pull/430/head
Kye 10 months ago
parent 9b225e955b
commit 0a48a97bf6

@ -9,8 +9,9 @@ from langchain_experimental.autonomous_agents.hugginggpt.task_planner import (
load_chat_planner,
)
from transformers import load_tool
from swarms.utils.loguru_logger import logger
from swarms.structs.agent import Agent
from swarms.utils.loguru_logger import logger
class OmniModalAgent(Agent):

@ -1,18 +1,13 @@
import os
from typing import List
# import faiss
from langchain.docstore import InMemoryDocstore
from langchain.embeddings import OpenAIEmbeddings
# from langchain.vectorstores import FAISS
from langchain_experimental.autonomous_agents import AutoGPT
from swarms.structs.agent import Agent
from swarms.tools.tool import BaseTool
from swarms.utils.decorators import error_decorator, timing_decorator
class Worker:
class Worker(Agent):
"""
The Worker class represents an autonomous agent that can perform tassks through
function calls or by running a chat.

@ -9,13 +9,14 @@ from dotenv import load_dotenv
from swarms.utils.data_to_text import data_to_text
from swarms.utils.markdown_message import display_markdown_message
from swarms.memory.base_vectordb import AbstractVectorDatabase
# Load environment variables
load_dotenv()
# Results storage using local ChromaDB
class ChromaDB:
class ChromaDB(AbstractVectorDatabase):
"""
ChromaDB database

@ -6,8 +6,8 @@ from langchain.chains.question_answering import load_qa_chain
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import Chroma
from swarms.models.openai_models import OpenAIChat
from swarms.models.popular_llms import OpenAIChat
from swarms.memory.base_vectordb import AbstractVectorDatabase
def synchronized_mem(method):
@ -31,7 +31,7 @@ def synchronized_mem(method):
return wrapper
class LangchainChromaVectorMemory:
class LangchainChromaVectorMemory(AbstractVectorDatabase):
"""
A class representing a vector memory for storing and retrieving text entries.

@ -5,9 +5,10 @@ from sqlalchemy import JSON, Column, String, create_engine
from sqlalchemy.dialects.postgresql import UUID
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import Session
from swarms.memory.base_vectordb import AbstractVectorDatabase
class PostgresDB:
class PostgresDB(AbstractVectorDatabase):
"""
A class representing a Postgres database.
@ -67,7 +68,7 @@ class PostgresDB:
return VectorModel
def add_or_update_vector(
def add(
self,
vector: str,
vector_id: Optional[str] = None,
@ -97,7 +98,7 @@ class PostgresDB:
except Exception as e:
print(f"Error adding or updating vector: {e}")
def query_vectors(
def query(
self, query: Any, namespace: Optional[str] = None
) -> List[Any]:
"""

@ -1,6 +1,7 @@
from typing import List
from httpx import RequestError
from swarms.memory.base_vectordb import AbstractVectorDatabase
try:
from sentence_transformers import SentenceTransformer
@ -20,7 +21,7 @@ except ImportError:
print("pip install qdrant-client")
class Qdrant:
class Qdrant(AbstractVectorDatabase):
"""
Qdrant class for managing collections and performing vector operations using QdrantClient.

@ -25,7 +25,6 @@ class SequentialAccountingSwarm(AbstractSwarm):
Run the swarm simulation.
"""
def __init__(
self,
name: Optional[str] = "kyegomez/sequential-accounting-swarm",
@ -35,6 +34,8 @@ class SequentialAccountingSwarm(AbstractSwarm):
iters: Optional[int] = 100,
max_agents: Optional[int] = 100,
agents: Sequence[AbstractLLM] = None,
*args,
**kwargs,
):
super().__init__()
self.name = name
@ -98,6 +99,8 @@ class AutoSwarmRouter(AbstractSwarm):
custom_preprocess: Optional[Callable] = None,
custom_postprocess: Optional[Callable] = None,
custom_router: Optional[Callable] = None,
*args,
**kwargs,
):
super().__init__()
self.name = name

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