update openai API call and fix output

README.md

@@ -37,11 +37,11 @@ pip install -e .
 Once you have installed all dependencies you are ready to go with:
 ```python
 from nl2ltl import translate
-from nl2ltl.engines.rasa.core import RasaEngine
+from nl2ltl.engines.gpt.core import GPTEngine, Models
 from nl2ltl.filters.simple_filters import BasicFilter
 from nl2ltl.engines.utils import pretty
 
-engine = RasaEngine()
+engine = GPTEngine()
 filter = BasicFilter()
 utterance = "Eventually send me a Slack after receiving a Gmail"
 
@@ -65,9 +65,10 @@ For instance, Rasa requires a `.tar.gz` format trained model in the
 - [x] [Rasa](https://rasa.com/) intents/entities classifier (to use Rasa, please install it with `pip install -e ".[rasa]"`)
 - [ ] [Watson Assistant](https://www.ibm.com/products/watson-assistant) intents/entities classifier -- Planned
 
-To use GPT models you need to have the OPEN_API_KEY set as environment variable. To set it:
+**NOTE**: To use OpenAI GPT models don't forget to add your `OPEN_API_KEY` in a `.env` file under your project folder. 
+The `.env` file should look like:
 ```bash
-export OPENAI_API_KEY=your_api_key
+OPENAI_API_KEY=your_api_key
 ```
 
 ## Write your own Engine

nl2ltl/engines/gpt/core.py

@@ -6,20 +6,19 @@
 
 """
 import json
-import os
 from enum import Enum
 from pathlib import Path
 from typing import Dict, Set
 
-import openai
+from openai import OpenAI
 from pylogics.syntax.base import Formula
 
 from nl2ltl.engines.base import Engine
 from nl2ltl.engines.gpt import ENGINE_ROOT
 from nl2ltl.engines.gpt.output import GPTOutput, parse_gpt_output, parse_gpt_result
 from nl2ltl.filters.base import Filter
 
-openai.api_key = os.getenv("OPENAI_API_KEY")
+client = OpenAI()
 engine_root = ENGINE_ROOT
 DATA_DIR = engine_root / "data"
 PROMPT_PATH = engine_root / DATA_DIR / "prompt.json"
@@ -75,7 +74,7 @@ def _check_consistency(self) -> None:
 
     def __check_openai_version(self):
         """Check that the GPT tool is at the right version."""
-        is_right_version = openai.__version__ == "1.12.0"
+        is_right_version = client._version == "1.12.0"
         if not is_right_version:
             raise Exception(
                 "OpenAI needs to be at version 1.12.0. "
@@ -149,7 +148,7 @@ def _process_utterance(
     query = f"NL: {utterance}\n"
     messages = [{"role": "user", "content": prompt + query}]
     if operation_mode == OperationModes.CHAT.value:
-        prediction = openai.chat.completions.create(
+        prediction = client.chat.completions.create(
             model=model,
             messages=messages,
             temperature=temperature,
@@ -160,7 +159,7 @@ def _process_utterance(
             stop=["\n\n"],
         )
     else:
-        prediction = openai.completions.create(
+        prediction = client.completions.create(
             model=model,
             prompt=messages[0]["content"],
             temperature=temperature,

nl2ltl/engines/gpt/output.py

@@ -40,15 +40,15 @@ def pattern(self) -> str:
                     Match,
                     re.search(
                         "PATTERN: (.*)\n",
-                        self.output["choices"][0]["message"]["content"],
+                        self.output.choices[0].message.content,
                     ),
                 ).group(1)
             )
         else:
             return str(
                 cast(
                     Match,
-                    re.search("PATTERN: (.*)\n", self.output["choices"][0]["text"]),
+                    re.search("PATTERN: (.*)\n", self.output.choices[0].text),
                 ).group(1)
             )
 
@@ -61,14 +61,14 @@ def entities(self) -> Tuple[str]:
             return tuple(
                 cast(
                     Match,
-                    re.search("SYMBOLS: (.*)", self.output["choices"][0]["message"]["content"]),
+                    re.search("SYMBOLS: (.*)", self.output.choices[0].message.content),
                 )
                 .group(1)
                 .split(", ")
             )
         else:
             return tuple(
-                cast(Match, re.search("SYMBOLS: (.*)", self.output["choices"][0]["text"])).group(1).split(", ")
+                cast(Match, re.search("SYMBOLS: (.*)", self.output.choices[0].text)).group(1).split(", ")
             )