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memory tool update, minor cleanup, utility models

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frdel 2024-07-12 10:19:21 +02:00
parent 76ff3c5fcf
commit b3adcc7bca
11 changed files with 204 additions and 55 deletions
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23
python/tools/memory_tool.py
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@ -9,7 +9,18 @@ db: VectorDB | None = None
class Memory(Tool):
def execute(self,**kwargs):
result = process_query(self.agent, self.args["memory"],self.args["action"], result_count=self.agent.config.auto_memory_count)
result=[]
if "query" in kwargs:
if "threshold" in kwargs: threshold = float(kwargs["threshold"])
else: threshold = 0.1
result = process_query(self.agent, kwargs["query"], action="load", threshold=threshold, result_count=3)
elif "memorize" in kwargs:
result = process_query(self.agent, kwargs["memorize"], action="save")
elif "forget" in kwargs:
result = process_query(self.agent, kwargs["forget"], action="delete")
# result = process_query(self.agent, self.args["memory"],self.args["action"], result_count=self.agent.config.auto_memory_count)
return Response(message="\n\n".join(result), break_loop=False)
@ -19,21 +30,21 @@ def initialize(embeddings_model, subdir=""):
db = VectorDB(embeddings_model=embeddings_model, in_memory=False, cache_dir=dir)
def process_query(agent:Agent, message: str, action: str = "load", result_count: int = 3, **kwargs):
def process_query(agent:Agent, message: str, action: str = "load", result_count: int = 3, threshold: float = 0.1, **kwargs):
if not db: initialize(agent.config.embeddings_model, subdir=agent.config.memory_subdir)
if action.strip().lower() == "save":
id = db.insert_document(str(message)) # type: ignore
return files.read_file("./prompts/fw.memory_saved.md")
return [files.read_file("./prompts/fw.memory_saved.md")]
elif action.strip().lower() == "delete":
deleted = db.delete_documents(message) # type: ignore
return files.read_file("./prompts/fw.memories_deleted.md", count=deleted)
return [files.read_file("./prompts/fw.memories_deleted.md", count=deleted)]
else:
results=[]
docs = db.search_max_rel(message,result_count) # type: ignore
if len(docs)==0: return files.read_file("./prompts/fw.memories_not_found.md", query=message)
docs = db.search_similarity_threshold(message,result_count,threshold) # type: ignore
if len(docs)==0: return [files.read_file("./prompts/fw.memories_not_found.md", query=message)]
for doc in docs:
results.append(doc.page_content)
return results