diff --git a/llvm/include/llvm/Analysis/InlineModelFeatureMaps.h b/llvm/include/llvm/Analysis/InlineModelFeatureMaps.h
--- a/llvm/include/llvm/Analysis/InlineModelFeatureMaps.h
+++ b/llvm/include/llvm/Analysis/InlineModelFeatureMaps.h
@@ -129,9 +129,10 @@
 constexpr size_t NumberOfFeatures =
     static_cast<size_t>(FeatureIndex::NumberOfFeatures);
 
-extern const std::array<TensorSpec, NumberOfFeatures> FeatureMap;
+extern const std::vector<TensorSpec> FeatureMap;
 
 extern const char *const DecisionName;
+extern const TensorSpec InlineDecisionSpec;
 extern const char *const DefaultDecisionName;
 extern const char *const RewardName;
 
diff --git a/llvm/include/llvm/Analysis/InteractiveModelRunner.h b/llvm/include/llvm/Analysis/InteractiveModelRunner.h
--- a/llvm/include/llvm/Analysis/InteractiveModelRunner.h
+++ b/llvm/include/llvm/Analysis/InteractiveModelRunner.h
@@ -48,7 +48,7 @@
   static bool classof(const MLModelRunner *R) {
     return R->getKind() == MLModelRunner::Kind::Interactive;
   }
-  void switchContext(StringRef Name) {
+  void switchContext(StringRef Name) override {
     Log->switchContext(Name);
     Log->flush();
   }
diff --git a/llvm/include/llvm/Analysis/MLModelRunner.h b/llvm/include/llvm/Analysis/MLModelRunner.h
--- a/llvm/include/llvm/Analysis/MLModelRunner.h
+++ b/llvm/include/llvm/Analysis/MLModelRunner.h
@@ -49,6 +49,7 @@
 
   enum class Kind : int { Unknown, Release, Development, NoOp, Interactive };
   Kind getKind() const { return Type; }
+  virtual void switchContext(StringRef Name) {}
 
 protected:
   MLModelRunner(LLVMContext &Ctx, Kind Type, size_t NrInputs)
diff --git a/llvm/include/llvm/Analysis/ReleaseModeModelRunner.h b/llvm/include/llvm/Analysis/ReleaseModeModelRunner.h
--- a/llvm/include/llvm/Analysis/ReleaseModeModelRunner.h
+++ b/llvm/include/llvm/Analysis/ReleaseModeModelRunner.h
@@ -85,6 +85,12 @@
   void *arg_data(int) { llvm_unreachable(NOOP_MODEL_ERRMSG); }
 #undef NOOP_MODEL_ERRMSG
 };
+
+template <class T> bool isEmbeddedModelEvaluatorValid() { return true; }
+
+template <> inline bool isEmbeddedModelEvaluatorValid<NoopSavedModelImpl>() {
+  return false;
+}
 } // namespace llvm
 
 #endif // LLVM_ANALYSIS_RELEASEMODEMODELRUNNER_H
diff --git a/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp b/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
--- a/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
+++ b/llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp
@@ -283,7 +283,7 @@
   FT.push_back(TensorSpec::createSpec<int64_t>(DefaultDecisionName, {1}));
 
   DecisionPos = FT.size();
-  FT.push_back(TensorSpec::createSpec<int64_t>(DecisionName, {1}));
+  FT.push_back(InlineDecisionSpec);
   std::error_code EC;
   auto OS = std::make_unique<raw_fd_ostream>(TrainingLog, EC);
   if (EC)
diff --git a/llvm/lib/Analysis/InlineAdvisor.cpp b/llvm/lib/Analysis/InlineAdvisor.cpp
--- a/llvm/lib/Analysis/InlineAdvisor.cpp
+++ b/llvm/lib/Analysis/InlineAdvisor.cpp
@@ -231,10 +231,8 @@
 #endif
     break;
   case InliningAdvisorMode::Release:
-#ifdef LLVM_HAVE_TF_AOT
     LLVM_DEBUG(dbgs() << "Using release-mode inliner policy.\n");
     Advisor = llvm::getReleaseModeAdvisor(M, MAM);
-#endif
     break;
   }
 
diff --git a/llvm/lib/Analysis/MLInlineAdvisor.cpp b/llvm/lib/Analysis/MLInlineAdvisor.cpp
--- a/llvm/lib/Analysis/MLInlineAdvisor.cpp
+++ b/llvm/lib/Analysis/MLInlineAdvisor.cpp
@@ -18,10 +18,12 @@
 #include "llvm/Analysis/FunctionPropertiesAnalysis.h"
 #include "llvm/Analysis/InlineCost.h"
 #include "llvm/Analysis/InlineModelFeatureMaps.h"
+#include "llvm/Analysis/InteractiveModelRunner.h"
 #include "llvm/Analysis/LazyCallGraph.h"
 #include "llvm/Analysis/LoopInfo.h"
 #include "llvm/Analysis/MLModelRunner.h"
 #include "llvm/Analysis/OptimizationRemarkEmitter.h"
+#include "llvm/Analysis/ReleaseModeModelRunner.h"
 #include "llvm/Analysis/TargetTransformInfo.h"
 #include "llvm/IR/Dominators.h"
 #include "llvm/IR/InstIterator.h"
@@ -30,19 +32,37 @@
 
 using namespace llvm;
 
+static cl::opt<std::string> InteractiveChannelBaseName(
+    "inliner-interactive-channel-base", cl::Hidden,
+    cl::desc(
+        "Base file path for the interactive mode. The incoming filename should "
+        "have the name <inliner-interactive-channel-base>.in, while the "
+        "outgoing name should be <inliner-interactive-channel-base>.out"));
+
 #if defined(LLVM_HAVE_TF_AOT_INLINERSIZEMODEL)
-#include "llvm/Analysis/ReleaseModeModelRunner.h"
 // codegen-ed file
 #include "InlinerSizeModel.h" // NOLINT
+using CompiledModelType = llvm::InlinerSizeModel;
+#else
+using CompiledModelType = NoopSavedModelImpl;
+#endif
 
 std::unique_ptr<InlineAdvisor>
 llvm::getReleaseModeAdvisor(Module &M, ModuleAnalysisManager &MAM) {
-  auto AOTRunner =
-      std::make_unique<ReleaseModeModelRunner<llvm::InlinerSizeModel>>(
-          M.getContext(), FeatureMap, DecisionName);
+  if (!llvm::isEmbeddedModelEvaluatorValid<CompiledModelType>() &&
+      InteractiveChannelBaseName.empty())
+    return nullptr;
+  std::unique_ptr<MLModelRunner> AOTRunner;
+  if (InteractiveChannelBaseName.empty())
+    AOTRunner = std::make_unique<ReleaseModeModelRunner<CompiledModelType>>(
+        M.getContext(), FeatureMap, DecisionName);
+  else
+    AOTRunner = std::make_unique<InteractiveModelRunner>(
+        M.getContext(), FeatureMap, InlineDecisionSpec,
+        InteractiveChannelBaseName + ".out",
+        InteractiveChannelBaseName + ".in");
   return std::make_unique<MLInlineAdvisor>(M, MAM, std::move(AOTRunner));
 }
-#endif
 
 #define DEBUG_TYPE "inline-ml"
 
@@ -59,7 +79,7 @@
     cl::init(false));
 
 // clang-format off
-const std::array<TensorSpec, NumberOfFeatures> llvm::FeatureMap{
+const std::vector<TensorSpec> llvm::FeatureMap{
 #define POPULATE_NAMES(_, NAME) TensorSpec::createSpec<int64_t>(NAME, {1} ),
 // InlineCost features - these must come first
   INLINE_COST_FEATURE_ITERATOR(POPULATE_NAMES)
@@ -73,6 +93,8 @@
 // clang-format on
 
 const char *const llvm::DecisionName = "inlining_decision";
+const TensorSpec llvm::InlineDecisionSpec =
+    TensorSpec::createSpec<int64_t>(DecisionName, {1});
 const char *const llvm::DefaultDecisionName = "inlining_default";
 const char *const llvm::RewardName = "delta_size";
 
@@ -94,7 +116,7 @@
       CG(MAM.getResult<LazyCallGraphAnalysis>(M)),
       InitialIRSize(getModuleIRSize()), CurrentIRSize(InitialIRSize) {
   assert(ModelRunner);
-
+  ModelRunner->switchContext("");
   // Extract the 'call site height' feature - the position of a call site
   // relative to the farthest statically reachable SCC node. We don't mutate
   // this value while inlining happens. Empirically, this feature proved
diff --git a/llvm/lib/Analysis/models/interactive_host.py b/llvm/lib/Analysis/models/interactive_host.py
new file mode 100644
--- /dev/null
+++ b/llvm/lib/Analysis/models/interactive_host.py
@@ -0,0 +1,79 @@
+"""Utility for testing InteractiveModelRunner.
+
+Use it from pass-specific tests by providing a main .py which calls this library's
+`run_interactive` with an appropriate callback to provide advice.
+
+From .ll tests, just call the above-mentioned main as a prefix to the opt/llc
+invocation (with the appropriate flags enabling the interactive mode)
+
+Examples:
+test/Transforms/Inline/ML/interactive-mode.ll
+test/CodeGen/MLRegalloc/interactive-mode.ll
+"""
+
+import ctypes
+import log_reader
+import io
+import math
+import os
+import subprocess
+from typing import BinaryIO, Callable
+
+
+def send(f: io.BufferedWriter, value: int | float, spec: log_reader.TensorSpec):
+  """Send the `value` - currently just a scalar - formatted as per `spec`."""
+
+  # just int64 for now
+  assert (spec.element_type == ctypes.c_int64)
+  to_send = ctypes.c_int64(int(value))
+  assert f.write(bytes(to_send)) == ctypes.sizeof(
+      spec.element_type) * math.prod(spec.shape)
+  f.flush()
+
+
+def run_interactive(temp_rootname: str,
+                    make_response: Callable[[list[log_reader.TensorValue]],
+                                            int | float],
+                    process_and_args: list[str]):
+  """Host the compiler.
+  Args:
+    temp_rootname: the base file name from which to construct the 2 pipes for
+    communicating with the compiler.
+    make_response: a function that, given the current tensor values, provides a
+    response.
+    process_and_args: the full commandline for the compiler. It it assumed it
+    contains a flag poiting to `temp_rootname` so that the InteractiveModeRunner
+    would attempt communication on the same pair as this function opens.
+
+  This function sets up the communication with the compiler - via 2 files named
+  `temp_rootname`.in and `temp_rootname`.out - prints out the received features,
+  and sends back to the compiler an advice (which it gets from `make_response`).
+  It's used for testing, and also to showcase how to set up communication in an
+  interactive ML ("gym") environment.
+  """
+  to_compiler = temp_rootname + ".in"
+  from_compiler = temp_rootname + ".out"
+  try:
+    os.mkfifo(to_compiler, 0o666)
+    os.mkfifo(from_compiler, 0o666)
+    compiler_proc = subprocess.Popen(process_and_args)
+    with io.BufferedWriter(io.FileIO(to_compiler, 'wb')) as tc:
+      with io.BufferedReader(io.FileIO(from_compiler, 'rb')) as fc:
+        tensor_specs, _, advice_spec = log_reader.read_header(fc)
+        context = None
+        while compiler_proc.poll() is None and (next_event := fc.readline()):
+          last_context, observation_id, features, _ = log_reader.read_one_observation(
+              context, next_event, fc, tensor_specs, None)
+          if last_context != context:
+            print(f'context: {last_context}')
+          context = last_context
+          print(f'observation: {observation_id}')
+          tensor_values = []
+          for fv in features:
+            log_reader.pretty_print_tensor_value(fv)
+            tensor_values.append(fv)
+          send(tc, make_response(tensor_values), advice_spec)
+
+  finally:
+    os.unlink(to_compiler)
+    os.unlink(from_compiler)
diff --git a/llvm/lib/CodeGen/MLRegallocEvictAdvisor.cpp b/llvm/lib/CodeGen/MLRegallocEvictAdvisor.cpp
--- a/llvm/lib/CodeGen/MLRegallocEvictAdvisor.cpp
+++ b/llvm/lib/CodeGen/MLRegallocEvictAdvisor.cpp
@@ -13,6 +13,7 @@
 #include "AllocationOrder.h"
 #include "RegAllocEvictionAdvisor.h"
 #include "RegAllocGreedy.h"
+#include "llvm/Analysis/InteractiveModelRunner.h"
 #include "llvm/Analysis/MLModelRunner.h"
 #include "llvm/Analysis/TensorSpec.h"
 #if defined(LLVM_HAVE_TF_AOT_REGALLOCEVICTMODEL) || defined(LLVM_HAVE_TFLITE)
@@ -52,6 +53,14 @@
 using CompiledModelType = NoopSavedModelImpl;
 #endif
 
+static cl::opt<std::string> InteractiveChannelBaseName(
+    "regalloc-evict-interactive-channel-base", cl::Hidden,
+    cl::desc(
+        "Base file path for the interactive mode. The incoming filename should "
+        "have the name <regalloc-evict-interactive-channel-base>.in, while the "
+        "outgoing name should be "
+        "<regalloc-evict-interactive-channel-base>.out"));
+
 // Options that only make sense in development mode
 #ifdef LLVM_HAVE_TFLITE
 #include "RegAllocScore.h"
@@ -213,6 +222,8 @@
 // will be guaranteed to be to a mask == 1 position. Using a macro here to
 // avoid 'not used' warnings (and keep cond compilation to a minimum)
 #define DecisionName "index_to_evict"
+static const TensorSpec DecisionSpec =
+    TensorSpec::createSpec<int64_t>(DecisionName, {1});
 
 // Named features index.
 enum FeatureIDs {
@@ -382,14 +393,21 @@
 
   std::unique_ptr<RegAllocEvictionAdvisor>
   getAdvisor(const MachineFunction &MF, const RAGreedy &RA) override {
-    if (!Runner)
-      Runner = std::make_unique<ReleaseModeModelRunner<CompiledModelType>>(
-          MF.getFunction().getContext(), InputFeatures, DecisionName);
+    if (!Runner) {
+      if (InteractiveChannelBaseName.empty())
+        Runner = std::make_unique<ReleaseModeModelRunner<CompiledModelType>>(
+            MF.getFunction().getContext(), InputFeatures, DecisionName);
+      else
+        Runner = std::make_unique<InteractiveModelRunner>(
+            MF.getFunction().getContext(), InputFeatures, DecisionSpec,
+            InteractiveChannelBaseName + ".out",
+            InteractiveChannelBaseName + ".in");
+    }
     return std::make_unique<MLEvictAdvisor>(
         MF, RA, Runner.get(), getAnalysis<MachineBlockFrequencyInfo>(),
         getAnalysis<MachineLoopInfo>());
   }
-  std::unique_ptr<ReleaseModeModelRunner<CompiledModelType>> Runner;
+  std::unique_ptr<MLModelRunner> Runner;
 };
 
 // ===================================
@@ -398,8 +416,6 @@
 //
 // Features we log
 #ifdef LLVM_HAVE_TFLITE
-static const TensorSpec Output =
-    TensorSpec::createSpec<int64_t>(DecisionName, {1});
 static const TensorSpec Reward = TensorSpec::createSpec<float>("reward", {1});
 
 // Features we bind on the model. The tensor names have a prefix, and we also
@@ -512,7 +528,7 @@
     // We always log the output; in particular, if we're not evaluating, we
     // don't have an output spec json file. That's why we handle the
     // 'normal' output separately.
-    LFS.push_back(Output);
+    LFS.push_back(DecisionSpec);
 
     Log = std::make_unique<Logger>(std::move(OS), LFS, Reward,
                                    /*IncludeReward*/ true);
@@ -557,6 +573,7 @@
       Runner(std::move(Runner)), MBFI(MBFI), Loops(Loops),
       InitialQSize(MLEvictAdvisor::getInitialQueueSize(MF)) {
   assert(this->Runner);
+  Runner->switchContext(MF.getName());
   DoNotNormalize.set(FeatureIDs::mask);
   DoNotNormalize.set(FeatureIDs::is_free);
   DoNotNormalize.set(FeatureIDs::is_hint);
@@ -1134,7 +1151,10 @@
 #endif // #ifdef LLVM_HAVE_TFLITE
 
 RegAllocEvictionAdvisorAnalysis *llvm::createReleaseModeAdvisor() {
-  return new ReleaseModeEvictionAdvisorAnalysis();
+  return llvm::isEmbeddedModelEvaluatorValid<CompiledModelType>() ||
+                 !InteractiveChannelBaseName.empty()
+             ? new ReleaseModeEvictionAdvisorAnalysis()
+             : nullptr;
 }
 
 // In all cases except development mode, we don't need scoring.
diff --git a/llvm/lib/CodeGen/MLRegallocPriorityAdvisor.cpp b/llvm/lib/CodeGen/MLRegallocPriorityAdvisor.cpp
--- a/llvm/lib/CodeGen/MLRegallocPriorityAdvisor.cpp
+++ b/llvm/lib/CodeGen/MLRegallocPriorityAdvisor.cpp
@@ -14,6 +14,7 @@
 #include "RegAllocGreedy.h"
 #include "RegAllocPriorityAdvisor.h"
 #include "llvm/Analysis/AliasAnalysis.h"
+#include "llvm/Analysis/InteractiveModelRunner.h"
 #include "llvm/Analysis/MLModelRunner.h"
 #include "llvm/Analysis/ReleaseModeModelRunner.h"
 #include "llvm/Analysis/TensorSpec.h"
@@ -40,6 +41,16 @@
 
 using namespace llvm;
 
+static cl::opt<std::string> InteractiveChannelBaseName(
+    "regalloc-priority-interactive-channel-base", cl::Hidden,
+    cl::desc(
+        "Base file path for the interactive mode. The incoming filename should "
+        "have the name <regalloc-priority-interactive-channel-base>.in, while "
+        "the outgoing name should be "
+        "<regalloc-priority-interactive-channel-base>.out"));
+
+using CompiledModelType = NoopSavedModelImpl;
+
 // Options that only make sense in development mode
 #ifdef LLVM_HAVE_TFLITE
 #include "RegAllocScore.h"
@@ -65,6 +76,9 @@
   M(float, weight, PerLiveRangeShape, "weight")
 
 #define DecisionName "priority"
+static const TensorSpec DecisionSpec =
+    TensorSpec::createSpec<float>(DecisionName, {1});
+
 
 // Named features index.
 enum FeatureIDs {
@@ -125,13 +139,20 @@
 
   std::unique_ptr<RegAllocPriorityAdvisor>
   getAdvisor(const MachineFunction &MF, const RAGreedy &RA) override {
-    if (!Runner)
-      Runner = std::make_unique<ReleaseModeModelRunner<NoopSavedModelImpl>>(
-          MF.getFunction().getContext(), InputFeatures, DecisionName);
+    if (!Runner) {
+      if (InteractiveChannelBaseName.empty())
+        Runner = std::make_unique<ReleaseModeModelRunner<CompiledModelType>>(
+            MF.getFunction().getContext(), InputFeatures, DecisionName);
+      else
+        Runner = std::make_unique<InteractiveModelRunner>(
+            MF.getFunction().getContext(), InputFeatures, DecisionSpec,
+            InteractiveChannelBaseName + ".out",
+            InteractiveChannelBaseName + ".in");
+    }
     return std::make_unique<MLPriorityAdvisor>(
         MF, RA, &getAnalysis<SlotIndexes>(), Runner.get());
   }
-  std::unique_ptr<ReleaseModeModelRunner<NoopSavedModelImpl>> Runner;
+  std::unique_ptr<MLModelRunner> Runner;
 };
 
 // ===================================
@@ -140,9 +161,6 @@
 //
 // Features we log
 #ifdef LLVM_HAVE_TFLITE
-
-static const TensorSpec Output =
-    TensorSpec::createSpec<float>(DecisionName, {1});
 static const TensorSpec Reward = TensorSpec::createSpec<float>("reward", {1});
 
 #define _DECL_TRAIN_FEATURES(type, name, shape, _)                             \
@@ -231,7 +249,7 @@
     // We always log the output; in particular, if we're not evaluating, we
     // don't have an output spec json file. That's why we handle the
     // 'normal' output separately.
-    LFS.push_back(Output);
+    LFS.push_back(DecisionSpec);
 
     Log = std::make_unique<Logger>(std::move(OS), LFS, Reward,
                                    /*IncludeReward*/ true);
@@ -258,7 +276,10 @@
 } // namespace llvm
 
 RegAllocPriorityAdvisorAnalysis *llvm::createReleaseModePriorityAdvisor() {
-  return new ReleaseModePriorityAdvisorAnalysis();
+  return llvm::isEmbeddedModelEvaluatorValid<CompiledModelType>() ||
+                 !InteractiveChannelBaseName.empty()
+             ? new ReleaseModePriorityAdvisorAnalysis()
+             : nullptr;
 }
 
 MLPriorityAdvisor::MLPriorityAdvisor(const MachineFunction &MF,
@@ -268,6 +289,7 @@
     : RegAllocPriorityAdvisor(MF, RA, Indexes), DefaultAdvisor(MF, RA, Indexes),
       Runner(std::move(Runner)) {
   assert(this->Runner);
+  Runner->switchContext(MF.getName());
 }
 
 float MLPriorityAdvisor::getPriorityImpl(const LiveInterval &LI) const {
diff --git a/llvm/lib/CodeGen/RegAllocEvictionAdvisor.cpp b/llvm/lib/CodeGen/RegAllocEvictionAdvisor.cpp
--- a/llvm/lib/CodeGen/RegAllocEvictionAdvisor.cpp
+++ b/llvm/lib/CodeGen/RegAllocEvictionAdvisor.cpp
@@ -100,9 +100,7 @@
 #endif
     break;
   case RegAllocEvictionAdvisorAnalysis::AdvisorMode::Release:
-#if defined(LLVM_HAVE_TF_AOT)
     Ret = createReleaseModeAdvisor();
-#endif
     break;
   }
   if (Ret)
diff --git a/llvm/lib/CodeGen/RegAllocPriorityAdvisor.cpp b/llvm/lib/CodeGen/RegAllocPriorityAdvisor.cpp
--- a/llvm/lib/CodeGen/RegAllocPriorityAdvisor.cpp
+++ b/llvm/lib/CodeGen/RegAllocPriorityAdvisor.cpp
@@ -81,9 +81,7 @@
 #endif
     break;
   case RegAllocPriorityAdvisorAnalysis::AdvisorMode::Release:
-#if defined(LLVM_HAVE_TF_AOT_REGALLOCPRIORITYMODEL)
     Ret = createReleaseModePriorityAdvisor();
-#endif
     break;
   }
   if (Ret)
diff --git a/llvm/test/CodeGen/MLRegalloc/Inputs/interactive_main.py b/llvm/test/CodeGen/MLRegalloc/Inputs/interactive_main.py
new file mode 100644
--- /dev/null
+++ b/llvm/test/CodeGen/MLRegalloc/Inputs/interactive_main.py
@@ -0,0 +1,28 @@
+import log_reader
+import interactive_host
+import sys
+
+
+def main(args):
+  # this advisor just picks the first legal register to evict, which is
+  # identifiable by the "mask" feature
+  class Advisor:
+    to_return = False
+
+    def advice(self, tensor_values: list[log_reader.TensorValue]):
+      for tv in tensor_values:
+        if tv.spec().name != 'mask':
+          continue
+        for i, v in enumerate(tv):
+          if v == 1:
+            return i
+      # i.e. invalid:
+      return -1
+
+
+  a = Advisor()
+  interactive_host.run_interactive(args[0], a.advice, args[1:])
+
+
+if __name__ == '__main__':
+  main(sys.argv[1:])
diff --git a/llvm/test/CodeGen/MLRegalloc/interactive-mode.ll b/llvm/test/CodeGen/MLRegalloc/interactive-mode.ll
new file mode 100644
--- /dev/null
+++ b/llvm/test/CodeGen/MLRegalloc/interactive-mode.ll
@@ -0,0 +1,23 @@
+; RUN: rm -rf %t.rundir
+; RUN: rm -rf %t.channel-basename.*
+; RUN: mkdir %t.rundir
+; RUN: cp %S/../../../lib/Analysis/models/log_reader.py %t.rundir
+; RUN: cp %S/../../../lib/Analysis/models/interactive_host.py %t.rundir
+; RUN: cp %S/Inputs/interactive_main.py %t.rundir
+; RUN: %python %t.rundir/interactive_main.py %t.channel-basename \
+; RUN:    llc -mtriple=x86_64-linux-unknown -regalloc=greedy -regalloc-enable-advisor=release -interactive-model-runner-echo-reply \
+; RUN:    -regalloc-evict-interactive-channel-base=%t.channel-basename %S/Inputs/two-large-fcts.ll -o /dev/null 2>%t.err | FileCheck %s
+; RUN: cat %t.err | FileCheck %s --check-prefix=ADVICE
+
+;; Make sure we see both contexts. Also sanity-check that the advice is the
+;; expected one - the index of the first legal register
+; CHECK: context: SyFgets
+; CHECK-NEXT: observation: 0
+; CHECK-NEXT: mask: 0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
+; CHECK: observation: 1
+; CHECK-NEXT: mask: 0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1
+; CHECK: context: SyFgetsCopy
+; CHECK-NEXT: observation: 0
+
+; ADVICE: index_to_evict: 9
+; ADVICE: index_to_evict: 10
diff --git a/llvm/test/Transforms/Inline/ML/Inputs/interactive_main.py b/llvm/test/Transforms/Inline/ML/Inputs/interactive_main.py
new file mode 100644
--- /dev/null
+++ b/llvm/test/Transforms/Inline/ML/Inputs/interactive_main.py
@@ -0,0 +1,21 @@
+import interactive_host
+import sys
+
+
+def main(args):
+
+  class Advisor:
+    to_return = False
+
+    def advice(self, _):
+      # The adice will be a sequence of yes/no/yes/no/...
+      # see ../interactive-mode.ll
+      self.to_return = not self.to_return
+      return int(self.to_return)
+
+  a = Advisor()
+  interactive_host.run_interactive(args[0], a.advice, args[1:])
+
+
+if __name__ == '__main__':
+  main(sys.argv[1:])
diff --git a/llvm/test/Transforms/Inline/ML/interactive-mode.ll b/llvm/test/Transforms/Inline/ML/interactive-mode.ll
new file mode 100644
--- /dev/null
+++ b/llvm/test/Transforms/Inline/ML/interactive-mode.ll
@@ -0,0 +1,28 @@
+; RUN: rm -rf %t.rundir
+; RUN: rm -rf %t.channel-basename.*
+; RUN: mkdir %t.rundir
+; RUN: cp %S/../../../../lib/Analysis/models/log_reader.py %t.rundir
+; RUN: cp %S/../../../../lib/Analysis/models/interactive_host.py %t.rundir
+; RUN: cp %S/Inputs/interactive_main.py %t.rundir
+; RUN: %python %t.rundir/interactive_main.py %t.channel-basename \
+; RUN:    opt -passes=scc-oz-module-inliner -interactive-model-runner-echo-reply \
+; RUN:    -enable-ml-inliner=release --inliner-interactive-channel-base=%t.channel-basename %S/Inputs/test-module.ll -S -o /dev/null 2>%t.err | FileCheck %s
+; RUN: cat %t.err | FileCheck %s --check-prefix=ADVICE
+
+;; It'd be nice if we had stdout and stderr interleaved, but we don't, so
+;; let's just check the features have non-zero values, and that we see as many
+;; advices as observations, and that the advices flip-flop as intended.
+; CHECK: context:
+; CHECK-NEXT: observation: 0
+; CHECK-NEXT: sroa_savings: 0
+; CHECK:      unsimplified_common_instructions: 5
+; CHECK:      callee_users: 3
+; CHECK:      observation: 5
+; CHECK-NOT:  observation: 6
+
+; ADVICE:     inlining_decision: 1
+; ADVICE:     inlining_decision: 0
+; ADVICE:     inlining_decision: 1
+; ADVICE:     inlining_decision: 0
+; ADVICE:     inlining_decision: 1
+; ADVICE:     inlining_decision: 0