Merge pull request #262 from HMB-research/GPT-4-turbo

Adds GPT-4 Turbo preview model

camel/model_backend.py

@@ -63,23 +63,27 @@ class OpenAIModel(ModelBackend):
             "gpt-4": 8192,
             "gpt-4-0613": 8192,
             "gpt-4-32k": 32768,
+            "gpt-4-1106-preview": 4096,
         }
         num_max_token = num_max_token_map[self.model_type.value]
         num_max_completion_tokens = num_max_token - num_prompt_tokens
         self.model_config_dict['max_tokens'] = num_max_completion_tokens
-        response = openai.ChatCompletion.create(*args, **kwargs,
+        print("using model: {}".format(self.model_type.value))
+        response = openai.chat.completions.create(*args, **kwargs,
                                                 model=self.model_type.value,
                                                 **self.model_config_dict)
         cost = prompt_cost(
-                self.model_type.value, 
+            self.model_type.value, 
-                num_prompt_tokens=response["usage"]["prompt_tokens"], 
+            num_prompt_tokens=response.usage.prompt_tokens, 
-                num_completion_tokens=response["usage"]["completion_tokens"]
+            num_completion_tokens=response.usage.completion_tokens
         )
 
         log_and_print_online(
             "**[OpenAI_Usage_Info Receive]**\nprompt_tokens: {}\ncompletion_tokens: {}\ntotal_tokens: {}\ncost: ${:.6f}\n".format(
-                response["usage"]["prompt_tokens"], response["usage"]["completion_tokens"],
+                response.usage.prompt_tokens, response.usage.completion_tokens,
-                response["usage"]["total_tokens"], cost))
+                response.usage.total_tokens, cost
+            )
+        )
         if not isinstance(response, Dict):
             raise RuntimeError("Unexpected return from OpenAI API")
         return response
@@ -116,7 +120,7 @@ class ModelFactory:
         default_model_type = ModelType.GPT_3_5_TURBO
 
         if model_type in {
-            ModelType.GPT_3_5_TURBO, ModelType.GPT_4, ModelType.GPT_4_32k,
+            ModelType.GPT_3_5_TURBO, ModelType.GPT_4, ModelType.GPT_4_TURBO, ModelType.GPT_4_32k,
             None
         }:
             model_class = OpenAIModel

camel/typing.py

@@ -46,6 +46,7 @@ class RoleType(Enum):
 class ModelType(Enum):
     GPT_3_5_TURBO = "gpt-3.5-turbo-16k-0613"
     GPT_4 = "gpt-4"
+    GPT_4_TURBO = "gpt-4-1106-preview"
     GPT_4_32k = "gpt-4-32k"
     STUB = "stub"
 

camel/utils.py

@@ -83,7 +83,7 @@ def num_tokens_from_messages(
         encoding = tiktoken.get_encoding("cl100k_base")
 
     if model in {
-        ModelType.GPT_3_5_TURBO, ModelType.GPT_4, ModelType.GPT_4_32k,
+        ModelType.GPT_3_5_TURBO, ModelType.GPT_4, ModelType.GPT_4_TURBO, ModelType.GPT_4_32k,
         ModelType.STUB
     }:
         return count_tokens_openai_chat_models(messages, encoding)
@@ -113,6 +113,8 @@ def get_model_token_limit(model: ModelType) -> int:
         return 8192
     elif model == ModelType.GPT_4_32k:
         return 32768
+    elif model == ModelType.GPT_4_TURBO:
+        return 128000
     elif model == ModelType.STUB:
         return 4096
     else:

chatdev/statistics.py

@@ -12,6 +12,7 @@ def prompt_cost(model_type: str, num_prompt_tokens: float, num_completion_tokens
         "gpt-4": 0.03,
         "gpt-4-0613": 0.03,
         "gpt-4-32k": 0.06,
+        "gpt-4-1106-preview": 0.01,
     }
 
     output_cost_map = {
@@ -22,6 +23,7 @@ def prompt_cost(model_type: str, num_prompt_tokens: float, num_completion_tokens
         "gpt-4": 0.06,
         "gpt-4-0613": 0.06,
         "gpt-4-32k": 0.12,
+        "gpt-4-1106-preview": 0.03,
     }
 
     if model_type not in input_cost_map or model_type not in output_cost_map:
@@ -107,6 +109,8 @@ def get_info(dir, log_filepath):
                 model_type = "gpt-4"
             elif model_type == "GPT_4_32k":
                 model_type = "gpt-4-32k"
+            elif model_type == "GPT_4_TURBO":
+                model_type = "gpt-4-1106-preview"
             # print("model_type:", model_type)
         
         lines = open(log_filepath, "r", encoding="utf8").read().split("\n")

requirements.txt

@@ -3,7 +3,7 @@ Flask==2.3.2
 Flask-SocketIO==5.3.4
 importlib-metadata==6.8.0
 numpy==1.24.3
-openai==0.27.8
+openai==1.1.1
 regex==2023.6.3
 requests==2.31.0
 tenacity==8.2.2

run.py

@@ -15,6 +15,7 @@ import argparse
 import logging
 import os
 import sys
+from types import ModuleType
 
 from camel.typing import ModelType
 
@@ -67,7 +68,7 @@ parser.add_argument('--task', type=str, default="Develop a basic Gomoku game.",
 parser.add_argument('--name', type=str, default="Gomoku",
                     help="Name of software, your software will be generated in WareHouse/name_org_timestamp")
 parser.add_argument('--model', type=str, default="GPT_3_5_TURBO",
-                    help="GPT Model, choose from {'GPT_3_5_TURBO','GPT_4','GPT_4_32K'}")
+                    help="GPT Model, choose from {'GPT_3_5_TURBO','GPT_4','GPT_4_TURBO','GPT_4_32K'}")
 parser.add_argument('--path', type=str, default="",
                     help="Your file directory, ChatDev will build upon your software in the Incremental mode")
 args = parser.parse_args()
@@ -78,7 +79,7 @@ args = parser.parse_args()
 #          Init ChatChain
 # ----------------------------------------
 config_path, config_phase_path, config_role_path = get_config(args.config)
-args2type = {'GPT_3_5_TURBO': ModelType.GPT_3_5_TURBO, 'GPT_4': ModelType.GPT_4, 'GPT_4_32K': ModelType.GPT_4_32k}
+args2type = {'GPT_3_5_TURBO': ModelType.GPT_3_5_TURBO, 'GPT_4': ModelType.GPT_4, 'GPT_4_TURBO': ModelType.GPT_4_TURBO, 'GPT_4_32K': ModelType.GPT_4_32k}
 chat_chain = ChatChain(config_path=config_path,
                        config_phase_path=config_phase_path,
                        config_role_path=config_role_path,