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完成PR374修改
This commit is contained in:
didi 2023-09-28 11:18:22 +08:00
parent 6911ca87ab
commit c10f1306f5
3 changed files with 10 additions and 10 deletions
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12
examples/st_game/memory/retrieve.py
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@ -27,10 +27,10 @@ def agent_retrive(agentmemory:AgentMemory, currtime:datetime, memory_forget:floa
memories = sorted_memories[:n] if len(sorted_memories) >= n else sorted_memories
Score_list = []
Score_list = extract_importance(memories,Score_list)
Score_list = extract_recency(currtime,memory_forget,Score_list)
Score_list = extract_relevance(query,Score_list)
Score_list = normalize_Socre_floats(Score_list,0,1)
Score_list = extract_importance(memories, Score_list)
Score_list = extract_recency(currtime, memory_forget, Score_list)
Score_list = extract_relevance(query, Score_list)
Score_list = normalize_Socre_floats(Score_list, 0, 1)
total_dict = {}
gw = [1,1,1] # 三个因素的权重,重要性，近因性，相关性
@ -41,7 +41,7 @@ def agent_retrive(agentmemory:AgentMemory, currtime:datetime, memory_forget:floa
)
total_dict[Score_list[i]['memory']] = total_score
result = top_highest_x_values(total_dict,topk)
result = top_highest_x_values(total_dict, topk)
return result
@ -73,7 +73,7 @@ def extract_relevance(query, Score_list):
query_embedding = embedding_tools(query)
# 进行
for i in range(len(Score_list)):
result = cos_sim(Score_list[i]["memory"].embedding_key,query_embedding)
result = cos_sim(Score_list[i]["memory"].embedding_key, query_embedding)
Score_list[i]['relevance'] = result
return Score_list

0
examples/st_game/prompts/prompts_templates/poignancy_chat_v1.txt → examples/st_game/prompts/poignancy_chat_v1.txt
View file

8
examples/st_game/prompts/run_gpt_prompts.py
View file

@ -7,11 +7,11 @@ from memory.scratch import Scratch
from memory.associative_memory import MemoryBasic
import json
def run_gpt_prompt_chat_poignancy(scratch:Scratch,content:MemoryBasic.content)->str:
def get_poignancy_action(scratch:Scratch, content:MemoryBasic.content)->str:
"""
衡量事件心酸度
"""
def create_prompt_input(scratch,content):
def create_prompt_input(scratch, content):
prompt_input = [scratch.name,
scratch.iss,
scratch.name,
@ -20,11 +20,11 @@ def run_gpt_prompt_chat_poignancy(scratch:Scratch,content:MemoryBasic.content)->
# 1. Prompt构建
# 2. Instruction给出
prompt_template = "prompt_templates/poignancy_chat_v1.txt" ########
prompt_template = "poignancy_chat_v1.txt" ########
prompt_input = create_prompt_input(scratch, content) ########
prompt = prompt_generate(prompt_input, prompt_template)
special_instruction = "The output should ONLY contain ONE integer value on the scale of 1 to 10."
poignancy = special_response_generate(prompt,special_instruction)
poignancy = special_response_generate(prompt, special_instruction)
try:
poi_dict = json.loads(poignancy)
return (poi_dict['poignancy'])