iteratisons on agent class, moving away from langchain

Former-commit-id: 874eaa12e1
pull/47/head
Kye 1 year ago
parent 4893b55054
commit 03296b4d0f

@ -7,12 +7,11 @@ from pydantic import ValidationError
from swarms.agents.utils.Agent import AgentOutputParser from swarms.agents.utils.Agent import AgentOutputParser
from swarms.agents.utils.human_input import HumanInputRun from swarms.agents.utils.human_input import HumanInputRun
from swarms.agents.prompts.prompt_generator import FINISH_NAME from swarms.agents.prompts.prompt_generator import FINISH_NAME
from swarms.agents.models.base import AbstractModel
from langchain.chains.llm import LLMChain from langchain.chains.llm import LLMChain
from langchain.chat_models.base import BaseChatModel
from langchain.memory import ChatMessageHistory from langchain.memory import ChatMessageHistory
from langchain.schema import (BaseChatMessageHistory, Document,) from langchain.schema import (BaseChatMessageHistory, Document,)
from langchain.schema.messages import AIMessage, HumanMessage, SystemMessage from langchain.schema.messages import AIMessage, HumanMessage, SystemMessage
from langchain.tools.base import BaseTool from langchain.tools.base import BaseTool
@ -25,17 +24,17 @@ class Agent:
def __init__( def __init__(
self, self,
ai_name: str, ai_name: str,
memory: VectorStoreRetriever,
chain: LLMChain, chain: LLMChain,
memory: VectorStoreRetriever,
output_parser: BaseAgentOutputParser, output_parser: BaseAgentOutputParser,
tools: List[BaseTool], tools: List[BaseTool],
feedback_tool: Optional[HumanInputRun] = None, feedback_tool: Optional[HumanInputRun] = None,
chat_history_memory: Optional[BaseChatMessageHistory] = None, chat_history_memory: Optional[BaseChatMessageHistory] = None,
): ):
self.ai_name = ai_name self.ai_name = ai_name
self.chain = chain
self.memory = memory self.memory = memory
self.next_action_count = 0 self.next_action_count = 0
self.chain = chain
self.output_parser = output_parser self.output_parser = output_parser
self.tools = tools self.tools = tools
self.feedback_tool = feedback_tool self.feedback_tool = feedback_tool
@ -48,7 +47,7 @@ class Agent:
ai_role: str, ai_role: str,
memory: VectorStoreRetriever, memory: VectorStoreRetriever,
tools: List[BaseTool], tools: List[BaseTool],
llm: BaseChatModel, llm: AbstractModel,
human_in_the_loop: bool = False, human_in_the_loop: bool = False,
output_parser: Optional[BaseAgentOutputParser] = None, output_parser: Optional[BaseAgentOutputParser] = None,
chat_history_memory: Optional[BaseChatMessageHistory] = None, chat_history_memory: Optional[BaseChatMessageHistory] = None,

@ -2,11 +2,6 @@ from abc import ABC, abstractmethod
class AbstractModel(ABC): class AbstractModel(ABC):
#abstract base class for language models #abstract base class for language models
@abstractmethod
def __init__(self, model_name **kwargs):
self.model_name = model_name
@abstractmethod @abstractmethod
def generate(self, prompt): def generate(self, prompt):
#generate text using language model #generate text using language model

@ -1,4 +1,3 @@
import os
from transformers import AutoTokenizer, AutoModelForCausalLM from transformers import AutoTokenizer, AutoModelForCausalLM
class Petals: class Petals:

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