[Feature] Enhance OpenAI API, add example config for GPT evaluation (#53)

* [Feature] Enhance OpenAI API, add example config for GPT evaluation

* fix

configs/eval_gpt3.5.py

+from mmengine.config import read_base
+from opencompass.models import OpenAI
+from opencompass.partitioners import NaivePartitioner
+from opencompass.runners import LocalRunner
+from opencompass.tasks import OpenICLInferTask
+
+with read_base():
+    # choose a list of datasets
+    from .datasets.collections.chat_medium import datasets
+    # and output the results in a choosen format
+    from .summarizers.medium import summarizer
+
+
+api_meta_template = dict(
+    round=[
+            dict(role='HUMAN', api_role='HUMAN'),
+            dict(role='BOT', api_role='BOT', generate=True),
+    ],
+)
+
+models = [
+    dict(abbr='GPT-3.5-turbo-0613',
+        type=OpenAI, path='gpt-3.5-turbo-0613',
+        key='ENV',  # The key will be obtained from $OPENAI_API_KEY, but you can write down your key here as well
+        meta_template=api_meta_template,
+        query_per_second=1,
+        max_out_len=2048, max_seq_len=2048, batch_size=8),
+]
+
+infer = dict(
+    partitioner=dict(type=NaivePartitioner),
+    runner=dict(
+        type=LocalRunner,
+        max_num_workers=8,
+        task=dict(type=OpenICLInferTask)),
+)

opencompass/models/openai_api.py

+import json
 import os
 from concurrent.futures import ThreadPoolExecutor
+from threading import Lock
 from typing import Dict, List, Optional, Union
 
+import requests
+
 from opencompass.registry import MODELS
 from opencompass.utils.prompt import PromptList
 
@@ -22,39 +26,54 @@ class OpenAI(BaseAPIModel):
         query_per_second (int): The maximum queries allowed per second
             between two consecutive calls of the API. Defaults to 1.
         retry (int): Number of retires if the API call fails. Defaults to 2.
-        key (str): OpenAI key. In particular, when it is set to "ENV", the key
-            will be fetched from the environment variable $OPENAI_API_KEY, as
-            how openai defaults to be. Defaults to 'ENV'
+        key (str or List[str]): OpenAI key(s). In particular, when it
+            is set to "ENV", the key will be fetched from the environment
+            variable $OPENAI_API_KEY, as how openai defaults to be. If it's a
+            list, the keys will be used in round-robin manner. Defaults to
+            'ENV'.
+        org (str or List[str], optional): OpenAI organization(s). If not
+            specified, OpenAI uses the default organization bound to each API
+            key. If specified, the orgs will be posted with each request in
+            round-robin manner. Defaults to None.
         meta_template (Dict, optional): The model's meta prompt
             template if needed, in case the requirement of injecting or
             wrapping of any meta instructions.
         openai_api_base (str): The base url of OpenAI's API. Defaults to
-            'https://api.openai.com/v1'.
+            'https://api.openai.com/v1/chat/completions'.
     """
 
     is_api: bool = True
 
-    def __init__(self,
-                 path: str,
-                 max_seq_len: int = 2048,
-                 query_per_second: int = 1,
-                 retry: int = 2,
-                 key: str = 'ENV',
-                 meta_template: Optional[Dict] = None,
-                 openai_api_base: str = 'https://api.openai.com/v1'):
+    def __init__(
+        self,
+        path: str,
+        max_seq_len: int = 2048,
+        query_per_second: int = 1,
+        retry: int = 2,
+        key: Union[str, List[str]] = 'ENV',
+        org: Optional[Union[str, List[str]]] = None,
+        meta_template: Optional[Dict] = None,
+        openai_api_base: str = 'https://api.openai.com/v1/chat/completions'
+    ):  # noqa
         super().__init__(path=path,
                          max_seq_len=max_seq_len,
                          meta_template=meta_template,
                          query_per_second=query_per_second,
                          retry=retry)
-        import openai
         import tiktoken
-        self.openai = openai
         self.tiktoken = tiktoken
 
-        self.openai.api_key = os.getenv(
-            'OPENAI_API_KEY') if key == 'ENV' else key
-        self.openai.api_rase = openai_api_base
+        if isinstance(key, str):
+            self.keys = [os.getenv('OPENAI_API_KEY') if key == 'ENV' else key]
+        else:
+            self.keys = key
+        self.key_ctr = 0
+        if isinstance(org, str):
+            self.orgs = [org]
+        else:
+            self.orgs = org
+        self.org_ctr = 0
+        self.url = openai_api_base
 
     def generate(
         self,
@@ -103,9 +122,6 @@ class OpenAI(BaseAPIModel):
         """
         assert isinstance(input, (str, PromptList))
 
-        # max num token for gpt-3.5-turbo is 4097
-        max_out_len = min(max_out_len, 4000 - self.get_token_len(str(input)))
-
         if isinstance(input, str):
             messages = [{'role': 'user', 'content': input}]
         else:
@@ -120,11 +136,32 @@ class OpenAI(BaseAPIModel):
                     msg['role'] = 'system'
                 messages.append(msg)
 
+        # max num token for gpt-3.5-turbo is 4097
+        max_out_len = min(max_out_len, 4000 - self.get_token_len(str(input)))
+        if max_out_len <= 0:
+            return ''
+
         max_num_retries = 0
         while max_num_retries < self.retry:
             self.wait()
+            if hasattr(self, 'keys'):
+                with Lock():
+                    self.key_ctr += 1
+                    if self.key_ctr == len(self.keys):
+                        self.key_ctr = 0
+                header = {
+                    'Authorization': f'Bearer {self.keys[self.key_ctr]}',
+                    'content-type': 'application/json',
+                }
+            if self.orgs:
+                with Lock():
+                    self.org_ctr += 1
+                    if self.org_ctr == len(self.orgs):
+                        self.org_ctr = 0
+                header['OpenAI-Organization'] = self.orgs[self.org_ctr]
+
             try:
-                response = self.openai.ChatCompletion.create(
+                data = dict(
                     model=self.path,
                     messages=messages,
                     max_tokens=max_out_len,
@@ -132,12 +169,28 @@ class OpenAI(BaseAPIModel):
                     stop=None,
                     temperature=temperature,
                 )
-            except self.openai.error.RateLimitError:
-                max_num_retries -= 1
+                raw_response = requests.post(self.url,
+                                             headers=header,
+                                             data=json.dumps(data))
+            except requests.ConnectionError:
+                self.logger.error('Got connection error, retrying...')
+                continue
+            try:
+                response = raw_response.json()
+            except requests.JSONDecodeError:
+                self.logger.error('JsonDecode error, got',
+                                  str(raw_response.content))
+            try:
+                return response['choices'][0]['message']['content'].strip()
+            except KeyError:
+                if 'error' in response:
+                    self.logger.error('Find error message in response: ',
+                                      str(response['error']))
             max_num_retries += 1
 
-        result = response.choices[0].message.content.strip()
-        return result
+        raise RuntimeError('Calling OpenAI failed after retrying for '
+                           f'{max_num_retries} times. Check the logs for '
+                           'details.')
 
     def get_token_len(self, prompt: str) -> int:
         """Get lengths of the tokenized string. Only English and Chinese