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import HuggingFaceAI
from langchain_huggingface import HuggingFacePipeline, ChatHuggingFace
from langchain_core.messages import BaseMessage, HumanMessage, AIMessage
from agents.supervisor import Supervisor
from agents.agent_support import create_agent
from agents.agent_node import agent_node
from agents.help_agent import HelpAgent
from agents.project_agent import ProjectAgent
from agent_system import AgentSystem
from tools.multiply_tool import multiply
import functools
import os
from uuid import uuid4
unique_id = uuid4().hex[0:8]
os.environ["LANGCHAIN_TRACING_V2"] = "true"
os.environ["LANGCHAIN_PROJECT"] = f"InfiniFleetTrace"
os.environ["LANGCHAIN_ENDPOINT"] = "https://api.smith.langchain.com"
os.environ["LANGCHAIN_API_KEY"] = "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" # Update to your API key
llm = HuggingFacePipeline.from_model_id(
model_id="mistralai/Mistral-7B-Instruct-v0.3",
device_map="auto",
task="text-generation",
pipeline_kwargs={
"max_new_tokens": 100,
"top_k": 50,
},
)
print("Creating chat interface")
chat_llm = ChatHuggingFace(llm=llm)
print("Done")
print("---------")
supervisor = Supervisor(chat_llm, ["ProductHelp","ProjectHelp", "Multiplier"])
help_agent = HelpAgent(chat_llm, "You provide help for the InfiniFleet product in general")
help_node = functools.partial(agent_node, agent=help_agent, name="ProductHelp")
project_agent = ProjectAgent(chat_llm, "Always use robot_information tool to get all required information.")
project_node = functools.partial(agent_node, agent=project_agent, name="ProjectHelp")
print("--project agent-------")
input_data = "Use the tool to give me information about how many robots there are in the project called 'largeProject'."
result = project_agent.invoke({"messages":[HumanMessage(input_data)]})
print(result)
print("---------")
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