openai nits (#1139)

* fixed syntactic nits

* fix temperature and seed

* fix logprobs

* fixup merge

lm_eval/models/openai_completions.py

 import os
 import time
-from typing import List, Tuple
+from typing import List, Tuple, Optional
 
 import copy
 from collections import defaultdict
@@ -11,7 +11,7 @@ from lm_eval.api.model import LM
 from lm_eval.api.registry import register_model
 
 
-def get_result(response: dict, ctxlen: int) -> Tuple[float, bool]:
+def get_result(response, ctxlen: int) -> Tuple[float, bool]:
     """Process results from OpenAI API response.
 
     :param response: dict
@@ -25,12 +25,12 @@ def get_result(response: dict, ctxlen: int) -> Tuple[float, bool]:
             whether argmax matches given continuation exactly
     """
     is_greedy = True
-    logprobs = response["logprobs"]["token_logprobs"]
+    logprobs = response.logprobs.token_logprobs
     continuation_logprobs = sum(logprobs[ctxlen:])
 
-    for i in range(ctxlen, len(response["logprobs"]["tokens"])):
-        token = response["logprobs"]["tokens"][i]
-        top_tokens = response["logprobs"]["top_logprobs"][i]
+    for i in range(ctxlen, len(response.logprobs.token_logprobs)):
+        token = response.logprobs.token_logprobs[i]
+        top_tokens = response.logprobs.top_logprobs[i]
         top_token = max(top_tokens.keys(), key=lambda x: top_tokens[x])
         if top_token != token:
             is_greedy = False
@@ -67,12 +67,16 @@ please install these via `pip install lm-eval[openai]` or `pip install -e .[open
 @register_model("openai-completions")
 class OpenaiCompletionsLM(LM):
     REQ_CHUNK_SIZE = 20
+    _DEFAULT_MAX_LENGTH = 2048
 
     def __init__(
         self,
         model: str = "text-davinci-003",
         truncate: bool = False,
+        max_gen_toks: int = 256,
         batch_size: int = 1,
+        seed: int = 1234,
+        max_length: Optional[int] = None,
     ) -> None:
         """
 
@@ -82,6 +86,7 @@ class OpenaiCompletionsLM(LM):
             Truncate input if too long (if False and input is too long, throw error)
         """
         super().__init__()
+        self.seed = seed
         try:
             import openai, tiktoken  # noqa: E401
         except ModuleNotFoundError:
@@ -89,14 +94,16 @@ class OpenaiCompletionsLM(LM):
                 "attempted to use 'openai' LM type, but package `openai` or `tiktoken` are not installed. \
     please install these via `pip install lm-eval[openai]` or `pip install -e .[openai]`",
             )
-        self.model= model
+        self.model = model
         self.tokenizer = tiktoken.encoding_for_model(self.model)
         self.vocab_size = self.tokenizer.n_vocab
         self.truncate = truncate
         self.end_of_text_token_id = self.tokenizer.eot_token
+        self._max_gen_toks = max_gen_toks
+        self._max_length = max_length
 
         # Read from environment variable OPENAI_API_SECRET_KEY
-        openai.api_key = os.environ["OPENAI_API_SECRET_KEY"]
+        openai.api_key = os.environ["OPENAI_API_KEY"]
 
     @property
     def eot_token_id(self):
@@ -104,12 +111,14 @@ class OpenaiCompletionsLM(LM):
 
     @property
     def max_length(self) -> int:
-        # Note: the OpenAI API supports up to 2049 tokens, with the first token being the first input token
-        return 2048
+        if self._max_length:
+            return self._max_length
+        else:
+            return self._DEFAULT_MAX_LENGTH
 
     @property
     def max_gen_toks(self) -> int:
-        return 256
+        return self._max_gen_toks
 
     @property
     def batch_size(self):
@@ -187,12 +196,13 @@ class OpenaiCompletionsLM(LM):
                 ctxlens.append(ctxlen)
 
             response = oa_completion(
-                engine=self.engine,
+                model=self.model,
                 prompt=inps,
                 echo=True,
                 max_tokens=0,
                 temperature=0.0,
                 logprobs=10,
+                seed=self.seed,
             )
 
             for resp, ctxlen, (cache_key, context_enc, continuation_enc) in zip(
@@ -242,21 +252,22 @@ class OpenaiCompletionsLM(LM):
                 inp = context_enc[-(self.max_length - self.max_gen_toks) :]
                 inps.append(inp)
 
-            until = request_args.get("until", ["<|endoftext|>"])
+            until = request_args.pop("until", ["<|endoftext|>"])
+            request_args.pop("do_sample", None)
+            request_args["temperature"] = request_args.get("temperature", 0)
 
             response = oa_completion(
                 model=self.model,
                 prompt=inps,
                 max_tokens=self.max_gen_toks,
-                temperature=0.0,
-                logprobs=10,
                 stop=until,
+                seed=self.seed,
+                **request_args,
             )
-
             for resp, (context, args_) in zip(response.choices, chunk):
-                s = getattr(resp, 'text')
+                s = getattr(resp, "text")
 
-                until_ = args_.get("until", ["<|endoftext|>"])
+                until_ = until
 
                 for term in until_:
                     if len(term) > 0: