Upload Agent.py

Agent.py

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+#import openai
+import os
+import backoff
+import time
+import random
+import traceback
+#from openai.error import RateLimitError, APIError, ServiceUnavailableError, APIConnectionError
+#from .openai_utils import OutOfQuotaException, AccessTerminatedException
+#from .openai_utils import num_tokens_from_string, model2max_context
+from together import Together
+
+
+class Agent:
+    def __init__(self, model_name: str, name: str, temperature: float, sleep_time: float=0) -> None:
+        """Create an agent
+
+        Args:
+            model_name(str): model name
+            name (str): name of this agent
+            temperature (float): higher values make the output more random, while lower values make it more focused and deterministic
+            sleep_time (float): sleep because of rate limits
+        """
+        self.model_name = model_name
+        self.name = name
+        self.temperature = temperature
+        self.memory_lst = []
+        self.sleep_time = sleep_time
+        self.client = Together(api_key=os.environ.get('TOGETHER_API_KEY'))
+
+    def query(self, messages: "list[dict]", max_tokens: int, temperature: float) -> str:
+        """make a query
+
+        Args:
+            messages (list[dict]): chat history in turbo format
+            max_tokens (int): max token in api call
+            api_key (str): openai api key
+            temperature (float): sampling temperature
+
+        Raises:
+            OutOfQuotaException: the apikey has out of quota
+            AccessTerminatedException: the apikey has been ban
+
+        Returns:
+            str: the return msg
+        """
+        time.sleep(self.sleep_time)
+        try:
+            #response = openai.ChatCompletion.create(
+            #    model=self.model_name,
+            #    messages=messages,
+            #    temperature=temperature,
+            #    max_tokens=max_tokens,
+            #    api_key=api_key,
+            #)
+            #gen = response['choices'][0]['message']['content']                
+            response = self.client.chat.completions.create(
+                model=self.model_name,
+                messages=messages,
+                max_tokens=512,
+                temperature=0.7,
+                top_p=0.7,
+                top_k=50,
+                repetition_penalty=1,
+                stop=["<|im_start|>","<|im_end|>"],
+                stream=False
+            )
+            #print(response.choices[0].message.content)
+            gen = response.choices[0].message.content
+            # 去除字符串中的所有 ```
+            cleaned_text = gen.replace('```', '')
+            return cleaned_text
+
+        except Exception as e:
+            print(f"An error occurred: {e}")
+            traceback.print_exc()  # 打印详细的错误堆栈信息
+
+    def set_meta_prompt(self, meta_prompt: str):
+        """Set the meta_prompt
+
+        Args:
+            meta_prompt (str): the meta prompt
+        """
+        self.memory_lst.append({"role": "system", "content": f"{meta_prompt}"})
+
+    def add_event(self, event: str):
+        """Add an new event in the memory
+
+        Args:
+            event (str): string that describe the event.
+        """
+        self.memory_lst.append({"role": "user", "content": f"{event}"})
+
+    def add_memory(self, memory: str):
+        """Monologue in the memory
+
+        Args:
+            memory (str): string that generated by the model in the last round.
+        """
+        self.memory_lst.append({"role": "assistant", "content": f"{memory}"})
+        print(f"----- {self.name} -----\n{memory}\n")
+
+    def ask(self, temperature: float=None):
+        """Query for answer
+
+        Args:
+        """
+        # query
+        #num_context_token = sum([num_tokens_from_string(m["content"], self.model_name) for m in self.memory_lst])
+        #max_token = model2max_context - num_context_token
+        return self.query(self.memory_lst, 100, temperature=temperature if temperature else self.temperature)