From 4a5423fe2d85f7f2c2f9244a9adc42f754735cb7 Mon Sep 17 00:00:00 2001
From: pliny <133052465+elder-plinius@users.noreply.github.com>
Date: Sat, 18 Nov 2023 14:30:51 -0800
Subject: [PATCH] Delete swarms/models/autotemp.py
---
swarms/models/autotemp.py | 101 --------------------------------------
1 file changed, 101 deletions(-)
delete mode 100644 swarms/models/autotemp.py
diff --git a/swarms/models/autotemp.py b/swarms/models/autotemp.py
deleted file mode 100644
index c3abb894..00000000
--- a/swarms/models/autotemp.py
+++ /dev/null
@@ -1,101 +0,0 @@
-import re
-from concurrent.futures import ThreadPoolExecutor, as_completed
-from swarms.models.openai_models import OpenAIChat
-
-
-class AutoTempAgent:
- """
- AutoTemp is a tool for automatically selecting the best temperature setting for a given task.
-
- Flow:
- 1. Generate outputs at a range of temperature settings.
- 2. Evaluate each output using the default temperature setting.
- 3. Select the best output based on the evaluation score.
- 4. Return the best output.
-
-
- Args:
- temperature (float, optional): The default temperature setting to use. Defaults to 0.5.
- api_key (str, optional): Your OpenAI API key. Defaults to None.
- alt_temps ([type], optional): A list of alternative temperature settings to try. Defaults to None.
- auto_select (bool, optional): If True, the best temperature setting will be automatically selected. Defaults to True.
- max_workers (int, optional): The maximum number of workers to use when generating outputs. Defaults to 6.
-
- Returns:
- [type]: [description]
-
- Examples:
- >>> from swarms.demos.autotemp import AutoTemp
- >>> autotemp = AutoTemp()
- >>> autotemp.run("Generate a 10,000 word blog on mental clarity and the benefits of meditation.", "0.4,0.6,0.8,1.0,1.2,1.4")
- Best AutoTemp Output (Temp 0.4 | Score: 100.0):
- Generate a 10,000 word blog on mental clarity and the benefits of meditation.
-
- """
-
- def __init__(
- self,
- temperature: float = 0.5,
- api_key: str = None,
- alt_temps=None,
- auto_select=True,
- max_workers=6,
- ):
- self.alt_temps = alt_temps if alt_temps else [0.4, 0.6, 0.8, 1.0, 1.2, 1.4]
- self.auto_select = auto_select
- self.max_workers = max_workers
- self.temperature = temperature
- self.alt_temps = alt_temps
- self.llm = OpenAIChat(
- openai_api_key=api_key,
- temperature=temperature,
- )
-
- def evaluate_output(self, output: str):
- """Evaluate the output using the default temperature setting."""
- eval_prompt = f"""
- Evaluate the following output which was generated at a temperature setting of {self.temperature}.
- Provide a precise score from 0.0 to 100.0, considering the criteria of relevance, clarity, utility, pride, and delight.
-
- Output to evaluate:
- ---
- {output}
- ---
- """
- score_text = self.llm(prompt=eval_prompt)
- score_match = re.search(r"\b\d+(\.\d)?\b", score_text)
- return round(float(score_match.group()), 1) if score_match else 0.0
-
- def run(self, task: str, temperature_string):
- """Run the AutoTemp agent."""
- 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.llm.generate, task, temp): temp
- for temp in temperature_list
- }
- for future in as_completed(future_to_temp):
- temp = future_to_temp[future]
- output_text = future.result()
- outputs[temp] = output_text
- scores[temp] = self.evaluate_output(output_text, temp)
-
- if not scores:
- return "No valid outputs generated.", None
-
- sorted_scores = sorted(scores.items(), key=lambda item: item[1], reverse=True)
- best_temp, best_score = sorted_scores[0]
- best_output = outputs[best_temp]
-
- return (
- f"Best AutoTemp Output (Temp {best_temp} | Score: {best_score}):\n{best_output}"
- if self.auto_select
- else "\n".join(
- f"Temp {temp} | Score: {score}:\n{outputs[temp]}"
- for temp, score in sorted_scores
- )
- )