Update variables.py

variables.py

@@ -1,3 +1,5 @@
+import json
+import os
 
 metaprompt_explanations = {
     "star": "Use ECHO when you need a comprehensive, multi-stage approach for complex prompts. It's ideal for tasks requiring in-depth analysis, exploration of multiple alternatives, and synthesis of ideas. Choose this over others when you have time for a thorough refinement process and need to consider various aspects of the prompt.",
@@ -9,6 +11,16 @@ metaprompt_explanations = {
     "bolism": "Utilize this method when working with autoregressive language models and when the task requires careful reasoning before conclusions. It's best for prompts that need detailed output formatting. Choose this over others when the prompt's structure and reasoning order are crucial."
 }
 
+# Load JSON data from environment variable
+PROMPT_DATA = json.loads(os.getenv('PROMPT_TEMPLATES', '[]'))
+
+# Create metaprompt_explanations dictionary from JSON data
+metaprompt_explanations = {
+    prompt["name"].lower().split()[0]: prompt["description"] 
+    for prompt in PROMPT_DATA
+}
+
+
 models =         [
         # Meta-Llama models (all support system)
         "meta-llama/Meta-Llama-3-70B-Instruct",
@@ -32,15 +44,27 @@ models =         [
     ]
 
 explanation_markdown = "".join([f"- **{key}**: {value}\n" for key, value in metaprompt_explanations.items()])
+# Generate explanation markdown from JSON data
+explanation_markdown = "".join([
+    f"- **{prompt['name'].lower().split()[0]}**: {prompt['description']}\n" 
+    for prompt in PROMPT_DATA
+])
 
 
-import os
 
 meta_info=""
 api_token = os.getenv('HF_API_TOKEN')
 if not api_token:
     raise ValueError("HF_API_TOKEN not found in environment variables")
 
+
+# Store templates in a dictionary
+meta_prompts = {
+    prompt["name"].lower().split()[0]: prompt["template"]
+    for prompt in PROMPT_DATA
+}
+
+
 metadone = os.getenv('metadone')
 prompt_refiner_model = os.getenv('prompt_refiner_model')
 echo_prompt_refiner = os.getenv('echo_prompt_refiner')