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diff --git a/extensions/functions/dependencies/tensorflow/models/xor_model.tflite b/extensions/functions/dependencies/tensorflow/models/xor_model.tflite
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diff --git a/extensions/functions/dependencies/tensorflow/tensorflow/lite/builtin_ops.h b/extensions/functions/dependencies/tensorflow/tensorflow/lite/builtin_ops.h
new file mode 100644
index 0000000000..c4e2907ffa
--- /dev/null
+++ b/extensions/functions/dependencies/tensorflow/tensorflow/lite/builtin_ops.h
@@ -0,0 +1,160 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_BUILTIN_OPS_H_
+#define TENSORFLOW_LITE_BUILTIN_OPS_H_
+
+// DO NOT EDIT MANUALLY: This file is automatically generated by
+// `schema/builtin_ops_header/generator.cc`.
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// The enum for builtin operators.
+// Note: CUSTOM and DELEGATE are 2 special ops which are not real built-in ops.
+typedef enum {
+  kTfLiteBuiltinAdd = 0,
+  kTfLiteBuiltinAveragePool2d = 1,
+  kTfLiteBuiltinConcatenation = 2,
+  kTfLiteBuiltinConv2d = 3,
+  kTfLiteBuiltinDepthwiseConv2d = 4,
+  kTfLiteBuiltinDepthToSpace = 5,
+  kTfLiteBuiltinDequantize = 6,
+  kTfLiteBuiltinEmbeddingLookup = 7,
+  kTfLiteBuiltinFloor = 8,
+  kTfLiteBuiltinFullyConnected = 9,
+  kTfLiteBuiltinHashtableLookup = 10,
+  kTfLiteBuiltinL2Normalization = 11,
+  kTfLiteBuiltinL2Pool2d = 12,
+  kTfLiteBuiltinLocalResponseNormalization = 13,
+  kTfLiteBuiltinLogistic = 14,
+  kTfLiteBuiltinLshProjection = 15,
+  kTfLiteBuiltinLstm = 16,
+  kTfLiteBuiltinMaxPool2d = 17,
+  kTfLiteBuiltinMul = 18,
+  kTfLiteBuiltinRelu = 19,
+  kTfLiteBuiltinReluN1To1 = 20,
+  kTfLiteBuiltinRelu6 = 21,
+  kTfLiteBuiltinReshape = 22,
+  kTfLiteBuiltinResizeBilinear = 23,
+  kTfLiteBuiltinRnn = 24,
+  kTfLiteBuiltinSoftmax = 25,
+  kTfLiteBuiltinSpaceToDepth = 26,
+  kTfLiteBuiltinSvdf = 27,
+  kTfLiteBuiltinTanh = 28,
+  kTfLiteBuiltinConcatEmbeddings = 29,
+  kTfLiteBuiltinSkipGram = 30,
+  kTfLiteBuiltinCall = 31,
+  kTfLiteBuiltinCustom = 32,
+  kTfLiteBuiltinEmbeddingLookupSparse = 33,
+  kTfLiteBuiltinPad = 34,
+  kTfLiteBuiltinUnidirectionalSequenceRnn = 35,
+  kTfLiteBuiltinGather = 36,
+  kTfLiteBuiltinBatchToSpaceNd = 37,
+  kTfLiteBuiltinSpaceToBatchNd = 38,
+  kTfLiteBuiltinTranspose = 39,
+  kTfLiteBuiltinMean = 40,
+  kTfLiteBuiltinSub = 41,
+  kTfLiteBuiltinDiv = 42,
+  kTfLiteBuiltinSqueeze = 43,
+  kTfLiteBuiltinUnidirectionalSequenceLstm = 44,
+  kTfLiteBuiltinStridedSlice = 45,
+  kTfLiteBuiltinBidirectionalSequenceRnn = 46,
+  kTfLiteBuiltinExp = 47,
+  kTfLiteBuiltinTopkV2 = 48,
+  kTfLiteBuiltinSplit = 49,
+  kTfLiteBuiltinLogSoftmax = 50,
+  kTfLiteBuiltinDelegate = 51,
+  kTfLiteBuiltinBidirectionalSequenceLstm = 52,
+  kTfLiteBuiltinCast = 53,
+  kTfLiteBuiltinPrelu = 54,
+  kTfLiteBuiltinMaximum = 55,
+  kTfLiteBuiltinArgMax = 56,
+  kTfLiteBuiltinMinimum = 57,
+  kTfLiteBuiltinLess = 58,
+  kTfLiteBuiltinNeg = 59,
+  kTfLiteBuiltinPadv2 = 60,
+  kTfLiteBuiltinGreater = 61,
+  kTfLiteBuiltinGreaterEqual = 62,
+  kTfLiteBuiltinLessEqual = 63,
+  kTfLiteBuiltinSelect = 64,
+  kTfLiteBuiltinSlice = 65,
+  kTfLiteBuiltinSin = 66,
+  kTfLiteBuiltinTransposeConv = 67,
+  kTfLiteBuiltinSparseToDense = 68,
+  kTfLiteBuiltinTile = 69,
+  kTfLiteBuiltinExpandDims = 70,
+  kTfLiteBuiltinEqual = 71,
+  kTfLiteBuiltinNotEqual = 72,
+  kTfLiteBuiltinLog = 73,
+  kTfLiteBuiltinSum = 74,
+  kTfLiteBuiltinSqrt = 75,
+  kTfLiteBuiltinRsqrt = 76,
+  kTfLiteBuiltinShape = 77,
+  kTfLiteBuiltinPow = 78,
+  kTfLiteBuiltinArgMin = 79,
+  kTfLiteBuiltinFakeQuant = 80,
+  kTfLiteBuiltinReduceProd = 81,
+  kTfLiteBuiltinReduceMax = 82,
+  kTfLiteBuiltinPack = 83,
+  kTfLiteBuiltinLogicalOr = 84,
+  kTfLiteBuiltinOneHot = 85,
+  kTfLiteBuiltinLogicalAnd = 86,
+  kTfLiteBuiltinLogicalNot = 87,
+  kTfLiteBuiltinUnpack = 88,
+  kTfLiteBuiltinReduceMin = 89,
+  kTfLiteBuiltinFloorDiv = 90,
+  kTfLiteBuiltinReduceAny = 91,
+  kTfLiteBuiltinSquare = 92,
+  kTfLiteBuiltinZerosLike = 93,
+  kTfLiteBuiltinFill = 94,
+  kTfLiteBuiltinFloorMod = 95,
+  kTfLiteBuiltinRange = 96,
+  kTfLiteBuiltinResizeNearestNeighbor = 97,
+  kTfLiteBuiltinLeakyRelu = 98,
+  kTfLiteBuiltinSquaredDifference = 99,
+  kTfLiteBuiltinMirrorPad = 100,
+  kTfLiteBuiltinAbs = 101,
+  kTfLiteBuiltinSplitV = 102,
+  kTfLiteBuiltinUnique = 103,
+  kTfLiteBuiltinCeil = 104,
+  kTfLiteBuiltinReverseV2 = 105,
+  kTfLiteBuiltinAddN = 106,
+  kTfLiteBuiltinGatherNd = 107,
+  kTfLiteBuiltinCos = 108,
+  kTfLiteBuiltinWhere = 109,
+  kTfLiteBuiltinRank = 110,
+  kTfLiteBuiltinElu = 111,
+  kTfLiteBuiltinReverseSequence = 112,
+  kTfLiteBuiltinMatrixDiag = 113,
+  kTfLiteBuiltinQuantize = 114,
+  kTfLiteBuiltinMatrixSetDiag = 115,
+  kTfLiteBuiltinRound = 116,
+  kTfLiteBuiltinHardSwish = 117,
+  kTfLiteBuiltinIf = 118,
+  kTfLiteBuiltinWhile = 119,
+  kTfLiteBuiltinNonMaxSuppressionV4 = 120,
+  kTfLiteBuiltinNonMaxSuppressionV5 = 121,
+  kTfLiteBuiltinScatterNd = 122,
+  kTfLiteBuiltinSelectV2 = 123,
+  kTfLiteBuiltinDensify = 124,
+  kTfLiteBuiltinSegmentSum = 125,
+} TfLiteBuiltinOperator;
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+#endif  // TENSORFLOW_LITE_BUILTIN_OPS_H_
diff --git a/extensions/functions/dependencies/tensorflow/tensorflow/lite/c/c_api.h b/extensions/functions/dependencies/tensorflow/tensorflow/lite/c/c_api.h
new file mode 100644
index 0000000000..754fc3b8bb
--- /dev/null
+++ b/extensions/functions/dependencies/tensorflow/tensorflow/lite/c/c_api.h
@@ -0,0 +1,269 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_C_C_API_H_
+#define TENSORFLOW_LITE_C_C_API_H_
+
+#include <stdarg.h>
+#include <stdint.h>
+
+#include "common.h"
+
+// --------------------------------------------------------------------------
+/// C API for TensorFlow Lite.
+///
+/// The API leans towards simplicity and uniformity instead of convenience, as
+/// most usage will be by language-specific wrappers. It provides largely the
+/// same set of functionality as that of the C++ TensorFlow Lite `Interpreter`
+/// API, but is useful for shared libraries where having a stable ABI boundary
+/// is important.
+///
+/// Conventions:
+/// * We use the prefix TfLite for everything in the API.
+/// * size_t is used to represent byte sizes of objects that are
+///   materialized in the address space of the calling process.
+/// * int is used as an index into arrays.
+///
+/// Usage:
+/// <pre><code>
+/// // Create the model and interpreter options.
+/// TfLiteModel* model = TfLiteModelCreateFromFile("/path/to/model.tflite");
+/// TfLiteInterpreterOptions* options = TfLiteInterpreterOptionsCreate();
+/// TfLiteInterpreterOptionsSetNumThreads(options, 2);
+///
+/// // Create the interpreter.
+/// TfLiteInterpreter* interpreter = TfLiteInterpreterCreate(model, options);
+///
+/// // Allocate tensors and populate the input tensor data.
+/// TfLiteInterpreterAllocateTensors(interpreter);
+/// TfLiteTensor* input_tensor =
+///     TfLiteInterpreterGetInputTensor(interpreter, 0);
+/// TfLiteTensorCopyFromBuffer(input_tensor, input.data(),
+///                            input.size() * sizeof(float));
+///
+/// // Execute inference.
+/// TfLiteInterpreterInvoke(interpreter);
+///
+/// // Extract the output tensor data.
+/// const TfLiteTensor* output_tensor =
+//      TfLiteInterpreterGetOutputTensor(interpreter, 0);
+/// TfLiteTensorCopyToBuffer(output_tensor, output.data(),
+///                          output.size() * sizeof(float));
+///
+/// // Dispose of the model and interpreter objects.
+/// TfLiteInterpreterDelete(interpreter);
+/// TfLiteInterpreterOptionsDelete(options);
+/// TfLiteModelDelete(model);
+
+#ifdef SWIG
+#define TFL_CAPI_EXPORT
+#else
+#if defined(_WIN32)
+#ifdef TFL_COMPILE_LIBRARY
+#define TFL_CAPI_EXPORT __declspec(dllexport)
+#else
+#define TFL_CAPI_EXPORT __declspec(dllimport)
+#endif  // TFL_COMPILE_LIBRARY
+#else
+#define TFL_CAPI_EXPORT __attribute__((visibility("default")))
+#endif  // _WIN32
+#endif  // SWIG
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// --------------------------------------------------------------------------
+// TfLiteVersion returns a string describing version information of the
+// TensorFlow Lite library. TensorFlow Lite uses semantic versioning.
+TFL_CAPI_EXPORT extern const char* TfLiteVersion(void);
+
+// --------------------------------------------------------------------------
+// TfLiteModel wraps a loaded TensorFlow Lite model.
+typedef struct TfLiteModel TfLiteModel;
+
+// Returns a model from the provided buffer, or null on failure.
+TFL_CAPI_EXPORT extern TfLiteModel* TfLiteModelCreate(const void* model_data,
+                                                      size_t model_size);
+
+// Returns a model from the provided file, or null on failure.
+TFL_CAPI_EXPORT extern TfLiteModel* TfLiteModelCreateFromFile(
+    const char* model_path);
+
+// Destroys the model instance.
+TFL_CAPI_EXPORT extern void TfLiteModelDelete(TfLiteModel* model);
+
+// --------------------------------------------------------------------------
+// TfLiteInterpreterOptions allows customized interpreter configuration.
+typedef struct TfLiteInterpreterOptions TfLiteInterpreterOptions;
+
+// Returns a new interpreter options instances.
+TFL_CAPI_EXPORT extern TfLiteInterpreterOptions*
+TfLiteInterpreterOptionsCreate();
+
+// Destroys the interpreter options instance.
+TFL_CAPI_EXPORT extern void TfLiteInterpreterOptionsDelete(
+    TfLiteInterpreterOptions* options);
+
+// Sets the number of CPU threads to use for the interpreter.
+TFL_CAPI_EXPORT extern void TfLiteInterpreterOptionsSetNumThreads(
+    TfLiteInterpreterOptions* options, int32_t num_threads);
+
+// Adds a delegate to be applied during `TfLiteInterpreter` creation.
+//
+// If delegate application fails, interpreter creation will also fail with an
+// associated error logged.
+//
+// NOTE: The caller retains ownership of the delegate and should ensure that it
+// remains valid for the duration of any created interpreter's lifetime.
+TFL_CAPI_EXPORT extern void TfLiteInterpreterOptionsAddDelegate(
+    TfLiteInterpreterOptions* options, TfLiteDelegate* delegate);
+
+// Sets a custom error reporter for interpreter execution.
+//
+// * `reporter` takes the provided `user_data` object, as well as a C-style
+//   format string and arg list (see also vprintf).
+// * `user_data` is optional. If provided, it is owned by the client and must
+//   remain valid for the duration of the interpreter lifetime.
+TFL_CAPI_EXPORT extern void TfLiteInterpreterOptionsSetErrorReporter(
+    TfLiteInterpreterOptions* options,
+    void (*reporter)(void* user_data, const char* format, va_list args),
+    void* user_data);
+
+// --------------------------------------------------------------------------
+// TfLiteInterpreter provides inference from a provided model.
+typedef struct TfLiteInterpreter TfLiteInterpreter;
+
+// Returns a new interpreter using the provided model and options, or null on
+// failure.
+//
+// * `model` must be a valid model instance. The caller retains ownership of the
+//   object, and can destroy it immediately after creating the interpreter; the
+//   interpreter will maintain its own reference to the underlying model data.
+// * `optional_options` may be null. The caller retains ownership of the object,
+//   and can safely destroy it immediately after creating the interpreter.
+//
+// NOTE: The client *must* explicitly allocate tensors before attempting to
+// access input tensor data or invoke the interpreter.
+TFL_CAPI_EXPORT extern TfLiteInterpreter* TfLiteInterpreterCreate(
+    const TfLiteModel* model, const TfLiteInterpreterOptions* optional_options);
+
+// Destroys the interpreter.
+TFL_CAPI_EXPORT extern void TfLiteInterpreterDelete(
+    TfLiteInterpreter* interpreter);
+
+// Returns the number of input tensors associated with the model.
+TFL_CAPI_EXPORT extern int32_t TfLiteInterpreterGetInputTensorCount(
+    const TfLiteInterpreter* interpreter);
+
+// Returns the tensor associated with the input index.
+// REQUIRES: 0 <= input_index < TfLiteInterpreterGetInputTensorCount(tensor)
+TFL_CAPI_EXPORT extern TfLiteTensor* TfLiteInterpreterGetInputTensor(
+    const TfLiteInterpreter* interpreter, int32_t input_index);
+
+// Resizes the specified input tensor.
+//
+// NOTE: After a resize, the client *must* explicitly allocate tensors before
+// attempting to access the resized tensor data or invoke the interpreter.
+// REQUIRES: 0 <= input_index < TfLiteInterpreterGetInputTensorCount(tensor)
+TFL_CAPI_EXPORT extern TfLiteStatus TfLiteInterpreterResizeInputTensor(
+    TfLiteInterpreter* interpreter, int32_t input_index, const int* input_dims,
+    int32_t input_dims_size);
+
+// Updates allocations for all tensors, resizing dependent tensors using the
+// specified input tensor dimensionality.
+//
+// This is a relatively expensive operation, and need only be called after
+// creating the graph and/or resizing any inputs.
+TFL_CAPI_EXPORT extern TfLiteStatus TfLiteInterpreterAllocateTensors(
+    TfLiteInterpreter* interpreter);
+
+// Runs inference for the loaded graph.
+//
+// NOTE: It is possible that the interpreter is not in a ready state to
+// evaluate (e.g., if a ResizeInputTensor() has been performed without a call to
+// AllocateTensors()).
+TFL_CAPI_EXPORT extern TfLiteStatus TfLiteInterpreterInvoke(
+    TfLiteInterpreter* interpreter);
+
+// Returns the number of output tensors associated with the model.
+TFL_CAPI_EXPORT extern int32_t TfLiteInterpreterGetOutputTensorCount(
+    const TfLiteInterpreter* interpreter);
+
+// Returns the tensor associated with the output index.
+// REQUIRES: 0 <= input_index < TfLiteInterpreterGetOutputTensorCount(tensor)
+//
+// NOTE: The shape and underlying data buffer for output tensors may be not
+// be available until after the output tensor has been both sized and allocated.
+// In general, best practice is to interact with the output tensor *after*
+// calling TfLiteInterpreterInvoke().
+TFL_CAPI_EXPORT extern const TfLiteTensor* TfLiteInterpreterGetOutputTensor(
+    const TfLiteInterpreter* interpreter, int32_t output_index);
+
+// --------------------------------------------------------------------------
+// TfLiteTensor wraps data associated with a graph tensor.
+//
+// Note that, while the TfLiteTensor struct is not currently opaque, and its
+// fields can be accessed directly, these methods are still convenient for
+// language bindings. In the future the tensor struct will likely be made opaque
+// in the public API.
+
+// Returns the type of a tensor element.
+TFL_CAPI_EXPORT extern TfLiteType TfLiteTensorType(const TfLiteTensor* tensor);
+
+// Returns the number of dimensions that the tensor has.
+TFL_CAPI_EXPORT extern int32_t TfLiteTensorNumDims(const TfLiteTensor* tensor);
+
+// Returns the length of the tensor in the "dim_index" dimension.
+// REQUIRES: 0 <= dim_index < TFLiteTensorNumDims(tensor)
+TFL_CAPI_EXPORT extern int32_t TfLiteTensorDim(const TfLiteTensor* tensor,
+                                               int32_t dim_index);
+
+// Returns the size of the underlying data in bytes.
+TFL_CAPI_EXPORT extern size_t TfLiteTensorByteSize(const TfLiteTensor* tensor);
+
+// Returns a pointer to the underlying data buffer.
+//
+// NOTE: The result may be null if tensors have not yet been allocated, e.g.,
+// if the Tensor has just been created or resized and `TfLiteAllocateTensors()`
+// has yet to be called, or if the output tensor is dynamically sized and the
+// interpreter hasn't been invoked.
+TFL_CAPI_EXPORT extern void* TfLiteTensorData(const TfLiteTensor* tensor);
+
+// Returns the (null-terminated) name of the tensor.
+TFL_CAPI_EXPORT extern const char* TfLiteTensorName(const TfLiteTensor* tensor);
+
+// Returns the parameters for asymmetric quantization. The quantization
+// parameters are only valid when the tensor type is `kTfLiteUInt8` and the
+// `scale != 0`. Quantized values can be converted back to float using:
+//    real_value = scale * (quantized_value - zero_point);
+TFL_CAPI_EXPORT extern TfLiteQuantizationParams TfLiteTensorQuantizationParams(
+    const TfLiteTensor* tensor);
+
+// Copies from the provided input buffer into the tensor's buffer.
+// REQUIRES: input_data_size == TfLiteTensorByteSize(tensor)
+TFL_CAPI_EXPORT extern TfLiteStatus TfLiteTensorCopyFromBuffer(
+    TfLiteTensor* tensor, const void* input_data, size_t input_data_size);
+
+// Copies to the provided output buffer from the tensor's buffer.
+// REQUIRES: output_data_size == TfLiteTensorByteSize(tensor)
+TFL_CAPI_EXPORT extern TfLiteStatus TfLiteTensorCopyToBuffer(
+    const TfLiteTensor* output_tensor, void* output_data,
+    size_t output_data_size);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_C_C_API_H_
diff --git a/extensions/functions/dependencies/tensorflow/tensorflow/lite/c/c_api_experimental.h b/extensions/functions/dependencies/tensorflow/tensorflow/lite/c/c_api_experimental.h
new file mode 100644
index 0000000000..a647e32b47
--- /dev/null
+++ b/extensions/functions/dependencies/tensorflow/tensorflow/lite/c/c_api_experimental.h
@@ -0,0 +1,56 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_C_C_API_EXPERIMENTAL_H_
+#define TENSORFLOW_LITE_C_C_API_EXPERIMENTAL_H_
+
+#include "tensorflow/lite/builtin_ops.h"
+#include "tensorflow/lite/c/c_api.h"
+#include "tensorflow/lite/c/common.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// Resets all variable tensors to zero.
+TFL_CAPI_EXPORT extern TfLiteStatus TfLiteInterpreterResetVariableTensors(
+    TfLiteInterpreter* interpreter);
+
+// Adds an op registration for a builtin operator.
+//
+// NOTE: The interpreter will make a copy of `registration` internally, so the
+// caller should ensure that its contents (function pointers, etc...) remain
+// valid for the duration of the interpreter's lifetime. A common practice is
+// making the provided TfLiteRegistration instance static.
+TFL_CAPI_EXPORT void TfLiteInterpreterOptionsAddBuiltinOp(
+    TfLiteInterpreterOptions* options, TfLiteBuiltinOperator op,
+    const TfLiteRegistration* registration, int32_t min_version,
+    int32_t max_version);
+
+// Adds an op registration for a custom operator.
+//
+// NOTE: The interpreter will make a copy of `registration` internally, so the
+// caller should ensure that its contents (function pointers, etc...) remain
+// valid for the duration of any created interpreter's lifetime. A common
+// practice is making the provided TfLiteRegistration instance static.
+TFL_CAPI_EXPORT void TfLiteInterpreterOptionsAddCustomOp(
+    TfLiteInterpreterOptions* options, const char* name,
+    const TfLiteRegistration* registration, int32_t min_version,
+    int32_t max_version);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_C_C_API_EXPERIMENTAL_H_
diff --git a/extensions/functions/dependencies/tensorflow/tensorflow/lite/c/common.h b/extensions/functions/dependencies/tensorflow/tensorflow/lite/c/common.h
new file mode 100644
index 0000000000..eff16783a1
--- /dev/null
+++ b/extensions/functions/dependencies/tensorflow/tensorflow/lite/c/common.h
@@ -0,0 +1,752 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+// This file defines common C types and APIs for implementing operations,
+// delegates and other constructs in TensorFlow Lite. The actual operations and
+// delegtes can be defined using C++, but the interface between the interpreter
+// and the operations are C.
+//
+// Summary of abstractions
+// TF_LITE_ENSURE - Self-sufficient error checking
+// TfLiteStatus - Status reporting
+// TfLiteIntArray - stores tensor shapes (dims),
+// TfLiteContext - allows an op to access the tensors
+// TfLiteTensor - tensor (a multidimensional array)
+// TfLiteNode - a single node or operation
+// TfLiteRegistration - the implementation of a conceptual operation.
+// TfLiteDelegate - allows delegation of nodes to alternative backends.
+//
+// Some abstractions in this file are created and managed by Interpreter.
+
+#ifndef TENSORFLOW_LITE_C_COMMON_H_
+#define TENSORFLOW_LITE_C_COMMON_H_
+
+#include <stdbool.h>
+#include <stddef.h>
+#include <stdint.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+typedef enum TfLiteStatus { kTfLiteOk = 0, kTfLiteError = 1 } TfLiteStatus;
+
+// The list of external context types known to TF Lite. This list exists solely
+// to avoid conflicts and to ensure ops can share the external contexts they
+// need. Access to the external contexts is controlled by one of the
+// corresponding support files.
+typedef enum TfLiteExternalContextType {
+  kTfLiteEigenContext = 0,       // include eigen_support.h to use.
+  kTfLiteGemmLowpContext = 1,    // include gemm_support.h to use.
+  kTfLiteEdgeTpuContext = 2,     // Placeholder for Edge TPU support.
+  kTfLiteCpuBackendContext = 3,  // include cpu_backend_support.h to use.
+  kTfLiteMaxExternalContexts = 4
+} TfLiteExternalContextType;
+
+// Forward declare so dependent structs and methods can reference these types
+// prior to the struct definitions.
+struct TfLiteContext;
+struct TfLiteDelegate;
+struct TfLiteRegistration;
+
+// An external context is a collection of information unrelated to the TF Lite
+// framework, but useful to a subset of the ops. TF Lite knows very little
+// about about the actual contexts, but it keeps a list of them, and is able to
+// refresh them if configurations like the number of recommended threads
+// change.
+typedef struct TfLiteExternalContext {
+  TfLiteExternalContextType type;
+  TfLiteStatus (*Refresh)(struct TfLiteContext* context);
+} TfLiteExternalContext;
+
+#define kTfLiteOptionalTensor (-1)
+
+// Fixed size list of integers. Used for dimensions and inputs/outputs tensor
+// indices
+typedef struct TfLiteIntArray {
+  int size;
+// gcc 6.1+ have a bug where flexible members aren't properly handled
+// https://github.com/google/re2/commit/b94b7cd42e9f02673cd748c1ac1d16db4052514c
+#if !defined(__clang__) && defined(__GNUC__) && __GNUC__ == 6 && \
+    __GNUC_MINOR__ >= 1
+  int data[0];
+#else
+  int data[];
+#endif
+} TfLiteIntArray;
+
+// Given the size (number of elements) in a TfLiteIntArray, calculate its size
+// in bytes.
+int TfLiteIntArrayGetSizeInBytes(int size);
+
+#ifndef TF_LITE_STATIC_MEMORY
+// Create a array of a given `size` (uninitialized entries).
+// This returns a pointer, that you must free using TfLiteIntArrayFree().
+TfLiteIntArray* TfLiteIntArrayCreate(int size);
+#endif
+
+// Check if two intarrays are equal. Returns 1 if they are equal, 0 otherwise.
+int TfLiteIntArrayEqual(const TfLiteIntArray* a, const TfLiteIntArray* b);
+
+// Check if an intarray equals an array. Returns 1 if equals, 0 otherwise.
+int TfLiteIntArrayEqualsArray(const TfLiteIntArray* a, int b_size,
+                              const int b_data[]);
+
+#ifndef TF_LITE_STATIC_MEMORY
+// Create a copy of an array passed as `src`.
+// You are expected to free memory with TfLiteIntArrayFree
+TfLiteIntArray* TfLiteIntArrayCopy(const TfLiteIntArray* src);
+
+// Free memory of array `a`.
+void TfLiteIntArrayFree(TfLiteIntArray* a);
+#endif  // TF_LITE_STATIC_MEMORY
+
+// Fixed size list of floats. Used for per-channel quantization.
+typedef struct TfLiteFloatArray {
+  int size;
+// gcc 6.1+ have a bug where flexible members aren't properly handled
+// https://github.com/google/re2/commit/b94b7cd42e9f02673cd748c1ac1d16db4052514c
+#if !defined(__clang__) && defined(__GNUC__) && __GNUC__ == 6 && \
+    __GNUC_MINOR__ >= 1
+  float data[0];
+#else
+  float data[];
+#endif
+} TfLiteFloatArray;
+
+// Given the size (number of elements) in a TfLiteFloatArray, calculate its size
+// in bytes.
+int TfLiteFloatArrayGetSizeInBytes(int size);
+
+#ifndef TF_LITE_STATIC_MEMORY
+// Create a array of a given `size` (uninitialized entries).
+// This returns a pointer, that you must free using TfLiteFloatArrayFree().
+TfLiteFloatArray* TfLiteFloatArrayCreate(int size);
+
+// Free memory of array `a`.
+void TfLiteFloatArrayFree(TfLiteFloatArray* a);
+#endif  // TF_LITE_STATIC_MEMORY
+
+// Since we must not depend on any libraries, define a minimal subset of
+// error macros while avoiding names that have pre-conceived meanings like
+// assert and check.
+
+// Try to make all reporting calls through TF_LITE_KERNEL_LOG rather than
+// calling the context->ReportError function directly, so that message strings
+// can be stripped out if the binary size needs to be severely optimized.
+#ifndef TF_LITE_STRIP_ERROR_STRINGS
+#define TF_LITE_KERNEL_LOG(context, ...)            \
+  do {                                              \
+    (context)->ReportError((context), __VA_ARGS__); \
+  } while (false)
+#else  // TF_LITE_STRIP_ERROR_STRINGS
+#define TF_LITE_KERNEL_LOG(context, ...)
+#endif  // TF_LITE_STRIP_ERROR_STRINGS
+
+// Check whether value is true, and if not return kTfLiteError from
+// the current function (and report the error string msg).
+#define TF_LITE_ENSURE_MSG(context, value, msg)        \
+  do {                                                 \
+    if (!(value)) {                                    \
+      TF_LITE_KERNEL_LOG((context), __FILE__ " " msg); \
+      return kTfLiteError;                             \
+    }                                                  \
+  } while (0)
+
+// Check whether the value `a` is true, and if not return kTfLiteError from
+// the current function, while also reporting the location of the error.
+#define TF_LITE_ENSURE(context, a)                                      \
+  do {                                                                  \
+    if (!(a)) {                                                         \
+      TF_LITE_KERNEL_LOG((context), "%s:%d %s was not true.", __FILE__, \
+                         __LINE__, #a);                                 \
+      return kTfLiteError;                                              \
+    }                                                                   \
+  } while (0)
+
+#define TF_LITE_ENSURE_STATUS(a) \
+  do {                           \
+    if ((a) != kTfLiteOk) {      \
+      return kTfLiteError;       \
+    }                            \
+  } while (0)
+
+// Check whether the value `a == b` is true, and if not return kTfLiteError from
+// the current function, while also reporting the location of the error.
+// `a` and `b` may be evaluated more than once, so no side effects or
+// extremely expensive computations should be done.
+#define TF_LITE_ENSURE_EQ(context, a, b)                                   \
+  do {                                                                     \
+    if ((a) != (b)) {                                                      \
+      TF_LITE_KERNEL_LOG((context), "%s:%d %s != %s (%d != %d)", __FILE__, \
+                         __LINE__, #a, #b, (a), (b));                      \
+      return kTfLiteError;                                                 \
+    }                                                                      \
+  } while (0)
+
+#define TF_LITE_ENSURE_TYPES_EQ(context, a, b)                             \
+  do {                                                                     \
+    if ((a) != (b)) {                                                      \
+      TF_LITE_KERNEL_LOG((context), "%s:%d %s != %s (%s != %s)", __FILE__, \
+                         __LINE__, #a, #b, TfLiteTypeGetName(a),           \
+                         TfLiteTypeGetName(b));                            \
+      return kTfLiteError;                                                 \
+    }                                                                      \
+  } while (0)
+
+#define TF_LITE_ENSURE_OK(context, status) \
+  do {                                     \
+    if ((status) != kTfLiteOk) {           \
+      return kTfLiteError;                 \
+    }                                      \
+  } while (0)
+
+// Single-precision complex data type compatible with the C99 definition.
+typedef struct TfLiteComplex64 {
+  float re, im;  // real and imaginary parts, respectively.
+} TfLiteComplex64;
+
+// Half precision data type compatible with the C99 definition.
+typedef struct TfLiteFloat16 {
+  uint16_t data;
+} TfLiteFloat16;
+
+// Types supported by tensor
+typedef enum {
+  kTfLiteNoType = 0,
+  kTfLiteFloat32 = 1,
+  kTfLiteInt32 = 2,
+  kTfLiteUInt8 = 3,
+  kTfLiteInt64 = 4,
+  kTfLiteString = 5,
+  kTfLiteBool = 6,
+  kTfLiteInt16 = 7,
+  kTfLiteComplex64 = 8,
+  kTfLiteInt8 = 9,
+  kTfLiteFloat16 = 10,
+} TfLiteType;
+
+// Return the name of a given type, for error reporting purposes.
+const char* TfLiteTypeGetName(TfLiteType type);
+
+// SupportedQuantizationTypes.
+typedef enum TfLiteQuantizationType {
+  // No quantization.
+  kTfLiteNoQuantization = 0,
+  // Affine quantization (with support for per-channel quantization).
+  // Corresponds to TfLiteAffineQuantization.
+  kTfLiteAffineQuantization = 1,
+} TfLiteQuantizationType;
+
+// Structure specifying the quantization used by the tensor, if-any.
+typedef struct TfLiteQuantization {
+  // The type of quantization held by params.
+  TfLiteQuantizationType type;
+  // Holds a reference to one of the quantization param structures specified
+  // below.
+  void* params;
+} TfLiteQuantization;
+
+// Legacy. Will be deprecated in favor of TfLiteAffineQuantization.
+// If per-layer quantization is specified this field will still be populated in
+// addition to TfLiteAffineQuantization.
+// Parameters for asymmetric quantization. Quantized values can be converted
+// back to float using:
+//     real_value = scale * (quantized_value - zero_point)
+typedef struct TfLiteQuantizationParams {
+  float scale;
+  int32_t zero_point;
+} TfLiteQuantizationParams;
+
+// Parameters for asymmetric quantization across a dimension (i.e per output
+// channel quantization).
+// quantized_dimension specifies which dimension the scales and zero_points
+// correspond to.
+// For a particular value in quantized_dimension, quantized values can be
+// converted back to float using:
+//     real_value = scale * (quantized_value - zero_point)
+typedef struct TfLiteAffineQuantization {
+  TfLiteFloatArray* scale;
+  TfLiteIntArray* zero_point;
+  int32_t quantized_dimension;
+} TfLiteAffineQuantization;
+
+/* A union of pointers that points to memory for a given tensor. */
+typedef union TfLitePtrUnion {
+  /* Do not access these members directly, if possible, use
+   * GetTensorData<TYPE>(tensor) instead, otherwise only access .data, as other
+   * members are deprecated. */
+  int32_t* i32;
+  int64_t* i64;
+  float* f;
+  TfLiteFloat16* f16;
+  char* raw;
+  const char* raw_const;
+  uint8_t* uint8;
+  bool* b;
+  int16_t* i16;
+  TfLiteComplex64* c64;
+  int8_t* int8;
+  /* Only use this member. */
+  void* data;
+} TfLitePtrUnion;
+
+// Memory allocation strategies. kTfLiteMmapRo is for read-only memory-mapped
+// data (or data externally allocated). kTfLiteArenaRw is arena allocated
+// data. kTfLiteDynamic is for tensors that are allocated during evaluation.
+typedef enum TfLiteAllocationType {
+  kTfLiteMemNone = 0,
+  kTfLiteMmapRo,
+  kTfLiteArenaRw,
+  kTfLiteArenaRwPersistent,
+  kTfLiteDynamic,
+} TfLiteAllocationType;
+
+// The delegates should use zero or positive integers to represent handles.
+// -1 is reserved from unallocated status.
+typedef int TfLiteBufferHandle;
+enum {
+  kTfLiteNullBufferHandle = -1,
+};
+
+// Storage format of each dimension in a sparse tensor.
+typedef enum TfLiteDimensionType {
+  kTfLiteDimDense = 0,
+  kTfLiteDimSparseCSR,
+} TfLiteDimensionType;
+
+// Metadata to encode each dimension in a sparse tensor.
+typedef struct TfLiteDimensionMetadata {
+  TfLiteDimensionType format;
+  int dense_size;
+  TfLiteIntArray* array_segments;
+  TfLiteIntArray* array_indices;
+} TfLiteDimensionMetadata;
+
+// Parameters used to encode a sparse tensor. For detailed explanation of each
+// field please refer to lite/schema/schema.fbs.
+typedef struct TfLiteSparsity {
+  TfLiteIntArray* traversal_order;
+  TfLiteIntArray* block_map;
+  TfLiteDimensionMetadata* dim_metadata;
+  int dim_metadata_size;
+} TfLiteSparsity;
+
+// An tensor in the interpreter system which is a wrapper around a buffer of
+// data including a dimensionality (or NULL if not currently defined).
+typedef struct TfLiteTensor {
+  // The data type specification for data stored in `data`. This affects
+  // what member of `data` union should be used.
+  TfLiteType type;
+  // A union of data pointers. The appropriate type should be used for a typed
+  // tensor based on `type`.
+  TfLitePtrUnion data;
+  // A pointer to a structure representing the dimensionality interpretation
+  // that the buffer should have. NOTE: the product of elements of `dims`
+  // and the element datatype size should be equal to `bytes` below.
+  TfLiteIntArray* dims;
+  // Quantization information.
+  TfLiteQuantizationParams params;
+  // How memory is mapped
+  //  kTfLiteMmapRo: Memory mapped read only.
+  //  i.e. weights
+  //  kTfLiteArenaRw: Arena allocated read write memory
+  //  (i.e. temporaries, outputs).
+  TfLiteAllocationType allocation_type;
+  // The number of bytes required to store the data of this Tensor. I.e.
+  // (bytes of each element) * dims[0] * ... * dims[n-1].  For example, if
+  // type is kTfLiteFloat32 and dims = {3, 2} then
+  // bytes = sizeof(float) * 3 * 2 = 4 * 3 * 2 = 24.
+  size_t bytes;
+
+  // An opaque pointer to a tflite::MMapAllocation
+  const void* allocation;
+
+  // Null-terminated name of this tensor.
+  const char* name;
+
+  // The delegate which knows how to handle `buffer_handle`.
+  // WARNING: This is an experimental interface that is subject to change.
+  struct TfLiteDelegate* delegate;
+
+  // An integer buffer handle that can be handled by `delegate`.
+  // The value is valid only when delegate is not null.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteBufferHandle buffer_handle;
+
+  // If the delegate uses its own buffer (e.g. GPU memory), the delegate is
+  // responsible to set data_is_stale to true.
+  // `delegate->CopyFromBufferHandle` can be called to copy the data from
+  // delegate buffer.
+  // WARNING: This is an // experimental interface that is subject to change.
+  bool data_is_stale;
+
+  // True if the tensor is a variable.
+  bool is_variable;
+
+  // Quantization information. Replaces params field above.
+  TfLiteQuantization quantization;
+
+  // Parameters used to encode a sparse tensor.
+  // This is optional. The field is NULL if a tensor is dense.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteSparsity* sparsity;
+
+  // Optional. Encodes shapes with unknown dimensions with -1. This field is
+  // only populated when unknown dimensions exist in a read-write tensor (i.e.
+  // an input or output tensor). (e.g.  `dims` contains [1, 1, 1, 3] and
+  // `dims_signature` contains [1, -1, -1, 3]).
+  const TfLiteIntArray* dims_signature;
+} TfLiteTensor;
+
+#ifndef TF_LITE_STATIC_MEMORY
+// Free data memory of tensor `t`.
+void TfLiteTensorDataFree(TfLiteTensor* t);
+
+// Free quantization data.
+void TfLiteQuantizationFree(TfLiteQuantization* quantization);
+
+// Free sparsity parameters.
+void TfLiteSparsityFree(TfLiteSparsity* sparsity);
+
+// Free memory of tensor `t`.
+void TfLiteTensorFree(TfLiteTensor* t);
+
+// Set all of a tensor's fields (and free any previously allocated data).
+void TfLiteTensorReset(TfLiteType type, const char* name, TfLiteIntArray* dims,
+                       TfLiteQuantizationParams quantization, char* buffer,
+                       size_t size, TfLiteAllocationType allocation_type,
+                       const void* allocation, bool is_variable,
+                       TfLiteTensor* tensor);
+
+// Resize the allocated data of a (dynamic) tensor. Tensors with allocation
+// types other than kTfLiteDynamic will be ignored.
+void TfLiteTensorRealloc(size_t num_bytes, TfLiteTensor* tensor);
+#endif  // TF_LITE_STATIC_MEMORY
+
+// A structure representing an instance of a node.
+// This structure only exhibits the inputs, outputs and user defined data, not
+// other features like the type.
+typedef struct TfLiteNode {
+  // Inputs to this node expressed as indices into the simulator's tensors.
+  TfLiteIntArray* inputs;
+
+  // Outputs to this node expressed as indices into the simulator's tensors.
+  TfLiteIntArray* outputs;
+
+  // intermediate tensors to this node expressed as indices into the simulator's
+  // tensors.
+  TfLiteIntArray* intermediates;
+
+  // Temporary tensors uses during the computations. This usually contains no
+  // tensors, but ops are allowed to change that if they need scratch space of
+  // any sort.
+  TfLiteIntArray* temporaries;
+
+  // Opaque data provided by the node implementer through `Registration.init`.
+  void* user_data;
+
+  // Opaque data provided to the node if the node is a builtin. This is usually
+  // a structure defined in builtin_op_data.h
+  void* builtin_data;
+
+  // Custom initial data. This is the opaque data provided in the flatbuffer.
+  // WARNING: This is an experimental interface that is subject to change.
+  const void* custom_initial_data;
+  int custom_initial_data_size;
+
+  // The pointer to the delegate. This is non-null only when the node is
+  // created by calling `interpreter.ModifyGraphWithDelegate`.
+  // WARNING: This is an experimental interface that is subject to change.
+  struct TfLiteDelegate* delegate;
+} TfLiteNode;
+
+// WARNING: This is an experimental interface that is subject to change.
+//
+// Currently, TfLiteDelegateParams has to be allocated in a way that it's
+// trivially destructable. It will be stored as `builtin_data` field in
+// `TfLiteNode` of the delegate node.
+//
+// See also the `CreateDelegateParams` function in `interpreter.cc` details.
+typedef struct TfLiteDelegateParams {
+  struct TfLiteDelegate* delegate;
+  TfLiteIntArray* nodes_to_replace;
+  TfLiteIntArray* input_tensors;
+  TfLiteIntArray* output_tensors;
+} TfLiteDelegateParams;
+
+typedef struct TfLiteContext {
+  // Number of tensors in the context.
+  size_t tensors_size;
+
+  // The execution plan contains a list of the node indices in execution
+  // order. execution_plan->size is the current number of nodes. And,
+  // execution_plan->data[0] is the first node that needs to be run.
+  // TfLiteDelegates can traverse the current execution plan by iterating
+  // through each member of this array and using GetNodeAndRegistration() to
+  // access details about a node. i.e.
+  // TfLiteIntArray* execution_plan;
+  // TF_LITE_ENSURE_STATUS(context->GetExecutionPlan(context, &execution_plan));
+  // for (int exec_index = 0; exec_index < execution_plan->size; exec_index++) {
+  //    int node_index = execution_plan->data[exec_index];
+  //    TfLiteNode* node;
+  //    TfLiteRegistration* reg;
+  //    context->GetNodeAndRegistration(context, node_index, &node, &reg);
+  // }
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteStatus (*GetExecutionPlan)(struct TfLiteContext* context,
+                                   TfLiteIntArray** execution_plan);
+
+  // An array of tensors in the interpreter context (of length `tensors_size`)
+  TfLiteTensor* tensors;
+
+  // opaque full context ptr (an opaque c++ data structure)
+  void* impl_;
+
+  // Request memory pointer be resized. Updates dimensions on the tensor.
+  // NOTE: ResizeTensor takes ownership of newSize.
+  TfLiteStatus (*ResizeTensor)(struct TfLiteContext*, TfLiteTensor* tensor,
+                               TfLiteIntArray* new_size);
+  // Request that an error be reported with format string msg.
+  void (*ReportError)(struct TfLiteContext*, const char* msg, ...);
+
+  // Add `tensors_to_add` tensors, preserving pre-existing Tensor entries.  If
+  // non-null, the value pointed to by `first_new_tensor_index` will be set to
+  // the index of the first new tensor.
+  TfLiteStatus (*AddTensors)(struct TfLiteContext*, int tensors_to_add,
+                             int* first_new_tensor_index);
+
+  // Get a Tensor node by node_index.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteStatus (*GetNodeAndRegistration)(
+      struct TfLiteContext*, int node_index, TfLiteNode** node,
+      struct TfLiteRegistration** registration);
+
+  // Replace ops with one or more stub delegate operations. This function
+  // does not take ownership of `nodes_to_replace`.
+  TfLiteStatus (*ReplaceNodeSubsetsWithDelegateKernels)(
+      struct TfLiteContext*, struct TfLiteRegistration registration,
+      const TfLiteIntArray* nodes_to_replace, struct TfLiteDelegate* delegate);
+
+  // Number of threads that are recommended to subsystems like gemmlowp and
+  // eigen.
+  int recommended_num_threads;
+
+  // Access external contexts by type.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteExternalContext* (*GetExternalContext)(struct TfLiteContext*,
+                                               TfLiteExternalContextType);
+  // Set the value of a external context. Does not take ownership of the
+  // pointer.
+  // WARNING: This is an experimental interface that is subject to change.
+  void (*SetExternalContext)(struct TfLiteContext*, TfLiteExternalContextType,
+                             TfLiteExternalContext*);
+
+  // Flag for allowing float16 precision for FP32 calculation.
+  // default: false.
+  // WARNING: This is an experimental API and subject to change.
+  bool allow_fp32_relax_to_fp16;
+
+  // Pointer to the op-level profiler, if set; nullptr otherwise.
+  void* profiler;
+
+  // Allocate persistent buffer which has the same life time as the interpreter.
+  // The memory is allocated from heap for TFL, and from tail in TFLM.
+  // If *ptr is not nullptr, the pointer will be reallocated.
+  // This method is only available in Prepare stage.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteStatus (*AllocatePersistentBuffer)(struct TfLiteContext* ctx,
+                                           size_t bytes, void** ptr);
+
+  // Allocate a buffer which will be deallocated right after invoke phase.
+  // The memory is allocated from heap in TFL, and from volatile arena in TFLM.
+  // This method is only available in invoke stage.
+  // NOTE: If possible use RequestScratchBufferInArena method to avoid memory
+  // allocation during inference time.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteStatus (*AllocateBufferForEval)(struct TfLiteContext* ctx, size_t bytes,
+                                        void** ptr);
+
+  // Request a scratch buffer in the arena through static memory planning.
+  // This method is only available in Prepare stage and the buffer is allocated
+  // by the interpreter between Prepare and Eval stage. In Eval stage,
+  // GetScratchBuffer API can be used to fetch the address.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteStatus (*RequestScratchBufferInArena)(struct TfLiteContext* ctx,
+                                              size_t bytes, int* buffer_idx);
+
+  // Get the scratch buffer pointer.
+  // This method is only available in Eval stage.
+  // WARNING: This is an experimental interface that is subject to change.
+  void* (*GetScratchBuffer)(struct TfLiteContext* ctx, int buffer_idx);
+
+  // Resize the memory pointer of the `tensor`. This method behaves the same as
+  // `ResizeTensor`, except that it makes a copy of the shape array internally
+  // so the shape array could be deallocated right afterwards.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteStatus (*ResizeTensorExplicit)(struct TfLiteContext* ctx,
+                                       TfLiteTensor* tensor, int dims,
+                                       const int* shape);
+
+  // This method provides a preview of post-delegation partitioning. Each
+  // TfLiteDelegateParams in the referenced array corresponds to one instance of
+  // the delegate kernel.
+  // Example usage:
+  //
+  // TfLiteIntArray* nodes_to_replace = ...;
+  // TfLiteDelegateParams* params_array;
+  // int num_partitions = 0;
+  // TF_LITE_ENSURE_STATUS(context->PreviewDelegatePartitioning(
+  //    context, delegate, nodes_to_replace, &params_array, &num_partitions));
+  // for (int idx = 0; idx < num_partitions; idx++) {
+  //    const auto& partition_params = params_array[idx];
+  //    ...
+  // }
+  //
+  // NOTE: The context owns the memory referenced by partition_params_array. It
+  // will be cleared with another call to PreviewDelegateParitioning, or after
+  // TfLiteDelegateParams::Prepare returns.
+  //
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteStatus (*PreviewDelegatePartitioning)(
+      struct TfLiteContext* context, const TfLiteIntArray* nodes_to_replace,
+      TfLiteDelegateParams** partition_params_array, int* num_partitions);
+} TfLiteContext;
+
+typedef struct TfLiteRegistration {
+  // Initializes the op from serialized data.
+  // If a built-in op:
+  //   `buffer` is the op's params data (TfLiteLSTMParams*).
+  //   `length` is zero.
+  // If custom op:
+  //   `buffer` is the op's `custom_options`.
+  //   `length` is the size of the buffer.
+  //
+  // Returns a type-punned (i.e. void*) opaque data (e.g. a primitive pointer
+  // or an instance of a struct).
+  //
+  // The returned pointer will be stored with the node in the `user_data` field,
+  // accessible within prepare and invoke functions below.
+  // NOTE: if the data is already in the desired format, simply implement this
+  // function to return `nullptr` and implement the free function to be a no-op.
+  void* (*init)(TfLiteContext* context, const char* buffer, size_t length);
+
+  // The pointer `buffer` is the data previously returned by an init invocation.
+  void (*free)(TfLiteContext* context, void* buffer);
+
+  // prepare is called when the inputs this node depends on have been resized.
+  // context->ResizeTensor() can be called to request output tensors to be
+  // resized.
+  //
+  // Returns kTfLiteOk on success.
+  TfLiteStatus (*prepare)(TfLiteContext* context, TfLiteNode* node);
+
+  // Execute the node (should read node->inputs and output to node->outputs).
+  // Returns kTfLiteOk on success.
+  TfLiteStatus (*invoke)(TfLiteContext* context, TfLiteNode* node);
+
+  // profiling_string is called during summarization of profiling information
+  // in order to group executions together. Providing a value here will cause a
+  // given op to appear multiple times is the profiling report. This is
+  // particularly useful for custom ops that can perform significantly
+  // different calculations depending on their `user-data`.
+  const char* (*profiling_string)(const TfLiteContext* context,
+                                  const TfLiteNode* node);
+
+  // Builtin codes. If this kernel refers to a builtin this is the code
+  // of the builtin. This is so we can do marshaling to other frameworks like
+  // NN API.
+  // Note: It is the responsibility of the registration binder to set this
+  // properly.
+  int32_t builtin_code;
+
+  // Custom op name. If the op is a builtin, this will be null.
+  // Note: It is the responsibility of the registration binder to set this
+  // properly.
+  // WARNING: This is an experimental interface that is subject to change.
+  const char* custom_name;
+
+  // The version of the op.
+  // Note: It is the responsibility of the registration binder to set this
+  // properly.
+  int version;
+} TfLiteRegistration;
+
+// The flags used in `TfLiteDelegate`. Note that this is a bitmask, so the
+// values should be 1, 2, 4, 8, ...etc.
+typedef enum TfLiteDelegateFlags {
+  kTfLiteDelegateFlagsNone = 0,
+  // The flag is set if the delegate can handle dynamic sized tensors.
+  // For example, the output shape of a `Resize` op with non-constant shape
+  // can only be inferred when the op is invoked.
+  // In this case, the Delegate is responsible for calling
+  // `SetTensorToDynamic` to mark the tensor as a dynamic tensor, and calling
+  // `ResizeTensor` when invoking the op.
+  //
+  // If the delegate isn't capable to handle dynamic tensors, this flag need
+  // to be set to false.
+  kTfLiteDelegateFlagsAllowDynamicTensors = 1
+} TfLiteDelegateFlags;
+
+// WARNING: This is an experimental interface that is subject to change.
+typedef struct TfLiteDelegate {
+  // Data that delegate needs to identify itself. This data is owned by the
+  // delegate. The delegate is owned in the user code, so the delegate is
+  // responsible for doing this when it is destroyed.
+  void* data_;
+
+  // Invoked by ModifyGraphWithDelegate. This prepare is called, giving the
+  // delegate a view of the current graph through TfLiteContext*. It typically
+  // will look at the nodes and call ReplaceNodeSubsetsWithDelegateKernels()
+  // to ask the TensorFlow lite runtime to create macro-nodes to represent
+  // delegated subgraphs of the original graph.
+  TfLiteStatus (*Prepare)(TfLiteContext* context,
+                          struct TfLiteDelegate* delegate);
+
+  // Copy the data from delegate buffer handle into raw memory of the given
+  // 'tensor'. This cannot be null. The delegate is allowed to allocate the raw
+  // bytes as long as it follows the rules for kTfLiteDynamic tensors.
+  TfLiteStatus (*CopyFromBufferHandle)(TfLiteContext* context,
+                                       struct TfLiteDelegate* delegate,
+                                       TfLiteBufferHandle buffer_handle,
+                                       TfLiteTensor* tensor);
+
+  // Copy the data from raw memory of the given 'tensor' to delegate buffer
+  // handle. This can be null if the delegate doesn't use its own buffer.
+  TfLiteStatus (*CopyToBufferHandle)(TfLiteContext* context,
+                                     struct TfLiteDelegate* delegate,
+                                     TfLiteBufferHandle buffer_handle,
+                                     TfLiteTensor* tensor);
+
+  // Free the Delegate Buffer Handle. Note: This only frees the handle, but
+  // this doesn't release the underlying resource (e.g. textures). The
+  // resources are either owned by application layer or the delegate.
+  // This can be null if the delegate doesn't use its own buffer.
+  void (*FreeBufferHandle)(TfLiteContext* context,
+                           struct TfLiteDelegate* delegate,
+                           TfLiteBufferHandle* handle);
+
+  // Bitmask flags. See the comments in `TfLiteDelegateFlags`.
+  int64_t flags;
+} TfLiteDelegate;
+
+// Build a 'null' delegate, with all the fields properly set to their default
+// values.
+TfLiteDelegate TfLiteDelegateCreate();
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+#endif  // TENSORFLOW_LITE_C_COMMON_H_
diff --git a/extensions/functions/labelImage/etc/labels.txt b/extensions/functions/labelImage/etc/labels.txt
new file mode 100644
index 0000000000..fe811239d8
--- /dev/null
+++ b/extensions/functions/labelImage/etc/labels.txt
@@ -0,0 +1,1001 @@
+background
+tench
+goldfish
+great white shark
+tiger shark
+hammerhead
+electric ray
+stingray
+cock
+hen
+ostrich
+brambling
+goldfinch
+house finch
+junco
+indigo bunting
+robin
+bulbul
+jay
+magpie
+chickadee
+water ouzel
+kite
+bald eagle
+vulture
+great grey owl
+European fire salamander
+common newt
+eft
+spotted salamander
+axolotl
+bullfrog
+tree frog
+tailed frog
+loggerhead
+leatherback turtle
+mud turtle
+terrapin
+box turtle
+banded gecko
+common iguana
+American chameleon
+whiptail
+agama
+frilled lizard
+alligator lizard
+Gila monster
+green lizard
+African chameleon
+Komodo dragon
+African crocodile
+American alligator
+triceratops
+thunder snake
+ringneck snake
+hognose snake
+green snake
+king snake
+garter snake
+water snake
+vine snake
+night snake
+boa constrictor
+rock python
+Indian cobra
+green mamba
+sea snake
+horned viper
+diamondback
+sidewinder
+trilobite
+harvestman
+scorpion
+black and gold garden spider
+barn spider
+garden spider
+black widow
+tarantula
+wolf spider
+tick
+centipede
+black grouse
+ptarmigan
+ruffed grouse
+prairie chicken
+peacock
+quail
+partridge
+African grey
+macaw
+sulphur-crested cockatoo
+lorikeet
+coucal
+bee eater
+hornbill
+hummingbird
+jacamar
+toucan
+drake
+red-breasted merganser
+goose
+black swan
+tusker
+echidna
+platypus
+wallaby
+koala
+wombat
+jellyfish
+sea anemone
+brain coral
+flatworm
+nematode
+conch
+snail
+slug
+sea slug
+chiton
+chambered nautilus
+Dungeness crab
+rock crab
+fiddler crab
+king crab
+American lobster
+spiny lobster
+crayfish
+hermit crab
+isopod
+white stork
+black stork
+spoonbill
+flamingo
+little blue heron
+American egret
+bittern
+crane
+limpkin
+European gallinule
+American coot
+bustard
+ruddy turnstone
+red-backed sandpiper
+redshank
+dowitcher
+oystercatcher
+pelican
+king penguin
+albatross
+grey whale
+killer whale
+dugong
+sea lion
+Chihuahua
+Japanese spaniel
+Maltese dog
+Pekinese
+Shih-Tzu
+Blenheim spaniel
+papillon
+toy terrier
+Rhodesian ridgeback
+Afghan hound
+basset
+beagle
+bloodhound
+bluetick
+black-and-tan coonhound
+Walker hound
+English foxhound
+redbone
+borzoi
+Irish wolfhound
+Italian greyhound
+whippet
+Ibizan hound
+Norwegian elkhound
+otterhound
+Saluki
+Scottish deerhound
+Weimaraner
+Staffordshire bullterrier
+American Staffordshire terrier
+Bedlington terrier
+Border terrier
+Kerry blue terrier
+Irish terrier
+Norfolk terrier
+Norwich terrier
+Yorkshire terrier
+wire-haired fox terrier
+Lakeland terrier
+Sealyham terrier
+Airedale
+cairn
+Australian terrier
+Dandie Dinmont
+Boston bull
+miniature schnauzer
+giant schnauzer
+standard schnauzer
+Scotch terrier
+Tibetan terrier
+silky terrier
+soft-coated wheaten terrier
+West Highland white terrier
+Lhasa
+flat-coated retriever
+curly-coated retriever
+golden retriever
+Labrador retriever
+Chesapeake Bay retriever
+German short-haired pointer
+vizsla
+English setter
+Irish setter
+Gordon setter
+Brittany spaniel
+clumber
+English springer
+Welsh springer spaniel
+cocker spaniel
+Sussex spaniel
+Irish water spaniel
+kuvasz
+schipperke
+groenendael
+malinois
+briard
+kelpie
+komondor
+Old English sheepdog
+Shetland sheepdog
+collie
+Border collie
+Bouvier des Flandres
+Rottweiler
+German shepherd
+Doberman
+miniature pinscher
+Greater Swiss Mountain dog
+Bernese mountain dog
+Appenzeller
+EntleBucher
+boxer
+bull mastiff
+Tibetan mastiff
+French bulldog
+Great Dane
+Saint Bernard
+Eskimo dog
+malamute
+Siberian husky
+dalmatian
+affenpinscher
+basenji
+pug
+Leonberg
+Newfoundland
+Great Pyrenees
+Samoyed
+Pomeranian
+chow
+keeshond
+Brabancon griffon
+Pembroke
+Cardigan
+toy poodle
+miniature poodle
+standard poodle
+Mexican hairless
+timber wolf
+white wolf
+red wolf
+coyote
+dingo
+dhole
+African hunting dog
+hyena
+red fox
+kit fox
+Arctic fox
+grey fox
+tabby
+tiger cat
+Persian cat
+Siamese cat
+Egyptian cat
+cougar
+lynx
+leopard
+snow leopard
+jaguar
+lion
+tiger
+cheetah
+brown bear
+American black bear
+ice bear
+sloth bear
+mongoose
+meerkat
+tiger beetle
+ladybug
+ground beetle
+long-horned beetle
+leaf beetle
+dung beetle
+rhinoceros beetle
+weevil
+fly
+bee
+ant
+grasshopper
+cricket
+walking stick
+cockroach
+mantis
+cicada
+leafhopper
+lacewing
+dragonfly
+damselfly
+admiral
+ringlet
+monarch
+cabbage butterfly
+sulphur butterfly
+lycaenid
+starfish
+sea urchin
+sea cucumber
+wood rabbit
+hare
+Angora
+hamster
+porcupine
+fox squirrel
+marmot
+beaver
+guinea pig
+sorrel
+zebra
+hog
+wild boar
+warthog
+hippopotamus
+ox
+water buffalo
+bison
+ram
+bighorn
+ibex
+hartebeest
+impala
+gazelle
+Arabian camel
+llama
+weasel
+mink
+polecat
+black-footed ferret
+otter
+skunk
+badger
+armadillo
+three-toed sloth
+orangutan
+gorilla
+chimpanzee
+gibbon
+siamang
+guenon
+patas
+baboon
+macaque
+langur
+colobus
+proboscis monkey
+marmoset
+capuchin
+howler monkey
+titi
+spider monkey
+squirrel monkey
+Madagascar cat
+indri
+Indian elephant
+African elephant
+lesser panda
+giant panda
+barracouta
+eel
+coho
+rock beauty
+anemone fish
+sturgeon
+gar
+lionfish
+puffer
+abacus
+abaya
+academic gown
+accordion
+acoustic guitar
+aircraft carrier
+airliner
+airship
+altar
+ambulance
+amphibian
+analog clock
+apiary
+apron
+ashcan
+assault rifle
+backpack
+bakery
+balance beam
+balloon
+ballpoint
+Band Aid
+banjo
+bannister
+barbell
+barber chair
+barbershop
+barn
+barometer
+barrel
+barrow
+baseball
+basketball
+bassinet
+bassoon
+bathing cap
+bath towel
+bathtub
+beach wagon
+beacon
+beaker
+bearskin
+beer bottle
+beer glass
+bell cote
+bib
+bicycle-built-for-two
+bikini
+binder
+binoculars
+birdhouse
+boathouse
+bobsled
+bolo tie
+bonnet
+bookcase
+bookshop
+bottlecap
+bow
+bow tie
+brass
+brassiere
+breakwater
+breastplate
+broom
+bucket
+buckle
+bulletproof vest
+bullet train
+butcher shop
+cab
+caldron
+candle
+cannon
+canoe
+can opener
+cardigan
+car mirror
+carousel
+carpenter's kit
+carton
+car wheel
+cash machine
+cassette
+cassette player
+castle
+catamaran
+CD player
+cello
+cellular telephone
+chain
+chainlink fence
+chain mail
+chain saw
+chest
+chiffonier
+chime
+china cabinet
+Christmas stocking
+church
+cinema
+cleaver
+cliff dwelling
+cloak
+clog
+cocktail shaker
+coffee mug
+coffeepot
+coil
+combination lock
+computer keyboard
+confectionery
+container ship
+convertible
+corkscrew
+cornet
+cowboy boot
+cowboy hat
+cradle
+crane
+crash helmet
+crate
+crib
+Crock Pot
+croquet ball
+crutch
+cuirass
+dam
+desk
+desktop computer
+dial telephone
+diaper
+digital clock
+digital watch
+dining table
+dishrag
+dishwasher
+disk brake
+dock
+dogsled
+dome
+doormat
+drilling platform
+drum
+drumstick
+dumbbell
+Dutch oven
+electric fan
+electric guitar
+electric locomotive
+entertainment center
+envelope
+espresso maker
+face powder
+feather boa
+file
+fireboat
+fire engine
+fire screen
+flagpole
+flute
+folding chair
+football helmet
+forklift
+fountain
+fountain pen
+four-poster
+freight car
+French horn
+frying pan
+fur coat
+garbage truck
+gasmask
+gas pump
+goblet
+go-kart
+golf ball
+golfcart
+gondola
+gong
+gown
+grand piano
+greenhouse
+grille
+grocery store
+guillotine
+hair slide
+hair spray
+half track
+hammer
+hamper
+hand blower
+hand-held computer
+handkerchief
+hard disc
+harmonica
+harp
+harvester
+hatchet
+holster
+home theater
+honeycomb
+hook
+hoopskirt
+horizontal bar
+horse cart
+hourglass
+iPod
+iron
+jack-o'-lantern
+jean
+jeep
+jersey
+jigsaw puzzle
+jinrikisha
+joystick
+kimono
+knee pad
+knot
+lab coat
+ladle
+lampshade
+laptop
+lawn mower
+lens cap
+letter opener
+library
+lifeboat
+lighter
+limousine
+liner
+lipstick
+Loafer
+lotion
+loudspeaker
+loupe
+lumbermill
+magnetic compass
+mailbag
+mailbox
+maillot
+maillot
+manhole cover
+maraca
+marimba
+mask
+matchstick
+maypole
+maze
+measuring cup
+medicine chest
+megalith
+microphone
+microwave
+military uniform
+milk can
+minibus
+miniskirt
+minivan
+missile
+mitten
+mixing bowl
+mobile home
+Model T
+modem
+monastery
+monitor
+moped
+mortar
+mortarboard
+mosque
+mosquito net
+motor scooter
+mountain bike
+mountain tent
+mouse
+mousetrap
+moving van
+muzzle
+nail
+neck brace
+necklace
+nipple
+notebook
+obelisk
+oboe
+ocarina
+odometer
+oil filter
+organ
+oscilloscope
+overskirt
+oxcart
+oxygen mask
+packet
+paddle
+paddlewheel
+padlock
+paintbrush
+pajama
+palace
+panpipe
+paper towel
+parachute
+parallel bars
+park bench
+parking meter
+passenger car
+patio
+pay-phone
+pedestal
+pencil box
+pencil sharpener
+perfume
+Petri dish
+photocopier
+pick
+pickelhaube
+picket fence
+pickup
+pier
+piggy bank
+pill bottle
+pillow
+ping-pong ball
+pinwheel
+pirate
+pitcher
+plane
+planetarium
+plastic bag
+plate rack
+plow
+plunger
+Polaroid camera
+pole
+police van
+poncho
+pool table
+pop bottle
+pot
+potter's wheel
+power drill
+prayer rug
+printer
+prison
+projectile
+projector
+puck
+punching bag
+purse
+quill
+quilt
+racer
+racket
+radiator
+radio
+radio telescope
+rain barrel
+recreational vehicle
+reel
+reflex camera
+refrigerator
+remote control
+restaurant
+revolver
+rifle
+rocking chair
+rotisserie
+rubber eraser
+rugby ball
+rule
+running shoe
+safe
+safety pin
+saltshaker
+sandal
+sarong
+sax
+scabbard
+scale
+school bus
+schooner
+scoreboard
+screen
+screw
+screwdriver
+seat belt
+sewing machine
+shield
+shoe shop
+shoji
+shopping basket
+shopping cart
+shovel
+shower cap
+shower curtain
+ski
+ski mask
+sleeping bag
+slide rule
+sliding door
+slot
+snorkel
+snowmobile
+snowplow
+soap dispenser
+soccer ball
+sock
+solar dish
+sombrero
+soup bowl
+space bar
+space heater
+space shuttle
+spatula
+speedboat
+spider web
+spindle
+sports car
+spotlight
+stage
+steam locomotive
+steel arch bridge
+steel drum
+stethoscope
+stole
+stone wall
+stopwatch
+stove
+strainer
+streetcar
+stretcher
+studio couch
+stupa
+submarine
+suit
+sundial
+sunglass
+sunglasses
+sunscreen
+suspension bridge
+swab
+sweatshirt
+swimming trunks
+swing
+switch
+syringe
+table lamp
+tank
+tape player
+teapot
+teddy
+television
+tennis ball
+thatch
+theater curtain
+thimble
+thresher
+throne
+tile roof
+toaster
+tobacco shop
+toilet seat
+torch
+totem pole
+tow truck
+toyshop
+tractor
+trailer truck
+tray
+trench coat
+tricycle
+trimaran
+tripod
+triumphal arch
+trolleybus
+trombone
+tub
+turnstile
+typewriter keyboard
+umbrella
+unicycle
+upright
+vacuum
+vase
+vault
+velvet
+vending machine
+vestment
+viaduct
+violin
+volleyball
+waffle iron
+wall clock
+wallet
+wardrobe
+warplane
+washbasin
+washer
+water bottle
+water jug
+water tower
+whiskey jug
+whistle
+wig
+window screen
+window shade
+Windsor tie
+wine bottle
+wing
+wok
+wooden spoon
+wool
+worm fence
+wreck
+yawl
+yurt
+web site
+comic book
+crossword puzzle
+street sign
+traffic light
+book jacket
+menu
+plate
+guacamole
+consomme
+hot pot
+trifle
+ice cream
+ice lolly
+French loaf
+bagel
+pretzel
+cheeseburger
+hotdog
+mashed potato
+head cabbage
+broccoli
+cauliflower
+zucchini
+spaghetti squash
+acorn squash
+butternut squash
+cucumber
+artichoke
+bell pepper
+cardoon
+mushroom
+Granny Smith
+strawberry
+orange
+lemon
+fig
+pineapple
+banana
+jackfruit
+custard apple
+pomegranate
+hay
+carbonara
+chocolate sauce
+dough
+meat loaf
+pizza
+potpie
+burrito
+red wine
+espresso
+cup
+eggnog
+alp
+bubble
+cliff
+coral reef
+geyser
+lakeside
+promontory
+sandbar
+seashore
+valley
+volcano
+ballplayer
+groom
+scuba diver
+rapeseed
+daisy
+yellow lady's slipper
+corn
+acorn
+hip
+buckeye
+coral fungus
+agaric
+gyromitra
+stinkhorn
+earthstar
+hen-of-the-woods
+bolete
+ear
+toilet tissue
diff --git a/extensions/functions/labelImage/etc/mobilenet_quant_v1_224.tflite b/extensions/functions/labelImage/etc/mobilenet_quant_v1_224.tflite
new file mode 100644
index 0000000000..98ae42a531
Binary files /dev/null and b/extensions/functions/labelImage/etc/mobilenet_quant_v1_224.tflite differ
diff --git a/extensions/functions/labelImage/install.sh b/extensions/functions/labelImage/install.sh
new file mode 100644
index 0000000000..c927ce2871
--- /dev/null
+++ b/extensions/functions/labelImage/install.sh
@@ -0,0 +1,40 @@
+#!/bin/sh
+#
+# Copyright 2021-2024 EMQ Technologies Co., Ltd.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+dir=/usr/local/tflite
+cur=$(dirname "$0")
+echo "Base path $cur" 
+if [ -d "$dir" ]; then
+    echo "SDK path $dir exists." 
+else
+    echo "Creating SDK path $dir"
+    mkdir -p $dir
+    echo "Created SDK path $dir"
+    echo "Moving libs"
+    cp -R $cur/lib $dir
+    echo "Moved libs"
+fi
+
+if [ -f "/etc/ld.so.conf.d/tflite.conf" ]; then
+    echo "/etc/ld.so.conf.d/tflite.conf exists"
+else
+    echo "Copy conf file"
+    cp $cur/tflite.conf /etc/ld.so.conf.d/
+    echo "Copied conf file"
+fi
+ldconfig
+echo "Done"
\ No newline at end of file
diff --git a/extensions/functions/labelImage/labelImage.go b/extensions/functions/labelImage/labelImage.go
new file mode 100644
index 0000000000..49cc0efe80
--- /dev/null
+++ b/extensions/functions/labelImage/labelImage.go
@@ -0,0 +1,186 @@
+// Copyright 2021-2024 EMQ Technologies Co., Ltd.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+//go:build tflite
+
+package main
+
+import (
+	"bufio"
+	"bytes"
+	"fmt"
+	"image"
+	_ "image/jpeg"
+	_ "image/png"
+	"os"
+	"path"
+	"sort"
+	"sync"
+
+	tflite "github.com/mattn/go-tflite" //nolint:typecheck
+	"github.com/nfnt/resize"
+
+	"github.com/lf-edge/ekuiper/contract/v2/api"
+)
+
+type labelImage struct {
+	modelPath   string
+	labelPath   string
+	once        sync.Once
+	interpreter *tflite.Interpreter
+	labels      []string
+}
+
+func (f *labelImage) Validate(args []interface{}) error {
+	if len(args) != 1 {
+		return fmt.Errorf("labelImage function only supports 1 parameter but got %d", len(args))
+	}
+	return nil
+}
+
+func (f *labelImage) Exec(args []interface{}, ctx api.FunctionContext) (interface{}, bool) {
+	arg0, ok := args[0].([]byte)
+	if !ok {
+		return fmt.Errorf("labelImage function parameter must be a bytea, but got %[1]T(%[1]v)", args[0]), false
+	}
+	img, _, err := image.Decode(bytes.NewReader(arg0))
+	if err != nil {
+		return err, false
+	}
+	var outerErr error
+	f.once.Do(func() {
+		ploc := path.Join(ctx.GetRootPath(), "data", "functions")
+		f.labels, err = loadLabels(path.Join(ploc, f.labelPath))
+		if err != nil {
+			outerErr = fmt.Errorf("fail to load labels: %s", err)
+			return
+		}
+
+		model := tflite.NewModelFromFile(path.Join(ploc, f.modelPath))
+		if model == nil {
+			outerErr = fmt.Errorf("fail to load model: %s", err)
+			return
+		}
+		defer model.Delete()
+
+		options := tflite.NewInterpreterOptions()
+		options.SetNumThread(4)
+		options.SetErrorReporter(func(msg string, user_data interface{}) {
+			fmt.Println(msg)
+		}, nil)
+		defer options.Delete()
+
+		interpreter := tflite.NewInterpreter(model, options)
+		if interpreter == nil {
+			outerErr = fmt.Errorf("cannot create interpreter")
+			return
+		}
+		status := interpreter.AllocateTensors()
+		if status != tflite.OK {
+			outerErr = fmt.Errorf("allocate failed")
+			interpreter.Delete()
+			return
+		}
+
+		f.interpreter = interpreter
+		// TODO If created, the interpreter will be kept through the whole life of kuiper. Refactor this later.
+		// defer interpreter.Delete()
+	})
+
+	if f.interpreter == nil {
+		return fmt.Errorf("fail to load model %s %s", f.modelPath, outerErr), false
+	}
+	input := f.interpreter.GetInputTensor(0)
+	wantedHeight := input.Dim(1)
+	wantedWidth := input.Dim(2)
+	wantedChannels := input.Dim(3)
+	wantedType := input.Type()
+
+	resized := resize.Resize(uint(wantedWidth), uint(wantedHeight), img, resize.NearestNeighbor)
+	bounds := resized.Bounds()
+	dx, dy := bounds.Dx(), bounds.Dy()
+
+	if wantedType == tflite.UInt8 {
+		bb := make([]byte, dx*dy*wantedChannels)
+		for y := 0; y < dy; y++ {
+			for x := 0; x < dx; x++ {
+				col := resized.At(x, y)
+				r, g, b, _ := col.RGBA()
+				bb[(y*dx+x)*3+0] = byte(float64(r) / 255.0)
+				bb[(y*dx+x)*3+1] = byte(float64(g) / 255.0)
+				bb[(y*dx+x)*3+2] = byte(float64(b) / 255.0)
+			}
+		}
+		input.CopyFromBuffer(bb)
+	} else {
+		return fmt.Errorf("is not wanted type"), false
+	}
+
+	status := f.interpreter.Invoke()
+	if status != tflite.OK {
+		return fmt.Errorf("invoke failed"), false
+	}
+
+	output := f.interpreter.GetOutputTensor(0)
+	outputSize := output.Dim(output.NumDims() - 1)
+	b := make([]byte, outputSize)
+	type result struct {
+		score float64
+		index int
+	}
+	status = output.CopyToBuffer(&b[0])
+	if status != tflite.OK {
+		return fmt.Errorf("output failed"), false
+	}
+	var results []result
+	for i := 0; i < outputSize; i++ {
+		score := float64(b[i]) / 255.0
+		if score < 0.2 {
+			continue
+		}
+		results = append(results, result{score: score, index: i})
+	}
+	sort.Slice(results, func(i, j int) bool {
+		return results[i].score > results[j].score
+	})
+	// output is the biggest score labelImage
+	if len(results) > 0 {
+		return f.labels[results[0].index], true
+	} else {
+		return "", true
+	}
+}
+
+func (f *labelImage) IsAggregate() bool {
+	return false
+}
+
+func loadLabels(filename string) ([]string, error) {
+	labels := []string{}
+	f, err := os.Open(filename)
+	if err != nil {
+		return nil, err
+	}
+	defer f.Close()
+	scanner := bufio.NewScanner(f)
+	for scanner.Scan() {
+		labels = append(labels, scanner.Text())
+	}
+	return labels, nil
+}
+
+var LabelImage = labelImage{
+	modelPath: "labelImage/mobilenet_quant_v1_224.tflite",
+	labelPath: "labelImage/labels.txt",
+}
diff --git a/extensions/functions/labelImage/labelImage.json b/extensions/functions/labelImage/labelImage.json
new file mode 100644
index 0000000000..716512fe63
--- /dev/null
+++ b/extensions/functions/labelImage/labelImage.json
@@ -0,0 +1,62 @@
+{
+  "about": {
+    "trial": false,
+    "author": {
+      "name": "EMQ",
+      "email": "contact@emqx.io",
+      "company": "EMQ Technologies Co., Ltd",
+      "website": "https://www.emqx.io"
+    },
+    "helpUrl": {
+      "en_US": "https://ekuiper.org/docs/en/latest/sqls/functions/custom_functions.html",
+      "zh_CN": "https://ekuiper.org/docs/zh/latest/sqls/functions/custom_functions.html"
+    },
+    "description": {
+      "en_US": "Example plugin to demonstrate inferring Tensorflow lite model to label an image",
+      "zh_CN": "示例插件，演示如何使用Tensorflow lite模型对图像进行标记推断。"
+    }
+  },
+  "name": "labelImage",
+  "functions": [
+    {
+      "name": "labelImage",
+      "example": "labelImage(col1)",
+      "hint": {
+        "en_US": "Label an image by tensorflow lite model.",
+        "zh_CN": "采用 tensorflow lite 模型标记图片。"
+      },
+      "args": [
+        {
+          "name": "image",
+          "hidden": false,
+          "optional": false,
+          "control": "field",
+          "type": "string",
+          "hint": {
+            "en_US": "Input image",
+            "zh_CN": "输入图像"
+          },
+          "label": {
+            "en_US": "Image",
+            "zh_CN": "图像"
+          }
+        }
+      ],
+      "return": {
+        "type": "string",
+        "hint": {
+          "en_US": "Image Label",
+          "zh_CN": "图像标注"
+        }
+      },
+      "node": {
+        "category": "function",
+        "icon": "iconPath",
+        "label": {
+          "en_US": "Label Image",
+          "zh_CN": "图像标注"
+        }
+      }
+    }
+  ]
+}
diff --git a/extensions/functions/labelImage/lib/Readme.md b/extensions/functions/labelImage/lib/Readme.md
new file mode 100644
index 0000000000..016b202dbc
--- /dev/null
+++ b/extensions/functions/labelImage/lib/Readme.md
@@ -0,0 +1,27 @@
+# Tensorflow Lite C API library
+
+This is the prebuilt tensorflow lite c library for debian 10. It can be used directly in eKuiper docker image of tags
+x.x.x or x.x.x-slim.
+
+To use in other environment, you need to build the library from source.
+
+## Build from source
+
+Here are the steps to build from source in debian.
+
+1. Install [Python](https://www.tensorflow.org/install/pip#1.-install-the-python-development-environment-on-your-system)
+
+2. Install required python lib: `pip3 install -r requirements.txt`. The requirements are
+   from `tensorflow/tensorflow/tools/pip_package/setup.py` of the corresponding tensorflow version.
+
+3. Install [Bazel](https://docs.bazel.build/versions/4.0.0/install-ubuntu.html)
+
+4. Clone [tensorflow](https://github.com/tensorflow/tensorflow)，switch to `git checkout v2.2.0-rc3 -b mybranch`
+
+5. Build the so files, the outputs are in ./bazel-bin
+
+   ```bash
+   $ cd $tensorflowSrc
+   $ bazel build --config monolithic -c opt //tensorflow/lite:libtensorflowlite.so
+   $ bazel build --config monolithic -c opt //tensorflow/lite/c:libtensorflowlite_c.so
+   ```
diff --git a/extensions/functions/labelImage/tflite.conf b/extensions/functions/labelImage/tflite.conf
new file mode 100644
index 0000000000..df0b739082
--- /dev/null
+++ b/extensions/functions/labelImage/tflite.conf
@@ -0,0 +1,2 @@
+# include tflite c api
+/usr/local/tflite/lib
\ No newline at end of file
diff --git a/extensions/functions/tfLite/install.sh b/extensions/functions/tfLite/install.sh
new file mode 100644
index 0000000000..c927ce2871
--- /dev/null
+++ b/extensions/functions/tfLite/install.sh
@@ -0,0 +1,40 @@
+#!/bin/sh
+#
+# Copyright 2021-2024 EMQ Technologies Co., Ltd.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+dir=/usr/local/tflite
+cur=$(dirname "$0")
+echo "Base path $cur" 
+if [ -d "$dir" ]; then
+    echo "SDK path $dir exists." 
+else
+    echo "Creating SDK path $dir"
+    mkdir -p $dir
+    echo "Created SDK path $dir"
+    echo "Moving libs"
+    cp -R $cur/lib $dir
+    echo "Moved libs"
+fi
+
+if [ -f "/etc/ld.so.conf.d/tflite.conf" ]; then
+    echo "/etc/ld.so.conf.d/tflite.conf exists"
+else
+    echo "Copy conf file"
+    cp $cur/tflite.conf /etc/ld.so.conf.d/
+    echo "Copied conf file"
+fi
+ldconfig
+echo "Done"
\ No newline at end of file
diff --git a/extensions/functions/tfLite/interpreters.go b/extensions/functions/tfLite/interpreters.go
new file mode 100644
index 0000000000..3fc7ce45d3
--- /dev/null
+++ b/extensions/functions/tfLite/interpreters.go
@@ -0,0 +1,79 @@
+// Copyright 2022-2024 EMQ Technologies Co., Ltd.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+//go:build tflite
+
+package main
+
+import (
+	"fmt"
+	"path/filepath"
+	"sync"
+
+	"github.com/mattn/go-tflite"
+
+	"github.com/lf-edge/ekuiper/v2/internal/conf"
+)
+
+var ipManager *interpreterManager
+
+func init() {
+	path, err := conf.GetDataLoc()
+	if err != nil {
+		panic(err)
+	}
+	ipManager = &interpreterManager{
+		registry: make(map[string]*tflite.Interpreter),
+		path:     filepath.Join(path, "uploads"),
+	}
+}
+
+type interpreterManager struct {
+	sync.Mutex
+	registry map[string]*tflite.Interpreter
+	path     string
+}
+
+func (m *interpreterManager) GetOrCreate(name string) (*tflite.Interpreter, error) {
+	log := conf.Log
+	m.Lock()
+	defer m.Unlock()
+	ip, ok := m.registry[name]
+	if !ok {
+		mf := filepath.Join(m.path, name+".tflite")
+		model := tflite.NewModelFromFile(mf)
+		if model == nil {
+			log.Errorf("fail to load model: %s", mf)
+			return nil, fmt.Errorf("fail to load model: %s", mf)
+		}
+		log.Infof("success load model: %s", mf)
+		defer model.Delete()
+		options := tflite.NewInterpreterOptions()
+		options.SetNumThread(4)
+		options.SetErrorReporter(func(msg string, user_data interface{}) {
+			fmt.Println(msg)
+		}, nil)
+		defer options.Delete()
+		ip = tflite.NewInterpreter(model, options)
+		status := ip.AllocateTensors()
+		if status != tflite.OK {
+			log.Errorf("allocate tensors failed for: %s", mf)
+			ip.Delete()
+			return nil, fmt.Errorf("allocate failed: %v", status)
+		}
+		log.Infof("success allocate tensors for: %s", mf)
+		m.registry[name] = ip
+	}
+	return ip, nil
+}
diff --git a/extensions/functions/tfLite/lib/Readme.md b/extensions/functions/tfLite/lib/Readme.md
new file mode 100644
index 0000000000..016b202dbc
--- /dev/null
+++ b/extensions/functions/tfLite/lib/Readme.md
@@ -0,0 +1,27 @@
+# Tensorflow Lite C API library
+
+This is the prebuilt tensorflow lite c library for debian 10. It can be used directly in eKuiper docker image of tags
+x.x.x or x.x.x-slim.
+
+To use in other environment, you need to build the library from source.
+
+## Build from source
+
+Here are the steps to build from source in debian.
+
+1. Install [Python](https://www.tensorflow.org/install/pip#1.-install-the-python-development-environment-on-your-system)
+
+2. Install required python lib: `pip3 install -r requirements.txt`. The requirements are
+   from `tensorflow/tensorflow/tools/pip_package/setup.py` of the corresponding tensorflow version.
+
+3. Install [Bazel](https://docs.bazel.build/versions/4.0.0/install-ubuntu.html)
+
+4. Clone [tensorflow](https://github.com/tensorflow/tensorflow)，switch to `git checkout v2.2.0-rc3 -b mybranch`
+
+5. Build the so files, the outputs are in ./bazel-bin
+
+   ```bash
+   $ cd $tensorflowSrc
+   $ bazel build --config monolithic -c opt //tensorflow/lite:libtensorflowlite.so
+   $ bazel build --config monolithic -c opt //tensorflow/lite/c:libtensorflowlite_c.so
+   ```
diff --git a/extensions/functions/tfLite/tfLite.go b/extensions/functions/tfLite/tfLite.go
new file mode 100644
index 0000000000..248adcd053
--- /dev/null
+++ b/extensions/functions/tfLite/tfLite.go
@@ -0,0 +1,184 @@
+// Copyright 2022-2024 EMQ Technologies Co., Ltd.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+//go:build tflite
+
+package main
+
+import (
+	"fmt"
+
+	"github.com/mattn/go-tflite"
+
+	"github.com/lf-edge/ekuiper/contract/v2/api"
+	"github.com/lf-edge/ekuiper/v2/pkg/cast"
+)
+
+type Tffunc struct{}
+
+// Validate the arguments.
+// args[0]: string, model name which maps to a path
+// args[1 to n]: tensors
+func (f *Tffunc) Validate(args []interface{}) error {
+	if len(args) < 2 {
+		return fmt.Errorf("tensorflow function must have at least 2 parameters but got %d", len(args))
+	}
+	return nil
+}
+
+func (f *Tffunc) IsAggregate() bool {
+	return false
+}
+
+func (f *Tffunc) Exec(args []interface{}, ctx api.FunctionContext) (interface{}, bool) {
+	model, ok := args[0].(string)
+	if !ok {
+		return fmt.Errorf("tensorflow function first parameter must be a string, but got %[1]T(%[1]v)", args[0]), false
+	}
+	interpreter, err := ipManager.GetOrCreate(model)
+	if err != nil {
+		return err, false
+	}
+	inputCount := interpreter.GetInputTensorCount()
+	if len(args)-1 != inputCount {
+		return fmt.Errorf("tensorflow function requires %d tensors but got %d", inputCount, len(args)-1), false
+	}
+
+	ctx.GetLogger().Debugf("tensorflow function %s with %d tensors", model, inputCount)
+	// Set input tensors
+	for i := 1; i < len(args); i++ {
+		input := interpreter.GetInputTensor(i - 1)
+		var arg []interface{}
+		switch v := args[i].(type) {
+		case []byte:
+			if int(input.ByteSize()) != len(v) {
+				return fmt.Errorf("tensorflow function input tensor %d has %d bytes but got %d", i-1, input.ByteSize(), len(v)), false
+			}
+			input.CopyFromBuffer(v)
+			continue
+		case []interface{}: // only supports one dimensional arg. Even dim 0 must be an array of 1 element
+			arg = v
+		default:
+			return fmt.Errorf("tensorflow function parameter %d must be a bytea or array of bytea, but got %[1]T(%[1]v)", i), false
+		}
+		paraLen := 1
+		for j := 0; j < input.NumDims(); j++ {
+			paraLen = paraLen * input.Dim(j)
+		}
+		ctx.GetLogger().Debugf("receive tensor %v, require %d length", arg, paraLen)
+		if paraLen != len(arg) {
+			return fmt.Errorf("tensorflow function input tensor %d must have %d elements but got %d", i-1, paraLen, len(arg)), false
+		}
+		switch input.Type() {
+		case tflite.Float32:
+			v, err := cast.ToFloat32Slice(arg, cast.CONVERT_SAMEKIND)
+			if err != nil {
+				return fmt.Errorf("invalid %d parameter, expect float32 but got %[2]T(%[2]v) with err %v", i, args[i], err), false
+			}
+			err = input.SetFloat32s(v)
+			if err != nil {
+				return nil, false
+			}
+		case tflite.Int64:
+			v, err := cast.ToInt64Slice(arg, cast.CONVERT_SAMEKIND)
+			if err != nil {
+				return fmt.Errorf("invalid %d parameter, expect int64 but got %[2]T(%[2]v) with err %v", i, args[i], err), false
+			}
+			err = input.SetInt64s(v)
+			if err != nil {
+				return nil, false
+			}
+		case tflite.Int32:
+			v, err := cast.ToTypedSlice(args, func(input interface{}, sn cast.Strictness) (interface{}, error) {
+				return cast.ToInt32(input, sn)
+			}, "int32", cast.CONVERT_SAMEKIND)
+			if err != nil {
+				return fmt.Errorf("invalid %d parameter, expect int32 but got %[2]T(%[2]v) with err %v", i, args[i], err), false
+			}
+			err = input.SetInt32s(v.([]int32))
+			if err != nil {
+				return nil, false
+			}
+		case tflite.Int16:
+			v, err := cast.ToTypedSlice(args, func(input interface{}, sn cast.Strictness) (interface{}, error) {
+				return cast.ToInt16(input, sn)
+			}, "int16", cast.CONVERT_SAMEKIND)
+			if err != nil {
+				return fmt.Errorf("invalid %d parameter, expect int16 but got %[2]T(%[2]v) with err %v", i, args[i], err), false
+			}
+			err = input.SetInt16s(v.([]int16))
+			if err != nil {
+				return nil, false
+			}
+		case tflite.Int8:
+			v, err := cast.ToTypedSlice(args, func(input interface{}, sn cast.Strictness) (interface{}, error) {
+				return cast.ToInt8(input, sn)
+			}, "int8", cast.CONVERT_SAMEKIND)
+			if err != nil {
+				return fmt.Errorf("invalid %d parameter, expect int8 but got %[2]T(%[2]v) with err %v", i, args[i], err), false
+			}
+			err = input.SetInt8s(v.([]int8))
+			if err != nil {
+				return nil, false
+			}
+		case tflite.UInt8:
+			v, err := cast.ToBytes(args, cast.CONVERT_SAMEKIND)
+			if err != nil {
+				return fmt.Errorf("invalid %d parameter, expect uint8 but got %[2]T(%[2]v) with err %v", i, args[i], err), false
+			}
+			err = input.SetUint8s(v)
+			if err != nil {
+				return nil, false
+			}
+		default:
+			return fmt.Errorf("invalid %d parameter, unsupported type %v in the model", i, input.Type()), false
+		}
+	}
+	status := interpreter.Invoke()
+	if status != tflite.OK {
+		return fmt.Errorf("invoke failed"), false
+	}
+	outputCount := interpreter.GetOutputTensorCount()
+	results := make([]interface{}, outputCount)
+	for i := 0; i < outputCount; i++ {
+		output := interpreter.GetOutputTensor(i)
+		//outputSize := output.Dim(output.NumDims() - 1)
+		//b := make([]byte, outputSize)
+		//status = output.CopyToBuffer(&b[0])
+		//if status != tflite.OK {
+		//	return fmt.Errorf("output failed"), false
+		//}
+		//results[i] = b
+		t := output.Type()
+		switch t {
+		case tflite.Float32:
+			results[i] = output.Float32s()
+		case tflite.Int64:
+			results[i] = output.Int64s()
+		case tflite.Int32:
+			results[i] = output.Int32s()
+		case tflite.Int16:
+			results[i] = output.Int16s()
+		case tflite.Int8:
+			results[i] = output.Int8s()
+		case tflite.UInt8:
+			results[i] = output.UInt8s()
+		default:
+			return fmt.Errorf("invalid %d parameter, unsupported type %v in the model", i, t), false
+		}
+	}
+	return results, true
+}
+
+var TfLite Tffunc
diff --git a/extensions/functions/tfLite/tfLite.json b/extensions/functions/tfLite/tfLite.json
new file mode 100644
index 0000000000..86d48ddec9
--- /dev/null
+++ b/extensions/functions/tfLite/tfLite.json
@@ -0,0 +1,77 @@
+{
+  "about": {
+    "trial": false,
+    "author": {
+      "name": "EMQ",
+      "email": "contact@emqx.io",
+      "company": "EMQ Technologies Co., Ltd",
+      "website": "https://www.emqx.io"
+    },
+    "helpUrl": {
+      "en_US": "https://ekuiper.org/docs/en/latest/sqls/functions/custom_functions.html",
+      "zh_CN": "https://ekuiper.org/docs/zh/latest/sqls/functions/custom_functions.html"
+    },
+    "description": {
+      "en_US": "General Tensorflow lite plugin which can infer any tflite model dynamically",
+      "zh_CN": "通用的 TensorFlow Lite 插件，可以动态推断任何 tflite 模型。"
+    }
+  },
+  "name": "tfLite",
+  "functions": [
+    {
+      "name": "tfLite",
+      "example": "tfLite(model,para1, para2,...)",
+      "hint": {
+        "en_US": "Select AI model in runtime and infer the stream data",
+        "zh_CN": "动态选择模型进行推断"
+      },
+      "args": [
+        {
+          "name": "model",
+          "hidden": false,
+          "optional": false,
+          "control": "text",
+          "type": "string",
+          "hint": {
+            "en_US": "Input data",
+            "zh_CN": "输入模型"
+          },
+          "label": {
+            "en_US": "Model Name",
+            "zh_CN": "模型名称"
+          }
+        },
+        {
+          "name": "fields",
+          "default": "",
+          "optional": false,
+          "control": "list",
+          "type": "list_string",
+          "hint": {
+            "en_US": "select parameter fields",
+            "zh_CN": "选取参数字段"
+          },
+          "label": {
+            "en_US": "Parameter Fields",
+            "zh_CN": "参数字段"
+          }
+        }
+      ],
+      "return": {
+        "type": "array",
+        "hint": {
+          "en_US": "Inferred result",
+          "zh_CN": "推理结果"
+        }
+      },
+      "node": {
+        "category": "function",
+        "icon": "iconPath",
+        "label": {
+          "en_US": "Tensorflow Lite",
+          "zh_CN": "Tensorflow Lite"
+        }
+      }
+    }
+  ]
+}
diff --git a/extensions/functions/tfLite/tfLite_test.go b/extensions/functions/tfLite/tfLite_test.go
new file mode 100644
index 0000000000..73ee1331c8
--- /dev/null
+++ b/extensions/functions/tfLite/tfLite_test.go
@@ -0,0 +1,95 @@
+// Copyright 2022-2024 EMQ Technologies Co., Ltd.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+//go:build tflite
+
+package main
+
+import (
+	"reflect"
+	"testing"
+
+	"github.com/lf-edge/ekuiper/contract/v2/api"
+	"github.com/lf-edge/ekuiper/v2/internal/conf"
+	"github.com/lf-edge/ekuiper/v2/internal/pkg/def"
+	kctx "github.com/lf-edge/ekuiper/v2/internal/topo/context"
+	"github.com/lf-edge/ekuiper/v2/internal/topo/state"
+)
+
+func TestTffunc_Exec(t *testing.T) {
+	contextLogger := conf.Log.WithField("rule", "testExec")
+	ctx := kctx.WithValue(kctx.Background(), kctx.LoggerKey, contextLogger)
+	tempStore, _ := state.CreateStore("mockRule0", def.AtMostOnce)
+	fctx := kctx.NewDefaultFuncContext(ctx.WithMeta("mockRule0", "test", tempStore), 2)
+
+	type args struct {
+		args []interface{}
+		ctx  api.FunctionContext
+	}
+	tests := []struct {
+		name  string
+		args  args
+		want  interface{}
+		want1 bool
+	}{
+		{
+			name: "fizzbuzz",
+			args: args{
+				args: []interface{}{
+					"fizzbuzz_model",
+					[]interface{}{1, 2, 3, 4, 5, 6, 7},
+				},
+				ctx: fctx,
+			},
+			want:  []interface{}{[]float32{0.9971661, 4.145413e-05, 0.0027840463, 8.373417e-06}},
+			want1: true,
+		},
+		{
+			name: "sin",
+			args: args{
+				args: []interface{}{
+					"sin_model",
+					[]interface{}{1},
+				},
+				ctx: fctx,
+			},
+			want:  []interface{}{[]float32{0.86996967}},
+			want1: true,
+		},
+		{
+			name: "xor",
+			args: args{
+				args: []interface{}{
+					"xor_model",
+					[]interface{}{1, 0},
+				},
+				ctx: fctx,
+			},
+			want:  []interface{}{[]float32{0.9586827}},
+			want1: true,
+		},
+	}
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			f := &Tffunc{}
+			got, got1 := f.Exec(tt.args.args, tt.args.ctx)
+			if !reflect.DeepEqual(got, tt.want) {
+				t.Errorf("Exec() got = %v, want %v", got, tt.want)
+			}
+			if got1 != tt.want1 {
+				t.Errorf("Exec() got1 = %v, want %v", got1, tt.want1)
+			}
+		})
+	}
+}
diff --git a/extensions/functions/tfLite/tflite.conf b/extensions/functions/tfLite/tflite.conf
new file mode 100644
index 0000000000..df0b739082
--- /dev/null
+++ b/extensions/functions/tfLite/tflite.conf
@@ -0,0 +1,2 @@
+# include tflite c api
+/usr/local/tflite/lib
\ No newline at end of file
diff --git a/go.mod b/go.mod
index 67620a9c41..acb935e7cb 100644
--- a/go.mod
+++ b/go.mod
@@ -31,11 +31,13 @@ require (
 	github.com/keepeye/logrus-filename v0.0.0-20190711075016-ce01a4391dd1
 	github.com/klauspost/compress v1.17.7
 	github.com/lf-edge/ekuiper/contract/v2 v2.0.0-alpha.3
+	github.com/mattn/go-tflite v1.0.5
 	github.com/mitchellh/mapstructure v1.5.0
 	github.com/mochi-mqtt/server/v2 v2.6.4
 	github.com/modern-go/reflect2 v1.0.2
 	github.com/montanaflynn/stats v0.7.1
 	github.com/msgpack-rpc/msgpack-rpc-go v0.0.0-20131026060856-c76397e1782b
+	github.com/nfnt/resize v0.0.0-20180221191011-83c6a9932646
 	github.com/pebbe/zmq4 v1.2.11
 	github.com/pingcap/failpoint v0.0.0-20220801062533-2eaa32854a6c
 	github.com/prometheus/client_golang v1.19.0
@@ -105,6 +107,7 @@ require (
 	github.com/leodido/go-urn v1.4.0 // indirect
 	github.com/lestrrat-go/strftime v1.0.6 // indirect
 	github.com/mattn/go-isatty v0.0.20 // indirect
+	github.com/mattn/go-pointer v0.0.1 // indirect
 	github.com/mitchellh/copystructure v1.2.0 // indirect
 	github.com/mitchellh/reflectwalk v1.0.2 // indirect
 	github.com/msgpack/msgpack-go v0.0.0-20130625150338-8224460e6fa3 // indirect
diff --git a/go.sum b/go.sum
index 4d965e8bfa..2178bf9d2a 100644
--- a/go.sum
+++ b/go.sum
@@ -352,9 +352,13 @@ github.com/mattn/go-isatty v0.0.3/go.mod h1:M+lRXTBqGeGNdLjl/ufCoiOlB5xdOkqRJdNx
 github.com/mattn/go-isatty v0.0.4/go.mod h1:M+lRXTBqGeGNdLjl/ufCoiOlB5xdOkqRJdNxMWT7Zi4=
 github.com/mattn/go-isatty v0.0.20 h1:xfD0iDuEKnDkl03q4limB+vH+GxLEtL/jb4xVJSWWEY=
 github.com/mattn/go-isatty v0.0.20/go.mod h1:W+V8PltTTMOvKvAeJH7IuucS94S2C6jfK/D7dTCTo3Y=
+github.com/mattn/go-pointer v0.0.1 h1:n+XhsuGeVO6MEAp7xyEukFINEa+Quek5psIR/ylA6o0=
+github.com/mattn/go-pointer v0.0.1/go.mod h1:2zXcozF6qYGgmsG+SeTZz3oAbFLdD3OWqnUbNvJZAlc=
 github.com/mattn/go-runewidth v0.0.2/go.mod h1:LwmH8dsx7+W8Uxz3IHJYH5QSwggIsqBzpuz5H//U1FU=
 github.com/mattn/go-sqlite3 v1.14.22 h1:2gZY6PC6kBnID23Tichd1K+Z0oS6nE/XwU+Vz/5o4kU=
 github.com/mattn/go-sqlite3 v1.14.22/go.mod h1:Uh1q+B4BYcTPb+yiD3kU8Ct7aC0hY9fxUwlHK0RXw+Y=
+github.com/mattn/go-tflite v1.0.5 h1:UOByIpeNtY9urOeID5zBMJBrQfZjT6SO4+CLAzSREWw=
+github.com/mattn/go-tflite v1.0.5/go.mod h1:j7bVlVHgKURK0p7AQOw3OqlGE2SVXqck7JsJo4wI+bc=
 github.com/matttproud/golang_protobuf_extensions v1.0.1/go.mod h1:D8He9yQNgCq6Z5Ld7szi9bcBfOoFv/3dc6xSMkL2PC0=
 github.com/miekg/dns v1.0.14/go.mod h1:W1PPwlIAgtquWBMBEV9nkV9Cazfe8ScdGz/Lj7v3Nrg=
 github.com/mitchellh/cli v1.0.0/go.mod h1:hNIlj7HEI86fIcpObd7a0FcrxTWetlwJDGcceTlRvqc=
@@ -401,6 +405,8 @@ github.com/nats-io/nuid v1.0.1 h1:5iA8DT8V7q8WK2EScv2padNa/rTESc1KdnPw4TC2paw=
 github.com/nats-io/nuid v1.0.1/go.mod h1:19wcPz3Ph3q0Jbyiqsd0kePYG7A95tJPxeL+1OSON2c=
 github.com/ncruces/go-strftime v0.1.9 h1:bY0MQC28UADQmHmaF5dgpLmImcShSi2kHU9XLdhx/f4=
 github.com/ncruces/go-strftime v0.1.9/go.mod h1:Fwc5htZGVVkseilnfgOVb9mKy6w1naJmn9CehxcKcls=
+github.com/nfnt/resize v0.0.0-20180221191011-83c6a9932646 h1:zYyBkD/k9seD2A7fsi6Oo2LfFZAehjjQMERAvZLEDnQ=
+github.com/nfnt/resize v0.0.0-20180221191011-83c6a9932646/go.mod h1:jpp1/29i3P1S/RLdc7JQKbRpFeM1dOBd8T9ki5s+AY8=
 github.com/nxadm/tail v1.4.4/go.mod h1:kenIhsEOeOJmVchQTgglprH7qJGnHDVpk1VPCcaMI8A=
 github.com/nxadm/tail v1.4.8/go.mod h1:+ncqLTQzXmGhMZNUePPaPqPvBxHAIsmXswZKocGu+AU=
 github.com/nxadm/tail v1.4.11 h1:8feyoE3OzPrcshW5/MJ4sGESc5cqmGkGCWlco4l0bqY=