Update autotemp.py

autotemp.py

@@ -21,7 +21,7 @@ class AutoTemp:
         self.max_workers = max_workers
         self.model_version = model_version
 
-    def generate_with_openai(self, prompt, temperature, retries=3):
+    def generate_with_openai(self, prompt, temperature, top_p, retries=3):
         while retries > 0:
             try:
                 response = openai.ChatCompletion.create(
@@ -30,14 +30,15 @@ class AutoTemp:
                         {"role": "system", "content": "You are a helpful assistant."},
                         {"role": "user", "content": prompt}
                     ],
-                    temperature=temperature
+                    temperature=temperature,
+                    top_p=top_p
                 )
                 message = response['choices'][0]['message']['content']
                 return message.strip()
             except Exception as e:
                 retries -= 1
                 if retries <= 0:
-                    return f"Error generating text at temperature {temperature}: {e}"
+                    return f"Error generating text at temperature {temperature} and top-p {top_p}: {e}"
 
     def evaluate_output(self, output, temperature):
         eval_prompt = f"""
@@ -56,21 +57,20 @@ class AutoTemp:
             {output}
             ---
             """
-        score_text = self.generate_with_openai(eval_prompt, 0.5)  # Use a neutral temperature for evaluation to get consistent results
+        score_text = self.generate_with_openai(eval_prompt, 0.5, top_p)  # Use a neutral temperature for evaluation
         score_match = re.search(r'\b\d+(\.\d)?\b', score_text)
         if score_match:
             return round(float(score_match.group()), 1)  # Round the score to one decimal place
         else:
             return 0.0  # Unable to parse score, default to 0.0
 
-    def run(self, prompt, temperature_list=None):
-        if temperature_list is not None:
-            self.alt_temps = temperature_list
+    def run(self, prompt, temperature_string, top_p):
+        temperature_list = [float(temp.strip()) for temp in temperature_string.split(',')]
         outputs = {}
         scores = {}
         with ThreadPoolExecutor(max_workers=self.max_workers) as executor:
             future_to_temp = {
-                executor.submit(self.generate_with_openai, prompt, temp): temp for temp in self.alt_temps
+                executor.submit(self.generate_with_openai, prompt, temp, top_p): temp for temp in temperature_list
             }
             for future in as_completed(future_to_temp):
                 temp = future_to_temp[future]
@@ -89,33 +89,43 @@ class AutoTemp:
         # If auto_select is enabled, return only the best result
         if self.auto_select:
             best_temp, best_output, best_score = sorted_outputs[0]
-            return f"Best AutoTemp Output (Temp {best_temp} | Score: {best_score}):\n{best_output}"
+            return f"Best AutoTemp Output (Temp {best_temp} | Top-p {top_p} | Score: {best_score}):\n{best_output}"
         else:
-            return "\n".join(f"Temp {temp} | Score: {score}:\n{text}" for temp, text, score in sorted_outputs)
+            return "\n".join(f"Temp {temp} | Top-p {top_p} | Score: {score}:\n{text}" for temp, text, score in sorted_outputs)
 
 # Gradio app logic
-def run_autotemp(prompt, temperature_string, auto_select):
-    temperature_list = [float(temp.strip()) for temp in temperature_string.split(',')]
+def run_autotemp(prompt, temperature_string, top_p, auto_select):
     agent = AutoTemp(auto_select=auto_select)
-    output = agent.run(prompt, temperature_list=temperature_list)
+    output = agent.run(prompt, temperature_string, top_p=float(top_p))
     return output
 
 # Gradio interface setup
 def main():
     iface = gr.Interface(
         fn=run_autotemp,
-        inputs=["text", "text", "checkbox"],
+        inputs=[
+            "text",
+            "text",
+            gr.Slider(minimum=0.0, maximum=1.0, step=0.1, default=1.0, label="Top-p value"),
+            "checkbox"
+        ],
         outputs="text",
-        title="AutoTemp: Improved LLM Completions through Temperature Tuning",
-        description="Enter different temperatures separated by commas (e.g., 0.4, 0.6, 0.8, 1.0, 1.2). Toggle 'Auto Select' to either see just the best output or all evaluated outputs.",
+        title="AutoTemp: Enhanced LLM Responses with Temperature and Top-p Tuning",
+        description="""AutoTemp generates responses at different temperatures, evaluates them, and ranks them based on quality. 
+                       Enter temperatures separated by commas for evaluation.
+                       Adjust 'Top-p' to control output diversity: lower for precision, higher for creativity.
+                       Toggle 'Auto Select' to either see the top-rated output or all evaluated outputs.""",
+        article="""**What's Top-p?** 'Top-p' controls the diversity of AI responses: a low 'top-p' makes output more focused and predictable, 
+                   while a high 'top-p' encourages variety and surprise. Pair with temperature to fine-tune AI creativity: 
+                   higher temperatures with high 'top-p' for bold ideas, or lower temperatures with low 'top-p' for precise answers.""",
         examples=[
-            ["Write a short story about AGI learning to love", "0.5, 0.7, 0.9, 1.1", False],
-            ["Create a dialogue between a chef and an alien creating an innovative new recipe", "0.3, 0.6, 0.9, 1.2", True],
-            ["Explain quantum computing to a 5-year-old", "0.4, 0.8, 1.2, 1.5", False],
-            ["Draft an email to a hotel asking for a special arrangement for a marriage proposal", "0.4, 0.7, 1.0, 1.3", True],
-            ["Describe a futuristic city powered by renewable energy", "0.5, 0.75, 1.0, 1.25", False],
-            ["Generate a poem about the ocean's depths in the style of Edgar Allan Poe", "0.6, 0.8, 1.0, 1.2", True],
-            ["What are some innovative startup ideas for improving urban transportation?", "0.45, 0.65, 0.85, 1.05", False]
+            ["Write a short story about AGI learning to love", "0.5, 0.7, 0.9, 1.1", 1.0, False],
+            ["Create a dialogue between a chef and an alien creating an innovative new recipe", "0.3, 0.6, 0.9, 1.2", 0.9, True],
+            ["Explain quantum computing to a 5-year-old", "0.4, 0.8, 1.2, 1.5", 0.8, False],
+            ["Draft an email to a hotel asking for a special arrangement for a marriage proposal", "0.4, 0.7, 1.0, 1.3", 0.7, True],
+            ["Describe a futuristic city powered by renewable energy", "0.5, 0.75, 1.0, 1.25", 0.6, False],
+            ["Generate a poem about the ocean's depths in the style of Edgar Allan Poe", "0.6, 0.8, 1.0, 1.2", 0.5, True],
+            ["What are some innovative startup ideas for improving urban transportation?", "0.45, 0.65, 0.85, 1.05", 0.4, False]
         ]
     )
     iface.launch()