refactor: put agent_knowledge in agents

SocialAI-tianji · Feb 4, 2024 · 36f36cf · 36f36cf
1 parent 20c4bc5
commit 36f36cf
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Showing 6 changed files with 13 additions and 15 deletions.
diff --git a/test/agents/metagpt/role_3_streamlit_prompt.py b/test/agents/metagpt/role_3_streamlit_prompt.py
@@ -20,9 +20,7 @@
 from tianji.agents.metagpt_agents.ruyi import RuYi
 from tianji.agents.metagpt_agents.qianbianzhe import QianBianZhe
 from tianji.agents.metagpt_agents.wendao import WenDao
-
-KNOWLEDGE_PATH = r"/Users/fengzetao/Workspace/Github/SocialAI/Tianji/tianji/knowledges/04-Wishes/knowledges.txt"
-SAVE_PATH = r"/Users/fengzetao/Workspace/Github/SocialAI/Tianji/temp"
+from tianji.agents.knowledges.config import AGENT_KNOWLEDGE_PATH, AGENT_EMBEDDING_PATH
 
 
 # 给出针对回答的知识 并用md展示
@@ -51,8 +49,8 @@ async def run(self, instruction: str):
         knowledge_key = json_from_data["festival"] + json_from_data["requirement"]
         knowledge = get_docs_list_query_zhipuai(
             query_str=knowledge_key,
-            loader_file_path=KNOWLEDGE_PATH,
-            persist_directory=SAVE_PATH,
+            loader_file_path=AGENT_KNOWLEDGE_PATH.WISHES.path(),
+            persist_directory=AGENT_EMBEDDING_PATH.WISHES.path(filename="zhipuai"),
             k_num=5,
         )
         print("knowledge:\n", knowledge)

diff --git a/test/knowledges/test_get_docs_list_query.py b/test/knowledges/test_get_docs_list_query.py
@@ -1,5 +1,5 @@
 import tianji.utils.knowledge_tool as knowledgetool
-from tianji.knowledges.config import KNOWLEDGE_PATH, EMBEDDING_PATH
+from tianji.agents.knowledges.config import AGENT_KNOWLEDGE_PATH, AGENT_EMBEDDING_PATH
 from dotenv import load_dotenv
 
 load_dotenv()
@@ -10,10 +10,10 @@
 # doclist = knowledgetool.get_docs_list_query_openai(query_str="春节",loader_file_path=KNOWLEDGE_PATH, \
 #                                   persist_directory = SAVE_PATH,k_num=5)
 
-doclist = knowledgetool.get_docs_list_query_openai(
+doclist = knowledgetool.get_docs_list_query_zhipuai(
     query_str="春节",
-    loader_file_path=KNOWLEDGE_PATH.WISHES.path(),
-    persist_directory=EMBEDDING_PATH.WISHES.path(filename="openai"),
+    loader_file_path=AGENT_KNOWLEDGE_PATH.WISHES.path(),
+    persist_directory=AGENT_EMBEDDING_PATH.WISHES.path(filename="zhipuai"),
     k_num=5,
 )
 

diff --git a/tianji/knowledges/04-Wishes/knowledges.txt → ...gents/knowledges/04-Wishes/knowledges.txt b/tianji/knowledges/04-Wishes/knowledges.txt → ...gents/knowledges/04-Wishes/knowledges.txt
diff --git a/tianji/knowledges/__init__.py → tianji/agents/knowledges/__init__.py b/tianji/knowledges/__init__.py → tianji/agents/knowledges/__init__.py
diff --git a/tianji/knowledges/config.py → tianji/agents/knowledges/config.py b/tianji/knowledges/config.py → tianji/agents/knowledges/config.py
@@ -18,8 +18,8 @@ def get_all_knowledge_paths(knowledge_path: str = METAGPT_ROOT, suffix: str = ".
 """
 
 
-class KNOWLEDGE_PATH(str, Enum):
-    WISHES = TIANJI_PATH / "tianji/knowledges/04-Wishes"
+class AGENT_KNOWLEDGE_PATH(str, Enum):
+    WISHES = TIANJI_PATH / "tianji/agents/knowledges/04-Wishes"
 
     def path(self):
         load_path = self.value
@@ -28,7 +28,7 @@ def path(self):
         return os.path.join(load_path, "knowledges.txt")
 
 
-class EMBEDDING_PATH(str, Enum):
+class AGENT_EMBEDDING_PATH(str, Enum):
     WISHES = TIANJI_PATH / "temp/embedding/04-Wishes"
 
     def path(self, filename="other"):

diff --git a/tianji/agents/metagpt_agents/ruyi/action.py b/tianji/agents/metagpt_agents/ruyi/action.py
@@ -9,7 +9,7 @@
 
 from tianji.utils.common_llm_api import LLMApi
 from tianji.utils.json_from import SharedDataSingleton
-from tianji.knowledges.config import KNOWLEDGE_PATH, EMBEDDING_PATH
+from tianji.agents.knowledges.config import AGENT_KNOWLEDGE_PATH, AGENT_EMBEDDING_PATH
 from tianji.utils.knowledge_tool import (
     get_docs_list_query_openai,
     get_docs_list_query_zhipuai,
@@ -42,8 +42,8 @@ async def run(self, instruction: str):
         knowledge_key = json_from_data["festival"] + json_from_data["requirement"]
         knowledge = get_docs_list_query_zhipuai(
             query_str=knowledge_key,
-            loader_file_path=KNOWLEDGE_PATH.WISHES.path(),
-            persist_directory=EMBEDDING_PATH.WISHES.path(filename="zhipuai"),
+            loader_file_path=AGENT_KNOWLEDGE_PATH.WISHES.path(),
+            persist_directory=AGENT_EMBEDDING_PATH.WISHES.path(filename="zhipuai"),
             k_num=5,
         )
         print("knowledge:\n", knowledge)