-- Lean 4 proof step from Mathlib.Probability.Independence.Kernel.Indep (goal)
Goal:
α : Type u_1
Ω : Type u_2
ι : Type u_3
_mα : MeasurableSpace α
_mΩ : MeasurableSpace Ω
κ : Kernel α Ω
μ : Measure α
m : ι → MeasurableSpace Ω
h_le : ∀ (i : ι), m i ≤ _mΩ
π : ι → Set (Set Ω)
h_pi : ∀ (n : ι), IsPiSystem (π n)
h_generate : ∀ (i : ι), m i = generateFrom (π i)
h_ind : iIndepSets π κ μ
inl : ∀ (h_ind : iIndepSets π κ 0), Kernel.iIndep m κ 0
inr inr₁ : ∀ (hμ : μ ≠ 0), Kernel.iIndep m κ μ
inr₂ :
  ∀ (hμ : μ ≠ 0) (η : Kernel α Ω)
    (η_eq :
      Filter.EventuallyEq.{u_1, u_2} (β := Measure Ω) (ae μ) (⇑κ : (a : α) → Measure Ω) (⇑η : (a : α) → Measure Ω))
    (hη : IsMarkovKernel η), Kernel.iIndep m κ μ
inr₃ :
  ∀ (hμ : μ ≠ 0) (η : Kernel α Ω)
    (η_eq :
      Filter.EventuallyEq.{u_1, u_2} (β := Measure Ω) (ae μ) (⇑κ : (a : α) → Measure Ω) (⇑η : (a : α) → Measure Ω))
    (hη : IsMarkovKernel η), Kernel.iIndep m η μ
inr₄ :
  ∀ (hμ : μ ≠ 0) (η : Kernel α Ω)
    (η_eq :
      Filter.EventuallyEq.{u_1, u_2} (β := Measure Ω) (ae μ) (⇑κ : (a : α) → Measure Ω) (⇑η : (a : α) → Measure Ω))
    (hη : IsMarkovKernel η) (s : Finset ι) {f : ι → Set Ω}
    (_H :
      ∀ i ∈ s,
        Membership.mem (γ := Set (Set Ω)) ((fun (x : ι) ↦ ({s : Set Ω | MeasurableSet s} : Set (Set Ω))) i) (f i)),
    ∀ᵐ (a : α) ∂μ,
      Eq (α := ℝ≥0∞) ((((η : (a : α) → Measure Ω) a : Measure Ω) : (a : Set Ω) → ℝ≥0∞) (⋂ i ∈ s, f i) : ℝ≥0∞)
        (∏ i ∈ s, (((η : (a : α) → Measure Ω) a : Measure Ω) : (a : Set Ω) → ℝ≥0∞) (f i) : ℝ≥0∞)
⊢ Kernel.iIndep m κ μ
have inr₅ : ∀ (hμ : μ ≠ 0) (η : Kernel α Ω)
  (η_eq : Filter.EventuallyEq.{u_1, u_2} (β := Measure Ω) (ae μ) (⇑κ : (a : α) → Measure Ω) (⇑η : (a : α) → Measure Ω))
  (hη : IsMarkovKernel η) (s : Finset ι) {f : ι → Set Ω}
  (_H :
    ∀ (i : ι),
      Membership.mem (γ := Finset ι) ∅ i →
        Membership.mem (γ := Set (Set Ω)) ((fun (x : ι) ↦ ({s : Set Ω | MeasurableSet s} : Set (Set Ω))) i) (f i)),
  ∀ᵐ (a : α) ∂μ,
    Eq (α := ℝ≥0∞)
      ((((η : (a : α) → Measure Ω) a : Measure Ω) : (a : Set Ω) → ℝ≥0∞)
          (⋂ (i : ι), ⋂ (_ : Membership.mem (γ := Finset ι) ∅ i), f i) :
        ℝ≥0∞)
      (∏ i ∈ ∅, (((η : (a : α) → Measure Ω) a : Measure Ω) : (a : Set Ω) → ℝ≥0∞) (f i) : ℝ≥0∞)
Tactic: classical
  rcases eq_or_ne μ 0 with rfl | hμ
  · simp
  obtain ⟨η, η_eq, hη⟩ : ∃ (η : Kernel α Ω), κ =ᵐ[μ] η ∧ IsMarkovKernel η :=
    exists_ae_eq_isMarkovKernel h_ind.ae_isProbabilityMeasure hμ
  apply iIndep.congr (Filter.EventuallyEq.symm η_eq)
  intro s f
  refine Finset.induction ?_ ?_ s
  · simp
  · intro a S ha_notin_S h_rec hf_m
    have hf_m_S : ∀ x ∈ S, MeasurableSet[m x] (f x) := fun x hx => hf_m x (by simp [hx])
    let p := piiUnionInter π S
    set m_p := generateFrom p with hS_eq_generate
    have h_indep : Indep m_p (m a) η μ := by
      have hp : IsPiSystem p := isPiSystem_piiUnionInter π h_pi S
      have h_le' : ∀ i, generateFrom (π i) ≤ _mΩ := fun i ↦ (h_generate i).symm.trans_le (h_le i)
      have hm_p : m_p ≤ _mΩ := generateFrom_piiUnionInter_le π h_le' S
      exact IndepSets.indep hm_p (h_le a) hp (h_pi a) hS_eq_generate (h_generate a)
        (iIndepSets.piiUnionInter_of_notMem (h_ind.congr η_eq) ha_notin_S)
    have h := h_indep.symm (f a) (⋂ n ∈ S, f n) (hf_m a (Finset.mem_insert_self a S)) ?_
    · filter_upwards [h_rec hf_m_S, h] with a' ha' h'
      rwa [Finset.set_biInter_insert, Finset.prod_insert ha_notin_S, ← ha']
    · have h_le_p : ∀ i ∈ S, m i ≤ m_p := by
        intro n hn
        rw [hS_eq_generate, h_generate n]
        exact le_generateFrom_piiUnionInter (S : Set ι) hn
      have h_S_f : ∀ i ∈ S, MeasurableSet[m_p] (f i) :=
        fun i hi ↦ (h_le_p i hi) (f i) (hf_m_S i hi)
      exact S.measurableSet_biInter h_S_f