Pymc3 - Mean changing for every data point

I have the following model im pymc3.

import pandas as pd
import pymc3 as pm
import numpy as np
import arviz as az

with basic_model:
     lambda1 = pm.Gamma(lambda1, alpha=0.001, beta=0.001)
     p =  pm.Beta('p', 1, 1,)
     z = [0.0] * len(x['Length'].values)
     Y_obs = [0.0] * len(x['Length'].values)
 
     for i in range(len(x['Length'].values)):
        z[i] = pm.Bernoulli('z[i]',p)
        Y_obs[i] = pm.Poisson(Y_obs[i], mu=lambda1*z[i]*x['Length'].values+0.001, observed=x['Count'].values[i])
     trace = pm.sample(7000, tune=2000, cores=1, return_inferencedata=True)

x is a data frame that is read form a csv file. It is producing the error for the names Y_obs[i] and z[i]. I understand that I cannot change use the same name for the variables, but I couldn’t figure out how to change the rate of Y_obs[i] at every iteration. At a later stage, I will be changing the rates with if-else conditions, as well. How do I define a different mean for every data point?