搬到st_reflect.py

examples/st_game/reflect/st_reflect.py

@@ -1,3 +1,97 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 # @Desc   : st's reflection execution
+
+import asyncio
+import json
+from metagpt.logs import logger
+import time
+from ga_prompt_generator import final_response
+'''
+等待Agent和memory更新，保留相关引用但可以忽略。
+'''
+from examples.st_game.associative_memory import MemoryBasic
+
+import json
+import time
+
+
+async def agent_reflect(agent):
+    """
+    代理反思函数：生成关注点并生成洞察和证据
+
+    """
+    A = await generate_focus_point(agent.memories_list)
+
+    for i in A:
+        B = await generate_insights_and_evidence(agent, agent.memories_list, question=i)
+
+
+async def generate_focus_point(memories_list: list[MemoryBasic], n=3):
+    """
+    生成关注点函数：根据记忆列表生成关注点
+    """
+    wait_sorted_mem = [[i.accessed_time, i] for i in memories_list]
+    sorted_memories = sorted(wait_sorted_mem, key=lambda x: x[0])
+    memorys = [i for created, i in sorted_memories]
+    statements = ''
+    for i in memorys:
+        statements += i.description + "\n"
+    prompt = '''
+    {statements}
+    Given only the information above, what are {num_question} most salient high-level questions we can answer about the subjects grounded in the statements?
+    '''
+    example_output = '["What should Jane do for lunch", "Does Jane like strawberry", "Who is Jane"]'
+    out = await final_response(prompt.format(statements=statements, num_question=n),
+                               "Output must be a list of str.", example_output)
+    try:
+        poi_dict = json.loads(out)
+        return poi_dict['output']
+    except ValueError:
+        print(out)
+        logger.error('无法返回正常结果')
+        return out
+
+
+async def generate_insights_and_evidence(agent, memories_list: list[MemoryBasic], question: str, n=5):
+    """
+    生成洞察和证据函数：根据问题生成洞察和证据
+    """
+    memories_list = await agent_retrieve(agent, question, 50, 10)
+    statements = ""
+    for count, mem in enumerate(memories_list):
+        statements += f'{str(count)}. {mem.description}\n'
+    prompt = '''
+    Input:
+    {statements}
+
+    What {n} high-level insights can you infer from the above statements?
+    You should return a list of list[str,list]. The first element is the insight you have found. The second element is the 
+    '''
+
+    ret = final_response(prompt.format(
+        question=question, statements=statements, n=n), "['insightA',[1,2,3]]")
+    try:
+        insight_list = json.loads(ret)
+        for insight, index in insight_list:
+            agent.memory_list.append(MemoryBasic(
+                time.time(), None, insight, None, None))
+        return insight_list
+    except:
+        logger.error('我们无法获得想要的返回。')
+        return ret
+
+
+""" if __name__ == "__main__":
+    # 例子，构建John Agent，实现retrive
+    John_iss = "John Lin is a pharmacy shopkeeper at the Willow Market and Pharmacy who loves to help people. He is always looking for ways to make the process of getting medication easier for his customers; John Lin is living with his wife, Mei Lin, who is a college professor, and son, Eddy Lin, who is a student studying music theory; John Lin loves his family very much; John Lin has known the old couple next-door, Sam Moore and Jennifer Moore, for a few years; John Lin thinks Sam Moore is a kind and nice man; John Lin knows his neighbor, Yuriko Yamamoto, well; John Lin knows of his neighbors, Tamara Taylor and Carmen Ortiz, but has not met them before; John Lin and Tom Moreno are colleagues at The Willows Market and Pharmacy; John Lin and Tom Moreno are friends and like to discuss local politics together; John Lin knows the Moreno family somewhat well — the husband Tom Moreno and the wife Jane Moreno."
+    John = AgentMemory(
+        "John", John_iss, memory_path="agent_memories/John_memory.json")
+
+    # John的相关信息：{'Had a friendly chat with Yuriko about her garden.': 2.4992317730827667, 'Helped Mrs. Moore carry groceries into her house.': 1.957656720441911, 'Discussed local politics with Tom Moreno.': 1.9458268038234035}
+    asyncio.run(agent_reflect(John))
+    '''
+    这里是输出,list形式，返回给记忆。
+    [['The pharmacy is a friendly and helpful community.', [0, 2, 9, 12]], ['The pharmacy is a place where people come for more than just medication.', [3, 5, 13, 14]], ['The pharmacy is a place where people come for advice and conversation.', [0, 2, 6, 9, 12]], ['The pharmacy is a place where people come for assistance with daily tasks.', [3, 5, 13, 14]], ['The pharmacy is a place where people come for political discussions.', [1]]]
+    '''
+ """