ai-mirow-projects
/
swarms
mirror of https://github.com/kyegomez/swarms
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

clean up

Browse Source 
Former-commit-id: 90c5f56793
pull/47/head
Kye 1 year ago
parent d2ce53d6c8
commit 788f027634
1 changed files with 6 additions and 6 deletions
Show Stats Download Patch File Download Diff File

12
swarms/workers/worker_node.py
Unescape View File

@ -33,7 +33,7 @@ class WorkerNodeInitializer:
openai_api_key: str, openai_api_key: str,
llm: Optional[Union[InMemoryDocstore, ChatOpenAI]] = None, llm: Optional[Union[InMemoryDocstore, ChatOpenAI]] = None,
tools: Optional[List[Tool]] = None, tools: Optional[List[Tool]] = None,
vectorstore: Optional[FAISS] = None, # vectorstore: Optional[FAISS] = None,
embedding_size: Optional[int] = 1926, embedding_size: Optional[int] = 1926,
worker_name: Optional[str] = "Swarm Worker AI Assistant", worker_name: Optional[str] = "Swarm Worker AI Assistant",
worker_role: Optional[str] = "Assistant", worker_role: Optional[str] = "Assistant",
@ -44,7 +44,7 @@ class WorkerNodeInitializer:
self.openai_api_key = openai_api_key self.openai_api_key = openai_api_key
self.llm = llm if llm is not None else ChatOpenAI() self.llm = llm if llm is not None else ChatOpenAI()
self.tools = tools if tools is not None else [ReadFileTool(), WriteFileTool()] self.tools = tools if tools is not None else [ReadFileTool(), WriteFileTool()]
self.vectorstore = vectorstore # self.vectorstore = vectorstore
# Initializing agent in the constructor # Initializing agent in the constructor
self.worker_name = worker_name self.worker_name = worker_name
@ -91,9 +91,8 @@ class WorkerNodeInitializer:
def initialize_vectorstore(self): def initialize_vectorstore(self):
try: try:
embedding_size = self.embedding_size
embeddings_model = OpenAIEmbeddings(openai_api_key=self.openai_api_key) embeddings_model = OpenAIEmbeddings(openai_api_key=self.openai_api_key)
embedding_size = embedding_size embedding_size = self.embedding_size
index = faiss.IndexFlatL2(embedding_size=embedding_size) index = faiss.IndexFlatL2(embedding_size=embedding_size)
return FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {}) return FAISS(embeddings_model.embed_query, index, InMemoryDocstore({}), {})
@ -123,8 +122,8 @@ class WorkerNode:
temperature: int, temperature: int,
llm: Optional[Union[InMemoryDocstore, ChatOpenAI]] = None, llm: Optional[Union[InMemoryDocstore, ChatOpenAI]] = None,
tools: Optional[List[Tool]] = None, tools: Optional[List[Tool]] = None,
vectorstore: Optional[FAISS] = None, # vectorstore: Optional[FAISS] = None,
embedding_size: Optional[int] = 1926, embedding_size: Optional[int] = 4026,
worker_name: Optional[str] = "Swarm Worker AI Assistant", worker_name: Optional[str] = "Swarm Worker AI Assistant",
worker_role: Optional[str] = "Assistant", worker_role: Optional[str] = "Assistant",
human_in_the_loop: Optional[bool] = False, human_in_the_loop: Optional[bool] = False,
@ -139,6 +138,7 @@ class WorkerNode:
self.worker_node_initializer = WorkerNodeInitializer(openai_api_key) self.worker_node_initializer = WorkerNodeInitializer(openai_api_key)
self.name = worker_name # Added a name attribute self.name = worker_name # Added a name attribute
self.description = "A worker node that executes tasks" # Added a description attribute self.description = "A worker node that executes tasks" # Added a description attribute
self.embedding_size = embedding_size
def initialize_llm(self, llm_class, temperature): def initialize_llm(self, llm_class, temperature):

Write Preview
Loading…
Cancel
Save