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import gradio as gr | |
import os | |
import pandas as pd | |
import matplotlib.pyplot as plt | |
import numpy as np | |
from langchain_community.chat_models import ChatAnyscale | |
from Hypothesis_Test_Agent.Hypothesis_Agent import infer_hypothesis | |
from EDA_Agent.EDA import infer_EDA | |
from Basic_Inf_Agent.Basic_Inference_Agent import infer_basic | |
print(os.getcwd()) | |
def run_agent(data_path:str = '', provider:str = 'Mistral', agent_type:str = 'EDA', query:str = '', layers:str ='', temp:float = 0.1): | |
df = pd.read_csv(data_path) | |
df.to_csv('./df.csv', index=False) | |
if provider.lower() == 'mistral': | |
llm = ChatAnyscale(model_name='mistralai/Mixtral-8x7B-Instruct-v0.1', temperature=temp) | |
if agent_type == 'Data Explorer': | |
EDA_response, EDA_image = infer_EDA(user_input=query, llm=llm, df=df) | |
return EDA_response, EDA_image | |
if agent_type == 'Hypothesis Tester': | |
hypothesis_response = infer_hypothesis(user_input=query, llm=llm, df=df) | |
return hypothesis_response, None | |
if agent_type == 'Basic Inference': | |
basic_response = infer_basic(user_input=query, df=df, llm=llm) | |
return basic_response, None | |
return None | |
demo = gr.Interface ( | |
run_agent, | |
[ | |
gr.UploadButton(label="Upload your CSV!"), | |
gr.Radio(["Mistral","GPT"],label="Select Your LLM"), | |
gr.Radio(["Data Explorer", "Hypothesis Tester", "Basic Inference", "Super Inference"], label="Choose Your Agent"), | |
gr.Text(label="Query", info="Your input to the Agent. Be descriptive!"), | |
gr.Text(label="Architecture", info="Specify the layer by layer architecture only for Super Inference Agent"), | |
gr.Slider(label="Model Temperature", info="Slide right to make your model more creative!") | |
], | |
[ | |
gr.Text(label="Agent Output", info="This might take a while to generate since agent debugs its errors too ..."), | |
gr.Image(label="Graph") | |
] | |
) | |
demo.launch(share=True) | |