Complete Migration

README.md

@@ -1,4 +1,4 @@
-# DSPy Tweet Optimizer
+# DSPy Tweet Optimizer - Modaic Agent
 
 ![Twitter X Logo](https://img.freepik.com/free-vector/twitter-new-2023-x-logo-white-background-vector_1017-45422.jpg?semt=ais_hybrid&w=740&q=80)
 

agent/__init__.py

@@ -0,0 +1,3 @@
+from .index import TweetOptimizerAgent, TweetOptimizerConfig
+
+__all__ = ["TweetOptimizerAgent", "TweetOptimizerConfig"]

agent/hill_climbing.py

@@ -32,7 +32,7 @@ class HillClimbingOptimizer:
         Yields:
             Tuple of (current_tweet, evaluation_result, is_improvement, patience_counter, generator_inputs, evaluator_inputs)
         """
-        # Generate initial tweet
+        # generate initial tweet
         generator_inputs = {
             "input_text": initial_text,
             "current_tweet": "",
@@ -67,10 +67,10 @@ class HillClimbingOptimizer:
             evaluator_inputs,
         )
 
-        for iteration in range(1, self.max_iterations):
-            # Generate improved tweet with previous evaluation as feedback
+        for _ in range(1, self.max_iterations):
+            # generate improved tweet with previous evaluation as feedback
             try:
-                # Format evaluation for display in generator inputs
+                # format evaluation for display in generator inputs
                 eval_text = format_evaluation_for_generator(best_score)
 
                 generator_inputs = {
@@ -85,7 +85,7 @@ class HillClimbingOptimizer:
                     previous_evaluation=best_score,
                 )
 
-                # Evaluate candidate
+                # evaluate candidate
                 evaluator_inputs = {
                     "original_text": initial_text,
                     "current_best_tweet": best_tweet,
@@ -98,7 +98,7 @@ class HillClimbingOptimizer:
                     current_best_tweet=best_tweet,
                 )
 
-                # Check if candidate is better (hill climbing condition)
+                # check if candidate is better (hill climbing condition)
                 is_improvement = candidate_score > best_score
 
                 if is_improvement:
@@ -124,12 +124,12 @@ class HillClimbingOptimizer:
                         evaluator_inputs,
                     )
 
-                # Early stopping if no improvement for 'patience' iterations
+                # early stopping if no improvement for 'patience' iterations
                 if patience_counter >= self.patience:
                     break
 
             except Exception as e:
-                # If generation fails, yield current best
+                # if generation fails, yield current best
                 patience_counter += 1
                 evaluator_inputs = {
                     "original_text": initial_text,

main.py

@@ -1,4 +1,4 @@
-from agent.index import TweetOptimizerAgent, TweetOptimizerConfig
+from agent import TweetOptimizerAgent, TweetOptimizerConfig
 
 
 def main():