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# HF libraries
from langchain_community.llms import HuggingFaceEndpoint
from langchain.agents import AgentExecutor
from langchain.agents.format_scratchpad import format_log_to_str
from langchain.agents.output_parsers import ReActJsonSingleInputOutputParser
# Import things that are needed generically
from langchain.tools.render import render_text_description
import os
from dotenv import load_dotenv
from innovation_pathfinder_ai.structured_tools.structured_tools import (
arxiv_search, get_arxiv_paper, google_search, wikipedia_search
)
from langchain.prompts import PromptTemplate
from innovation_pathfinder_ai.templates.react_json_with_memory import template_system
from innovation_pathfinder_ai.utils import logger
logger = logger.get_console_logger("hf_mixtral_agent")
config = load_dotenv(".env")
HUGGINGFACEHUB_API_TOKEN = os.getenv('HUGGINGFACEHUB_API_TOKEN')
GOOGLE_CSE_ID = os.getenv('GOOGLE_CSE_ID')
GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY')
LANGCHAIN_TRACING_V2 = "true"
LANGCHAIN_ENDPOINT = "https://api.smith.langchain.com"
LANGCHAIN_API_KEY = os.getenv('LANGCHAIN_API_KEY')
LANGCHAIN_PROJECT = os.getenv('LANGCHAIN_PROJECT')
# Load the model from the Hugging Face Hub
llm = HuggingFaceEndpoint(repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1",
temperature=0.1,
max_new_tokens=1024,
repetition_penalty=1.2,
return_full_text=False
)
tools = [
arxiv_search,
wikipedia_search,
google_search,
# get_arxiv_paper,
]
prompt = PromptTemplate.from_template(
template=template_system
)
prompt = prompt.partial(
tools=render_text_description(tools),
tool_names=", ".join([t.name for t in tools]),
)
# define the agent
chat_model_with_stop = llm.bind(stop=["\nObservation"])
agent = (
{
"input": lambda x: x["input"],
"agent_scratchpad": lambda x: format_log_to_str(x["intermediate_steps"]),
"chat_history": lambda x: x["chat_history"],
}
| prompt
| chat_model_with_stop
| ReActJsonSingleInputOutputParser()
)
# instantiate AgentExecutor
agent_executor = AgentExecutor(
agent=agent,
tools=tools,
verbose=True,
max_iterations=6, # cap number of iterations
#max_execution_time=60, # timout at 60 sec
return_intermediate_steps=True,
handle_parsing_errors=True,
) |