-v3-turbo', "llama3-groq-8b-8192-tool-use-preview", "llama3-groq-70b-8192-tool-use-preview"]
+    url = "https://api.groq.com/openai/v1/models"
+    api_key = GROQ_API_KEY#os.environ.get('GROQ_API_KEY')
+    headers = {
+        "Authorization": f"Bearer {api_key}",
+        "Content-Type": "application/json"
+    }
+    response = requests.get(url, headers=headers).json()['data']
+    if len(response) != 0:
+         return [model['id'] for model in response if model['id'] not in exclude_models]
+    else:
+        print("Error in fetching models!")
+        return []
+    
+print("selected_model", "<===>","prompt")
+def generate_content(selected_model, prompt):
+    chat_completion = client.chat.completions.create(
+                        messages=[{"role": "user", "content":prompt }],
+                        model=selected_model,
+                        )
+    return chat_completion.choices[0].message.content