From 3c148920be7d32f6e154418ac57b1984846bca6f Mon Sep 17 00:00:00 2001
From: Morgan Diverrez <morgan.diverrez@arkea.com>
Date: Thu, 15 Aug 2024 17:53:41 +0200
Subject: [PATCH] [DERCBOT-1173] RAG Evaluation - langfuse

---
 .../src/main/python/server/poetry.lock        | 1794 +++++++++--------
 .../src/main/python/server/pyproject.toml     |    2 +-
 .../tock-llm-indexing-tools/.env.exemple      |   11 +
 .../python/tock-llm-indexing-tools/README.md  |   41 +-
 .../docs/rag_testing_tools.png                |  Bin 335967 -> 32136 bytes
 .../export_run_results.py                     |  423 ++--
 .../generate_dataset.py                       |  179 +-
 .../tock-llm-indexing-tools/poetry.lock       |  173 +-
 .../tock-llm-indexing-tools/pyproject.toml    |   19 +-
 .../rag_testing_tool.py                       |  112 +-
 .../ragquery.json.example                     |   55 +
 11 files changed, 1593 insertions(+), 1216 deletions(-)
 create mode 100644 gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/.env.exemple
 create mode 100644 gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/ragquery.json.example

diff --git a/gen-ai/orchestrator-server/src/main/python/server/poetry.lock b/gen-ai/orchestrator-server/src/main/python/server/poetry.lock
index fe970127ea..df9c919877 100644
--- a/gen-ai/orchestrator-server/src/main/python/server/poetry.lock
+++ b/gen-ai/orchestrator-server/src/main/python/server/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
 
 [[package]]
 name = "aiohappyeyeballs"
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 optional = false
 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
@@ -150,13 +150,13 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.6.0"
+version = "4.6.2.post1"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
 python-versions = ">=3.9"
 files = [
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-    {file = "anyio-4.6.0.tar.gz", hash = "sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb"},
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 ]
 
 [package.dependencies]
@@ -167,7 +167,7 @@ typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"]
 trio = ["trio (>=0.26.1)"]
 
 [[package]]
@@ -267,17 +267,17 @@ files = [
 
 [[package]]
 name = "boto3"
-version = "1.35.37"
+version = "1.35.54"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
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+botocore = ">=1.35.54,<1.36.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -286,13 +286,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.35.37"
+version = "1.35.54"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -509,13 +509,13 @@ files = [
 
 [[package]]
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-version = "6.8.2"
+version = "6.9.0"
 description = "Add colours to the output of Python's logging module."
 optional = false
 python-versions = ">=3.6"
 files = [
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 [package.dependencies]
@@ -526,73 +526,73 @@ development = ["black", "flake8", "mypy", "pytest", "types-colorama"]
 
 [[package]]
 name = "coverage"
-version = "7.6.2"
+version = "7.6.4"
 description = "Code coverage measurement for Python"
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 python-versions = ">=3.9"
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 [[package]]
 name = "google-api-core"
-version = "2.21.0"
+version = "2.22.0"
 description = "Google API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -868,7 +883,10 @@ grpcio-status = [
     {version = ">=1.49.1,<2.0.dev0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
     {version = ">=1.33.2,<2.0.dev0", optional = true, markers = "python_version < \"3.11\" and extra == \"grpc\""},
 ]
-proto-plus = ">=1.22.3,<2.0.0dev"
+proto-plus = [
+    {version = ">=1.22.3,<2.0.0dev", markers = "python_version < \"3.13\""},
+    {version = ">=1.25.0,<2.0.0dev", markers = "python_version >= \"3.13\""},
+]
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
 requests = ">=2.18.0,<3.0.0.dev0"
 
@@ -903,20 +921,23 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-secret-manager"
-version = "2.20.2"
+version = "2.21.0"
 description = "Google Cloud Secret Manager API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
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 google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0dev"
 grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
-proto-plus = ">=1.22.3,<2.0.0dev"
+proto-plus = [
+    {version = ">=1.22.3,<2.0.0dev", markers = "python_version < \"3.13\""},
+    {version = ">=1.25.0,<2.0.0dev", markers = "python_version >= \"3.13\""},
+]
 protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0dev"
 
 [[package]]
@@ -1041,85 +1062,85 @@ protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4
 
 [[package]]
 name = "grpcio"
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+version = "1.67.1"
 description = "HTTP/2-based RPC framework"
 optional = false
 python-versions = ">=3.8"
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-version = "1.66.2"
+version = "1.67.1"
 description = "Status proto mapping for gRPC"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
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-grpcio = ">=1.66.2"
+grpcio = ">=1.67.1"
 protobuf = ">=5.26.1,<6.0dev"
 
 [[package]]
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+[[package]]
+name = "httpx-sse"
+version = "0.4.0"
+description = "Consume Server-Sent Event (SSE) messages with HTTPX."
+optional = false
+python-versions = ">=3.8"
+files = [
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+
 [[package]]
 name = "identify"
 version = "2.6.1"
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 [[package]]
@@ -1452,19 +1484,19 @@ referencing = ">=0.31.0"
 
 [[package]]
 name = "langchain"
-version = "0.3.3"
+version = "0.3.7"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
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 async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
-langchain-core = ">=0.3.10,<0.4.0"
+langchain-core = ">=0.3.15,<0.4.0"
 langchain-text-splitters = ">=0.3.0,<0.4.0"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = [
@@ -1475,24 +1507,25 @@ pydantic = ">=2.7.4,<3.0.0"
 PyYAML = ">=5.3"
 requests = ">=2,<3"
 SQLAlchemy = ">=1.4,<3"
-tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
 [[package]]
 name = "langchain-community"
-version = "0.3.2"
+version = "0.3.4"
 description = "Community contributed LangChain integrations."
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
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-langchain = ">=0.3.3,<0.4.0"
-langchain-core = ">=0.3.10,<0.4.0"
+httpx-sse = ">=0.4.0,<0.5.0"
+langchain = ">=0.3.6,<0.4.0"
+langchain-core = ">=0.3.14,<0.4.0"
 langsmith = ">=0.1.125,<0.2.0"
 numpy = [
     {version = ">=1,<2", markers = "python_version < \"3.12\""},
@@ -1502,17 +1535,17 @@ pydantic-settings = ">=2.4.0,<3.0.0"
 PyYAML = ">=5.3"
 requests = ">=2,<3"
 SQLAlchemy = ">=1.4,<3"
-tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
 [[package]]
 name = "langchain-core"
-version = "0.3.10"
+version = "0.3.15"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -1524,23 +1557,23 @@ pydantic = [
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 ]
 PyYAML = ">=5.3"
-tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0"
 typing-extensions = ">=4.7"
 
 [[package]]
 name = "langchain-openai"
-version = "0.2.2"
+version = "0.2.5"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
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 [package.dependencies]
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-openai = ">=1.40.0,<2.0.0"
+langchain-core = ">=0.3.15,<0.4.0"
+openai = ">=1.52.0,<2.0.0"
 tiktoken = ">=0.7,<1"
 
 [[package]]
@@ -1564,35 +1597,34 @@ sqlalchemy = ">=2,<3"
 
 [[package]]
 name = "langchain-text-splitters"
-version = "0.3.0"
+version = "0.3.2"
 description = "LangChain text splitting utilities"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.0,<0.4.0"
+langchain-core = ">=0.3.15,<0.4.0"
 
 [[package]]
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-version = "2.52.0"
+version = "2.36.2"
 description = "A client library for accessing langfuse"
 optional = false
 python-versions = "<4.0,>=3.8.1"
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 idna = ">=3.7,<4.0"
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+packaging = ">=23.2,<24.0"
 pydantic = ">=1.10.7,<3.0"
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@@ -1603,13 +1635,13 @@ openai = ["openai (>=0.27.8)"]
 
 [[package]]
 name = "langsmith"
-version = "0.1.133"
+version = "0.1.139"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
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 [package.dependencies]
@@ -1624,13 +1656,13 @@ requests-toolbelt = ">=1.0.0,<2.0.0"
 
 [[package]]
 name = "license-expression"
-version = "30.3.1"
+version = "30.4.0"
 description = "license-expression is a comprehensive utility library to parse, compare, simplify and normalize license expressions (such as SPDX license expressions) using boolean logic."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
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 ]
 
 [package.dependencies]
@@ -1820,92 +1852,92 @@ testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
 
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 description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
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 [package.dependencies]
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 [package.extras]
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+tests = ["pytest", "simplejson"]
 
 [[package]]
 name = "mdurl"
@@ -2164,13 +2196,13 @@ files = [
 
 [[package]]
 name = "openai"
-version = "1.51.2"
+version = "1.53.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
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 ]
 
 [package.dependencies]
@@ -2212,79 +2244,80 @@ kerberos = ["requests-kerberos"]
 
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 [[package]]
 name = "packageurl-python"
-version = "0.15.6"
+version = "0.16.0"
 description = "A purl aka. Package URL parser and builder"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -2295,13 +2328,13 @@ test = ["pytest"]
 
 [[package]]
 name = "packaging"
-version = "24.1"
+version = "23.2"
 description = "Core utilities for Python packages"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.7"
 files = [
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 ]
 
 [[package]]
@@ -2345,13 +2378,13 @@ numpy = "*"
 
 [[package]]
 name = "pip"
-version = "24.2"
+version = "24.3.1"
 description = "The PyPA recommended tool for installing Python packages."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -2573,13 +2606,13 @@ files = [
 
 [[package]]
 name = "proto-plus"
-version = "1.24.0"
+version = "1.25.0"
 description = "Beautiful, Pythonic protocol buffers."
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -2590,22 +2623,22 @@ testing = ["google-api-core (>=1.31.5)"]
 
 [[package]]
 name = "protobuf"
-version = "5.28.2"
+version = "5.28.3"
 description = ""
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -2884,13 +2917,13 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pydantic-settings"
-version = "2.5.2"
+version = "2.6.1"
 description = "Settings management using Pydantic"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2918,13 +2951,13 @@ windows-terminal = ["colorama (>=0.4.6)"]
 
 [[package]]
 name = "pyparsing"
-version = "3.1.4"
+version = "3.2.0"
 description = "pyparsing module - Classes and methods to define and execute parsing grammars"
 optional = false
-python-versions = ">=3.6.8"
+python-versions = ">=3.9"
 files = [
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 ]
 
 [package.extras]
@@ -2932,22 +2965,22 @@ diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
 name = "pyproject-api"
-version = "1.8.0"
+version = "1.6.1"
 description = "API to interact with the python pyproject.toml based projects"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-packaging = ">=24.1"
+packaging = ">=23.1"
 tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-docs = ["furo (>=2024.8.6)", "sphinx-autodoc-typehints (>=2.4.1)"]
-testing = ["covdefaults (>=2.3)", "pytest (>=8.3.3)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "setuptools (>=75.1)"]
+docs = ["furo (>=2023.8.19)", "sphinx (<7.2)", "sphinx-autodoc-typehints (>=1.24)"]
+testing = ["covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)", "setuptools (>=68.1.2)", "wheel (>=0.41.2)"]
 
 [[package]]
 name = "pytest"
@@ -3259,13 +3292,13 @@ files = [
 
 [[package]]
 name = "rich"
-version = "13.9.2"
+version = "13.9.4"
 description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
 optional = false
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -3278,114 +3311,114 @@ jupyter = ["ipywidgets (>=7.5.1,<9)"]
 
 [[package]]
 name = "rpds-py"
-version = "0.20.0"
+version = "0.20.1"
 description = "Python bindings to Rust's persistent data structures (rpds)"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3520,7 +3561,7 @@ aioodbc = ["aioodbc", "greenlet (!=0.4.17)"]
 aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"]
 asyncio = ["greenlet (!=0.4.17)"]
 asyncmy = ["asyncmy (>=0.2.3,!=0.2.4,!=0.2.6)", "greenlet (!=0.4.17)"]
-mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5)"]
+mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2,!=1.1.5,!=1.1.10)"]
 mssql = ["pyodbc"]
 mssql-pymssql = ["pymssql"]
 mssql-pyodbc = ["pyodbc"]
@@ -3541,13 +3582,13 @@ sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
 name = "starlette"
-version = "0.38.6"
+version = "0.41.2"
 description = "The little ASGI library that shines."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3572,13 +3613,13 @@ pbr = ">=2.0.0"
 
 [[package]]
 name = "tenacity"
-version = "8.5.0"
+version = "9.0.0"
 description = "Retry code until it succeeds"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -3656,41 +3697,40 @@ files = [
 
 [[package]]
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-version = "4.21.2"
+version = "4.15.1"
 description = "tox is a generic virtualenv management and test command line tool"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
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-filelock = ">=3.16.1"
-packaging = ">=24.1"
-platformdirs = ">=4.3.6"
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-typing-extensions = {version = ">=4.12.2", markers = "python_version < \"3.11\""}
-virtualenv = ">=20.26.6"
+virtualenv = ">=20.25"
 
 [package.extras]
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 [[package]]
 name = "tqdm"
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 description = "Fast, Extensible Progress Meter"
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 python-versions = ">=3.7"
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 [package.dependencies]
@@ -3802,13 +3842,13 @@ standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)",
 
 [[package]]
 name = "virtualenv"
-version = "20.26.6"
+version = "20.27.1"
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 [package.dependencies]
@@ -3927,103 +3967,93 @@ files = [
 
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 ]
 
 [package.dependencies]
@@ -4034,4 +4064,4 @@ propcache = ">=0.2.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "774a13ff8d9141f3c63c64464c18d7854fff45abfa362c59763faf4b499a7583"
+content-hash = "078835fe73f24f237538b2bcfe274972cf3e2a6828e4bc34976a5c3b0dd25190"
diff --git a/gen-ai/orchestrator-server/src/main/python/server/pyproject.toml b/gen-ai/orchestrator-server/src/main/python/server/pyproject.toml
index 6e72e2dabb..586b973b26 100644
--- a/gen-ai/orchestrator-server/src/main/python/server/pyproject.toml
+++ b/gen-ai/orchestrator-server/src/main/python/server/pyproject.toml
@@ -21,7 +21,7 @@ colorlog = "^6.8.2"
 boto3 = "^1.35.37"
 urllib3 = "^2.2.3"
 jinja2 = "^3.1.4"
-langfuse = "^2.52.0"
+langfuse = "2.36.2"
 httpx-auth-awssigv4 = "^0.1.4"
 langchain-postgres = "^0.0.12"
 google-cloud-secret-manager = "^2.20.2"
diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/.env.exemple b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/.env.exemple
new file mode 100644
index 0000000000..e6138c9bf9
--- /dev/null
+++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/.env.exemple
@@ -0,0 +1,11 @@
+#for LangFuse dataset provider
+LANGFUSE_SECRET_KEY=
+LANGFUSE_PUBLIC_KEY=
+LANGFUSE_HOST=
+
+# for LangsSmith dataset_provider
+LANGCHAIN_API_KEY=
+
+# for smarttribune_consumer.py script
+API_KEY=
+API_SECRET=
\ No newline at end of file
diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/README.md b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/README.md
index 621107de9b..6dc72845a5 100644
--- a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/README.md
+++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/README.md
@@ -205,12 +205,12 @@ To configure the default vector store, you can use the following environment var
 
 ### generate_dataset.py
 
-Generates a testing dataset based on an input file. The input file should have the correct format (see generate_datset_input.xlsx for sample). The generated dataset can be saved on filesystem, using the --csv-output option, on langsmith, using the --langsmith-dataset-name option, or both.
+Generates a testing dataset based on an input file. The input file should have the correct format (see generate_datset_input.xlsx for sample). The generated dataset can be saved on filesystem, using the --csv-output option, on langsmith, using the --langsmith-dataset-name option, on langfuse using the --langfuse-dataset-name option, or both.
 
 ```
 Usage:
-    generate_dataset.py [-v] <input_excel> --range=<s> [--csv-output=<path>] [ --langsmith-dataset-name=<name> ] [--locale=<locale>] [--no-answer=<na>]
-    generate_dataset.py [-v] <input_excel> --sheet=<n>... [--csv-output=<path>] [ --langsmith-dataset-name=<name> ] [--locale=<locale>] [--no-answer=<na>]
+    generate_dataset.py [-v] <input_excel> --range=<s> [--csv-output=<path>] [ --langsmith-dataset-name=<name> ] [ --langfuse-dataset-name=<name> ] [--locale=<locale>] [--no-answer=<na>]
+    generate_dataset.py [-v] <input_excel> --sheet=<n>... [--csv-output=<path>] [ --langsmith-dataset-name=<name> ] [ --langfuse-dataset-name=<name> ] [--locale=<locale>] [--no-answer=<na>]
 
 Arguments:
     input_excel path to the input excel file
@@ -220,22 +220,22 @@ Options:
     --sheet=<n>                     Sheet numbers to be parsed. Indices are 0-indexed.
     --csv-output=<path>             Output path of csv file to be generated.
     --langsmith-dataset-name=<name> Name of the dataset to be saved on langsmith.
+    --langfuse-dataset-name=<name> Name of the dataset to be saved on langfuse.
     --locale=<locale>               Locale to be included in de dataset. [default: French]
     --no-answer=<na>                Label of no_answer to be included in the dataset. [default: NO_RAG_SENTENCE]
     -h --help                       Show this screen
     --version                       Show version
     -v                              Verbose output for debugging (without this option, script will be silent but for errors)
-
-Generates a testing dataset based on an input file. The input file should have the correct format (see generate_datset_input.xlsx for sample). The generated dataset can be saved on filesystem, using the --csv-output option, on langsmith, using the --langsmith-dataset-name option, or both.
+Generates a testing dataset based on an input file. The input file should have the correct format (see generate_datset_input.xlsx for sample). The generated dataset can be saved on filesystem, using the --csv-output option, on langsmith, using the --langsmith-dataset-name option, on langfuse using the --langfuse-dataset-name option, or both.
 ```
 
 ### rag_testing_tool.py
 
-Retrieval-Augmented Generation (RAG) endpoint settings testing tool based on LangSmith's SDK: runs a specific RAG Settings configuration against a reference dataset.
+Retrieval-Augmented Generation (RAG) endpoint settings testing tool based on LangSmith's or LangFuse's SDK: runs a specific RAG Settings configuration against a reference dataset.
 
 ```
 Usage:
-    rag_testing_tool.py [-v] <rag_query> <dataset_name> <test_name> [<delay>]
+    rag_testing_tool.py [-v] <rag_query> <dataset_provider> <dataset_name> <test_name> [<delay>]
     rag_testing_tool.py -h | --help
     rag_testing_tool.py --version
 
@@ -245,6 +245,7 @@ Arguments:
                     provider, indexation session's unique id, and 'k', i.e. nb
                     of retrieved docs (question and chat history are ignored,
                     as they will come from the dataset)
+    dataset_provider the dataset provider (langsmith or langfuse)
     dataset_name    the reference dataset name
     test_name       name of the test run
 
@@ -256,7 +257,7 @@ Options:
                 be silent but for errors)
 ```
 
-Build a RAG (Lang)chain from the RAG Query and runs it against the provided LangSmith dataset. The chain is created anew for each entry of the dataset, and if a delay is provided each chain creation will be delayed accordingly.
+Build a RAG (Lang)chain from the RAG Query and runs it against the provided LangSmith or LangSmith dataset. The chain is created anew for each entry of the dataset, and if a delay is provided each chain creation will be delayed accordingly.
 ### export_run_results.py
 
 Export a LangSmith dataset run results, in csv format.
@@ -280,3 +281,27 @@ The exported CSV file will have these columns :
 'Reference input'|'Reference output'|'Response 1'|'Sources 1'|...|'Response N'|'Sources N'
 NB: There will be as many responses as run sessions
 ```
+
+### export_run_results_langfuse.py
+
+Export a LangFuse dataset run results, in csv format.
+
+```
+Usage:
+    export_run_results_langfuse.py [-v] <dataset_name> <runs_names>...
+    export_run_results_langfuse.py -h | --help
+    export_run_results_langfuse.py --version
+
+Arguments:
+    dataset_name      dataset id
+    runs_names     list of session ids
+
+Options:
+    -h --help   Show this screen
+    --version   Show version
+    -v          Verbose output for debugging
+
+The exported CSV file will have these columns :
+'Reference input'|'Reference output'|'Response 1'|'Sources 1'|...|'Response N'|'Sources N'
+NB: There will be as many responses as run sessions
+```
diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/docs/rag_testing_tools.png b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/docs/rag_testing_tools.png
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diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/export_run_results.py b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/export_run_results.py
index 6d80b1170d..7086a80b0d 100644
--- a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/export_run_results.py
+++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/export_run_results.py
@@ -1,99 +1,150 @@
-"""Export a LangSmith dataset run results.
-
+"""
+Export a LangSmith or LangFuse dataset run results.
 Usage:
-    export_run_results.py [-v] <dataset_id> <session_ids>...
-    export_run_results.py -h | --help
-    export_run_results.py --version
+        export_run_results_both.py [-v] <dataset_provider> <dataset_id_or_name> <session_or_run_ids>...
+        export_run_results_both.py -h | --help
+        export_run_results_both.py --version
 
 Arguments:
-    dataset_id      dataset id
-    session_ids     list of session ids
+    dataset_provider       specify either 'langfuse' or 'langsmith'
+    dataset_id_or_name     dataset id if langsmith or name if langfuse
+    session_or_run_ids     list of session or run ids
 
 Options:
+    -v          Verbose output
     -h --help   Show this screen
     --version   Show version
-    -v          Verbose output for debugging
+
 
 The exported CSV file will have these columns :
 'Reference input'|'Reference output'|'Response 1'|'Sources 1'|...|'Response N'|'Sources N'
 NB: There will be as many responses as run sessions
 """
+
 import csv
 import json
 import logging
 import os
+import sys
 import time
 
+import boto3
 import requests
 from docopt import docopt
+from dotenv import load_dotenv
+from gen_ai_orchestrator.configurations.environment.settings import application_settings
+from gen_ai_orchestrator.models.security.proxy_server_type import ProxyServerType
+from httpx_auth_awssigv4 import SigV4Auth
+from langfuse import Langfuse
 
+from generate_dataset import init_langfuse
 
-def first_true(iterable, predicate=None):
+
+# Function to create the CSV header, works for both providers
+def create_csv_header(_runs_names, provider, dataset_id):
     """
-    Returns the first element of the iterator that satisfies the given predicate
+    Create the CSV file header.
+    This function handles both LangFuse and LangSmith providers.
+
     Args:
-        iterable: the iterator
-        predicate: the predicate
+        _runs_names: List of run/session IDs.
+        provider: The provider being used (either 'langfuse' or 'langsmith').
+        dataset_id : dataset id for langsmith or dataset name for langfuse
 
-    Returns: element of the iterator
+    Returns:
+        The CSV file header as a list.
     """
-    return next(filter(predicate, iterable), None)
+    header_topic = 'Thématique de la question'
+    header_reference_input = 'Entrée de référence'
+    header_reference_output = 'Sortie de référence'
+    header_answer = 'Réponse'
+    header_sources = 'Sources'
 
+    csv_header = [header_topic, header_reference_input, header_reference_output]
 
-def get_session_name(_id: str, sessions) -> str:
-    """
-    Get session name.
-    Args:
-        _id: the session id
-        sessions: the sessions
+    if provider == 'langfuse':
+        counter = 1
+        for run_name in _runs_names:
+            csv_header.append(f"{header_answer} {counter} ({run_name})")
+            csv_header.append(f"{header_sources} {counter} ({run_name})")
+            counter += 1
+
+    elif provider == 'langsmith':
+        sessions_content = get_sessions(dataset_id)
+        counter = 1
+        for session_id in _runs_names:
+            session_name = get_session_name(session_id, sessions_content)
+            csv_header.append(f"{header_answer} {counter} ({session_name})")
+            csv_header.append(f"{header_sources} {counter} ({session_name})")
+            counter += 1
 
-    Returns: the session name
-    """
-    return first_true(sessions, predicate=lambda x: x['id'] == _id)['name']
+    return csv_header
 
 
-def create_csv_header(_session_ids: list[str]):
+# LangFuse-specific functions
+def fetch_trace_by_item_and_dataset_run(dataset_run, item):
     """
-    Create the CSV file header
+    Fetches the trace for a dataset item from a LangFuse dataset run.
+
     Args:
-        _session_ids: the session ids
+        dataset_run: The dataset run with items.
+        item: The dataset item.
 
-    Returns: the CSV file header
+    Returns:
+        Trace data if found, otherwise None.
     """
+    for item_run in dataset_run:
+        if item.id == item_run.dataset_item_id:
+            trace = client.get_trace(item_run.trace_id)
+            return trace
+    return None
 
-    # CSV Headers
-    header_topic = 'Thématique de la question'
-    header_reference_input = 'Entrée de référence'
-    header_reference_output = 'Sortie de référence'
-    header_answer = 'Réponse'
-    header_sources = 'Sources'
 
-    # Init csv header
-    csv_header = [header_topic, header_reference_input, header_reference_output]
+def append_runs_langfuse(dataset_item, _runs_names):
+    """
+    Append LangFuse run data to the CSV.
 
-    # Get sessions info
-    sessions_content = get_sessions(dataset_id)
+    Args:
+        dataset_item: The dataset item.
+        _runs_names: List of run names.
 
-    # Complete csv header with sessions name
-    counter = 1
-    for session_id in _session_ids:
-        session_name = get_session_name(session_id, sessions_content)
-        csv_header.append(f"{header_answer} {counter} ({session_name})")
-        csv_header.append(f"{header_sources} {counter} ({session_name})")
-        counter += 1
+    Returns:
+        A list representing a line in the CSV.
+    """
+    csv_line = [
+        dataset_item.metadata["topic"] if dataset_item.metadata else "",
+        dataset_item.input["question"],
+        dataset_item.expected_output["answer"]
+    ]
 
-    return csv_header
+    for _run_name in _runs_names:
+        dataset_run = client.get_dataset_run(dataset_name=dataset_name, dataset_run_name=_run_name)
+        trace = fetch_trace_by_item_and_dataset_run(dataset_run.dataset_run_items, dataset_item)
+        if trace is None or trace.output is None or not isinstance(trace.output, dict):
+            csv_line.append('')  # Empty if no trace is found
+            csv_line.append('')  # Empty for sources as well
+        else:
+            csv_line.append(trace.output["answer"])  # Append the answer
+            csv_line.append('\n\n'.join(
+                [f'[{doc["metadata"]["title"]}]({doc["metadata"]["source"]}) : {doc["page_content"]}'
+                 f'\n################################################################################'
+                 f'################################################################################' for doc in
+                 trace.output["source_documents"]]))
+
+    return csv_line
 
 
+# LangSmith-specific functions (restored)
 def get_sessions(_dataset_id):
     """
-    Fetch the dataset run sessions
+    Fetches the dataset run sessions for LangSmith.
+
     Args:
-        _dataset_id: the dataset id
+        _dataset_id: The dataset ID.
 
-    Returns: the dataset run sessions
+    Returns:
+        The sessions as a list.
     """
-
     logging.info(f'Call the LangSmith API to get run sessions for dataset_id={_dataset_id}.')
     sessions_response = requests.get(
         f'{base_url}/sessions?reference_dataset={_dataset_id}',
@@ -104,25 +155,70 @@ def get_sessions(_dataset_id):
         logging.debug(f"Number of example runs obtained = {len(sessions_content)}")
         return sessions_content
     else:
-        logging.error(f"Failed to get example runs. \n"
-                      f"Http code : {sessions_response.status_code} \n"
-                      f"Content   : {sessions_response.content}")
+        logging.error(
+            f"Failed to get example runs. \nHttp code: {sessions_response.status_code} \nContent: {sessions_response.content}")
         raise RuntimeError
 
 
-def get_dataset_examples(nb_example):
+def get_example_runs_content(example_id):
     """
-    Fetch the dataset examples
+    Fetch runs of an example
     Args:
-        nb_example: number of examples to fetch
+        example_id: the example id
 
-    Returns: the dataset examples
+    Returns: the runs
     """
 
+    logging.info(f'Call the LangSmith API to get dataset runs for the example_id={example_id}.')
+    example_runs_response = requests.post(
+        f'{base_url}/runs/query',
+        json={
+            "reference_example": [
+                example_id
+            ],
+            "is_root": "true",
+            "filter": "eq(is_root, true)",
+            "select": [
+                "status",
+                # "inputs",
+                "outputs",
+                "end_time",
+                "total_cost",
+                # "extra",
+                "feedback_stats",
+                "error"
+            ],
+            "limit": 15
+        },
+        headers={"x-api-key": _LANGSMITH_API_KEY},
+    )
+    if example_runs_response.status_code == 200:
+        example_runs_content = json.loads(example_runs_response.content)
+        logging.debug(f"Number of example runs obtained = {len(example_runs_content)}")
+        return example_runs_content
+    else:
+        logging.error(f"Failed to get example runs. \n"
+                      f"Http code : {example_runs_response.status_code} \n"
+                      f"Content   : {example_runs_response.content}")
+        raise RuntimeError
+
+
+# Restoring get_dataset_examples function for LangSmith
+def get_dataset_examples(nb_example, dataset_id):
+    """
+    Fetch the dataset examples from LangSmith.
+
+    Args:
+        nb_example: The number of examples to fetch.
+        dataset_id: The dataset ID to fetch examples for.
+
+    Returns:
+        The dataset examples.
+    """
     examples = []
     counter = nb_example
     offset = 0
-    limit = 100  # less_than_equal should be less than or equal to 100
+    limit = 100  # Less than or equal to 100
 
     while counter > 0:
         logging.info(f'Call the LangSmith API to get {limit} dataset examples, starting from {offset}.')
@@ -137,18 +233,64 @@ def get_dataset_examples(nb_example):
             logging.debug(f"Number of examples obtained = {len(dataset_examples_content)}")
             logging.debug(f"Number of examples collected = {len(examples)}/{nb_example}")
         else:
-            logging.error(f"Failed to get dataset examples. \n"
-                          f"Http code : {dataset_examples_response.status_code} \n"
-                          f"Content   : {dataset_examples_response.content}")
+            logging.error(
+                f"Failed to get dataset examples. \nHttp code: {dataset_examples_response.status_code} \nContent: {dataset_examples_response.content}")
             raise RuntimeError
 
         counter -= limit
         offset += limit
 
-    logging.info(f"Fetched dataset examples = {len(examples)}/{nb_example} -> {len(examples) / nb_example * 100:.2f}%")
+    logging.info(f"Fetched dataset examples = {len(examples)}/{nb_example}")
     return examples
 
 
+def append_runs_langsmith(dataset_example, _session_ids):
+    """
+    Append LangSmith run data to the CSV.
+
+    Args:
+        dataset_example: The dataset example.
+        _session_ids: List of session IDs.
+
+    Returns:
+        A list representing a line in the CSV.
+    """
+    csv_line = [
+        dataset_example["inputs"]["metadata"]["topic"],
+        dataset_example["inputs"]["question"],
+        dataset_example["outputs"]["answer"]
+    ]
+
+    example_runs_content = get_example_runs_content(dataset_example['id'])
+
+    for _id in _session_ids:
+        run = first_true(example_runs_content['runs'], lambda x: x['session_id'] == _id)
+        if run is None or run["outputs"] is None:
+            csv_line.append('')
+            csv_line.append('')
+        elif run["error"]:
+            csv_line.append(run["error"])
+            csv_line.append('')
+        else:
+            csv_line.append(run["outputs"]["answer"])
+            csv_line.append(','.join([doc["metadata"]["url"] for doc in run["outputs"]["source_documents"]]))
+
+    return csv_line
+
+
+def get_session_name(_id: str, sessions) -> str:
+    """
+    Get session name.
+    Args:
+        _id: the session id
+        sessions: the sessions
+
+    Returns: the session name
+    """
+
+    return first_true(sessions, predicate=lambda x: x['id'] == _id)['name']
+
+
 def get_example_runs_content(example_id):
     """
     Fetch runs of an example
@@ -192,111 +334,80 @@ def get_example_runs_content(example_id):
         raise RuntimeError
 
 
-def append_example_runs(dataset_example, _session_ids):
+def first_true(iterable, predicate=None):
     """
-    Append in a CSV line, the fetched runs for the given dataset example
+    Returns the first element in the iterable that satisfies the predicate.
+
     Args:
-        dataset_example: the dataset example
-        _session_ids: the session ids
+        iterable: The iterable to search.
+        predicate: The condition to check for.
 
-    Returns: The CSV line
+    Returns:
+        The first element satisfying the predicate.
     """
+    return next(filter(predicate, iterable), None)
 
-    # Init csv line
-    csv_line = [
-        dataset_example["input"]["metadata"]["topic"],
-        dataset_example["input"]["question"],
-        dataset_example["outputs"]["answer"]
-    ]
-
-    # Get example runs
-    example_runs_content = get_example_runs_content(dataset_example['id'])
 
-    # Complete csv line with example run result
-    for _id in _session_ids:
-        run = first_true(example_runs_content['runs'], predicate=lambda x: x['session_id'] == _id)
-        if run is None:
-            csv_line.append('')
-            csv_line.append('')
-        elif run["error"]:
-            csv_line.append(run["error"])
-            csv_line.append('')
-        else:
-            csv_line.append(run["outputs"]["answer"])
-            csv_line.append(
-                ','.join([doc["metadata"]["url"] for doc in run["outputs"]["source_documents"]])
-            )
+# Check for environment variables from LangFuse and LangSmith
+def check_environment_variables(provider):
+    """
+    Checks the required environment variables based on the provider.
 
-    return csv_line
+    Args:
+        provider: The provider being used ('langfuse' or 'langsmith').
+    """
+    if provider == 'langfuse':
+        if not os.getenv('LANGFUSE_SECRET_KEY'):
+            logging.error('Cannot proceed: LANGFUSE_SECRET_KEY is not defined.')
+            sys.exit(1)
+        if not os.getenv('LANGFUSE_HOST'):
+            logging.error('Cannot proceed: LANGFUSE_HOST is not defined.')
+            sys.exit(1)
+    elif provider == 'langsmith':
+        if not os.getenv('LANGCHAIN_API_KEY'):
+            logging.error('Cannot proceed: LANGCHAIN_API_KEY is not defined.')
+            sys.exit(1)
 
 
 if __name__ == '__main__':
     start_time = time.time()
+    load_dotenv()  # Load environment variables from .env file
 
-    cli_args = docopt(__doc__, version='Export dataset result runs')
-    # Set logging level
-    log_format = '%(levelname)s:%(module)s:%(message)s'
-    logging.basicConfig(
-        level=logging.DEBUG if cli_args['-v'] else logging.INFO, format=log_format
-    )
-    # Get LangSmith API key from environment
-    _LANGSMITH_API_KEY = os.environ["LANGCHAIN_API_KEY"]
-    # The LangSmith API base url
-    base_url = 'https://api.smith.langchain.com/api/v1'
-    # The script arguments
-    dataset_id = cli_args['<dataset_id>']
-    session_ids = cli_args['<session_ids>']
-
-    try:
-        logging.info(f'Call the LangSmith API to get the dataset information for dataset_id={dataset_id}.')
-        dataset_info_response = requests.get(
-            f'{base_url}/datasets?id={dataset_id}',
-            headers={"x-api-key": _LANGSMITH_API_KEY},
-        )
+    cli_args = docopt(__doc__, version='Export Run Results 0.1.0')
 
-        # Exit the programme if an error occurs
-        if dataset_info_response.status_code != 200:
-            logging.error(f"Failed to get dataset information. \n"
-                          f"Http code : {dataset_info_response.status_code} \n"
-                          f"Content   : {dataset_info_response.content}")
-            exit(1)
-
-        # No error occurred, continue loading content
-        dataset_info_content = json.loads(dataset_info_response.content)
-        example_counter = dataset_info_content[0]['example_count']
-        logging.info(f"Number of examples in dataset = {example_counter}")
-
-        # Get dataset examples
-        dataset_examples = get_dataset_examples(example_counter)
-
-        # Exit the programme if no runs is found
-        if len(dataset_examples) == 0:
-            logging.error("No runs found !")
-            exit(1)
-
-        # Get the runs of all examples, then create a csv file
-        # CSV filename
-        output_csv_file = f"export_run_result_{dataset_id}_{int(time.time())}.csv"
-        # CSV header line
-        csv_lines = [create_csv_header(session_ids)]
-
-        # CSV data lines
-        index = 1
-        for example in dataset_examples:
-            csv_lines.append(append_example_runs(example, session_ids))
-            progress = index / example_counter * 100
-            logging.info(f"Example processed : {index}/{example_counter} - Progression : {progress:.2f}%")
-            index += 1
-
-        # Creation of CSV file
-        with open(output_csv_file, 'w', newline='') as csv_file:
-            writer = csv.writer(csv_file, delimiter='|')
-            writer.writerows(csv_lines)
-        logging.info(f"Successful csv generation. Filename : {output_csv_file}")
-    except requests.exceptions.RequestException as e:
-        logging.error("A connection error has occurred : %s", e)
-
-    logging.info(
-        'End of execution. (Duration : %.2f seconds)',
-        time.time() - start_time
-    )
+    provider = cli_args['<dataset_provider>']
+    log_format = '%(levelname)s:%(module)s:%(message)s'
+    logging.basicConfig(level=logging.DEBUG if cli_args['-v'] else logging.INFO, format=log_format)
+
+    check_environment_variables(provider)  # Check environment variables based on provider
+
+    csv_lines = []
+    if provider == 'langfuse':
+        dataset_name = cli_args['<dataset_id_or_name>']
+        runs_names = cli_args['<session_or_run_ids>']
+        client = init_langfuse()
+        dataset = client.get_dataset(name=dataset_name)
+        csv_lines = [create_csv_header(runs_names, provider, dataset_name)]
+        for item in dataset.items:
+            csv_lines.append(append_runs_langfuse(item, runs_names))
+
+    elif provider == 'langsmith':
+        # The LangSmith API base url
+        base_url = 'https://api.smith.langchain.com/api/v1'
+        # Get LangSmith API key from environment
+        _LANGSMITH_API_KEY = os.environ["LANGCHAIN_API_KEY"]
+        dataset_id = cli_args['<dataset_id_or_name>']
+        session_ids = cli_args['<session_or_run_ids>']
+        dataset_info = get_sessions(dataset_id)
+        examples = get_dataset_examples(len(dataset_info), dataset_id)
+        csv_lines = [create_csv_header(session_ids, provider, dataset_id)]
+        for example in examples:
+            csv_lines.append(append_runs_langsmith(example, session_ids))
+
+    output_csv_file = f"export_run_result_{provider}_{int(time.time())}.csv"
+    with open(output_csv_file, 'w', newline='') as csv_file:
+        writer = csv.writer(csv_file, delimiter='|')
+        writer.writerows(csv_lines)
+
+    logging.info(f"CSV file successfully generated: {output_csv_file}")
+    logging.info(f"Total execution time: {time.time() - start_time:.2f} seconds")
diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/generate_dataset.py b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/generate_dataset.py
index a5180e7fdf..c6be41cbc4 100644
--- a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/generate_dataset.py
+++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/generate_dataset.py
@@ -15,8 +15,8 @@
 """Dataset generator. This script takes an excel file as input and generates a csv dataset as output. The generated dataset can also be directly sent to langsmith.
 
 Usage:
-    generate_dataset.py [-v] <input_excel> --range=<s> [--csv-output=<path>] [ --langsmith-dataset-name=<name> ] [--locale=<locale>] [--no-answer=<na>]
-    generate_dataset.py [-v] <input_excel> --sheet=<n>... [--csv-output=<path>] [ --langsmith-dataset-name=<name> ] [--locale=<locale>] [--no-answer=<na>]
+    generate_dataset.py [-v] <input_excel> --range=<s> [--csv-output=<path>] [ --langsmith-dataset-name=<name> ] [ --langfuse-dataset-name=<name> ] [--locale=<locale>] [--no-answer=<na>]
+    generate_dataset.py [-v] <input_excel> --sheet=<n>... [--csv-output=<path>] [ --langsmith-dataset-name=<name> ] [ --langfuse-dataset-name=<name> ] [--locale=<locale>] [--no-answer=<na>]
 
 Arguments:
     input_excel path to the input excel file
@@ -26,23 +26,31 @@
     --sheet=<n>                     Sheet numbers to be parsed. Indices are 0-indexed.
     --csv-output=<path>             Output path of csv file to be generated.
     --langsmith-dataset-name=<name> Name of the dataset to be saved on langsmith.
+    --langfuse-dataset-name=<name> Name of the dataset to be saved on langfuse.
     --locale=<locale>               Locale to be included in de dataset. [default: French]
     --no-answer=<na>                Label of no_answer to be included in the dataset. [default: NO_RAG_SENTENCE]
     -h --help                       Show this screen
     --version                       Show version
     -v                              Verbose output for debugging (without this option, script will be silent but for errors)
 
-Generates a testing dataset based on an input file. The input file should have the correct format (see generate_datset_input.xlsx for sample). The generated dataset can be saved on filesystem, using the --csv-output option, on langsmith, using the --langsmith-dataset-name option, or both.
+Generates a testing dataset based on an input file. The input file should have the correct format (see generate_datset_input.xlsx for sample). The generated dataset can be saved on filesystem, using the --csv-output option, on langsmith, using the --langsmith-dataset-name option, on langfuse using the --langfuse-dataset-name option, or both.
 """
-
+import base64
 import logging
 import os
 from json import loads
 from pathlib import Path
 from typing import List
 
+import boto3
+import httpx
 import pandas as pd
 from docopt import docopt
+from dotenv import load_dotenv
+from gen_ai_orchestrator.configurations.environment.settings import application_settings
+from gen_ai_orchestrator.models.security.proxy_server_type import ProxyServerType
+from httpx_auth_awssigv4 import SigV4Auth
+from langfuse import Langfuse
 from langsmith import Client
 
 
@@ -57,64 +65,67 @@ def _generate_dataset(
 
 
 def _parse_sheet(filename: str, sheet_index: int) -> pd.DataFrame:
-    logging.debug("Parsing sheet %s", sheet_index)
+    logging.debug('Parsing sheet %s', sheet_index)
     df = pd.read_excel(filename, sheet_name=sheet_index, header=None)
 
     df = df.drop(0, axis=0)  # Remove header row
     df = df.drop([3, 4, 6, 7], axis=1)  # Remove unnecessary columns
-    df = df.rename(columns={0: "topic", 1: "question", 2: "answer", 5: "quality"})
-    df = df.loc[df["quality"].notnull()]  # Ignore not annotated questions
-    df = df.loc[df["answer"].notnull()]  # Ignore not answered questions
-    df["topic"] = df["topic"].ffill()  # Fill in blanks in topic
+    df = df.rename(columns={0: 'topic', 1: 'question', 2: 'answer', 5: 'quality'})
+    # df = df.loc[df['quality'].notnull()]  # Ignore not annotated questions
+    # df = df.loc[df['answer'].notnull()]  # Ignore not answered questions
+    df['quality'] = df['quality'].fillna('No default quality')
+    df['answer'] = df['answer'].fillna('No default answer')
+    df['topic'] = df['topic'].fillna('No default topic')
+    #df['topic'] = df['topic'].ffill()  # Fill in blanks in topic
     return df
 
 
 def _add_locale(dataset: pd.DataFrame, locale: str) -> pd.DataFrame:
-    logging.debug("Using locale %s", locale)
+    logging.debug('Using locale %s', locale)
     return dataset.assign(locale=locale)
 
 
 def _add_no_answer(dataset: pd.DataFrame, no_answer: str) -> pd.DataFrame:
-    logging.debug("Using no_answer label %s", no_answer)
+    logging.debug('Using no_answer label %s', no_answer)
     return dataset.assign(no_answer=no_answer)
 
 
 def _parse_range(input_range: str) -> List[int]:
-    [a, b] = input_range.split(",")
+    [a, b] = input_range.split(',')
     return [i for i in range(int(a), int(b) + 1)]
 
 
 def _save_on_fs(dataset: pd.DataFrame, path: str):
-    logging.info("Saving dataset on path %s", path)
+    logging.info('Saving dataset on path %s', path)
     dataset.to_csv(path, index=False)
 
 
 def _send_to_langsmith(dataset: pd.DataFrame, dataset_name: str):
     # Transforms dataset to langsmith format
-    records = dataset.to_json(orient="records")
+    records = dataset.to_json(orient='records')
     records = loads(str(records))
 
     # Creates dataset in langsmith
     client = Client()
-    logging.info("Creating dataset %s on langsmith...", dataset_name)
+    logging.info('Creating dataset %s on langsmith...', dataset_name)
     ls_dataset = client.create_dataset(dataset_name=dataset_name)
-    logging.info("Creating examples on langsmith dataset id %s...", ls_dataset.id)
+    logging.info('Creating examples on langsmith dataset id %s...', ls_dataset.id)
     client.create_examples(
         inputs=[
             {
-                "question": r["question"],
-                "locale": r["locale"],
-                "no_answer": r["no_answer"],
-                "metadata": {
-                    "topic": r["topic"],
+                'question': r['question'],
+                'locale': r['locale'],
+                'no_answer': r['no_answer'],
+                'metadata': {
+                    'topic': r['topic'],
                 },
             }
             for r in records
         ],
         outputs=[
             {
-                "answer": r["answer"],
-                "quality": r["quality"],
+                'answer': r['answer'],
+                'quality': r['quality'],
             }
             for r in records
         ],
@@ -122,49 +133,137 @@ def _send_to_langsmith(dataset: pd.DataFrame, dataset_name: str):
     )
 
 
-if __name__ == "__main__":
-    cli_args = docopt(__doc__, version="Dataset generator 0.1.0")
+def init_langfuse():
+    if ProxyServerType.AWS_LAMBDA == application_settings.observability_proxy_server:
+        """
+        This AWSLambda proxy is used when the architecture implemented for the Langfuse
+        observability tool places it behind an API Gateway which requires its
+        own authentication, itself invoked by an AWS Lambda.
+        The API Gateway uses the standard "Authorization" header,
+        and uses observability_proxy_server_authorization_header_name
+        to define the "Authorization bearer token" for Langfuse.
+        """
+        aws_session = boto3.Session()
+        aws_credentials = aws_session.get_credentials()
+        auth = SigV4Auth(
+            access_key=aws_credentials.access_key,
+            secret_key=aws_credentials.secret_key,
+            token=aws_credentials.token,
+            service="lambda",
+            region=aws_session.region_name,
+        )
+
+        langfuse_creds = base64.b64encode(
+            f"{os.environ['LANGFUSE_PUBLIC_KEY']}:{os.environ['LANGFUSE_SECRET_KEY']}".encode()
+        ).decode()
+
+        return Langfuse(httpx_client=httpx.Client(
+            auth=auth,
+            headers={
+                application_settings.observability_proxy_server_authorization_header_name: f"Basic {langfuse_creds}"
+            },
+        ))
+
+    return Langfuse()
+
+
+def _send_to_langfuse(dataset: pd.DataFrame, dataset_name: str):
+    # Transforms dataset to JSON format
+    records = dataset.to_json(orient='records')
+    records = loads(str(records))
+
+    # Initializes the Langfuse client
+    client = init_langfuse()
+
+    logging.info('Creating dataset %s on Langfuse...', dataset_name)
+
+    # Creates dataset in Langfuse
+    lf_dataset = client.create_dataset(name=dataset_name)
+
+    logging.info('Creating examples on Langfuse dataset id %s...', lf_dataset.id)
+
+    # Prepares inputs and outputs
+    inputs = [
+        {
+            'question': r['question'],
+            'locale': r['locale'],
+            'no_answer': r['no_answer'],
+        }
+        for r in records
+    ]
+    metadatas = [{'topic': r['topic']} for r in records]
+
+    outputs = [
+        {
+            'answer': r['answer'],
+            'quality': r['quality'],
+        }
+        for r in records
+    ]
+
+    # Creates examples in the dataset on Langfuse
+    for input, metadata, output in zip(inputs, metadatas, outputs):
+        logging.info('import data')
+        client.create_dataset_item(
+            dataset_name=dataset_name,
+            input=input,
+            expected_output=output,
+            metadata=metadata,
+        )
+
 
+if __name__ == '__main__':
+    cli_args = docopt(__doc__, version='Dataset generator 0.1.0')
+    load_dotenv()
     # Set logging level
-    log_format = "%(levelname)s:%(module)s:%(message)s"
+    log_format = '%(levelname)s:%(module)s:%(message)s'
     logging.basicConfig(
-        level=logging.DEBUG if cli_args["-v"] else logging.INFO, format=log_format
+        level=logging.DEBUG if cli_args['-v'] else logging.INFO, format=log_format
     )
 
     # check if input filer exists
-    filename = cli_args["<input_excel>"]
+    filename = cli_args['<input_excel>']
     if not os.path.isfile(filename):
-        logging.error("Specified input excel file was not found.")
+        logging.error('Specified input excel file was not found.')
         exit(1)
 
     # check if langsmith creds is set
-    langsmith_dataset_name = cli_args["--langsmith-dataset-name"]
-    if langsmith_dataset_name and not os.environ.get("LANGCHAIN_API_KEY"):
-        logging.error("Envvar LANGCHAIN_API_KEY not found.")
+    langsmith_dataset_name = cli_args['--langsmith-dataset-name']
+    if langsmith_dataset_name and not os.environ.get('LANGCHAIN_API_KEY'):
+        logging.error('Envvar LANGCHAIN_API_KEY not found.')
+        exit(1)
+
+    # check if langfuse creds is set
+    langfuse_dataset_name = cli_args['--langfuse-dataset-name']
+    if langfuse_dataset_name and not os.environ.get('LANGFUSE_PUBLIC_KEY'):
+        logging.error('Envvar LANGFUSE_PUBLIC_KEY not found.')
         exit(1)
 
     # check if output file can be written
-    output_path = cli_args["--csv-output"]
+    output_path = cli_args['--csv-output']
     if output_path and not Path(output_path).parent.exists():
         logging.error(
-            "Cannot proceed: directory %s does not exist", Path(output_path).parent
+            'Cannot proceed: directory %s does not exist', Path(output_path).parent
         )
         exit(1)
 
-    if cli_args.get("--range") is not None:
-        sheet_indices = _parse_range(str(cli_args["--range"]))
+    if cli_args.get('--range') is not None:
+        sheet_indices = _parse_range(str(cli_args['--range']))
     else:
-        sheet_indices = [int(i) for i in cli_args["--sheet"]]
+        sheet_indices = [int(i) for i in cli_args['--sheet']]
 
     dataset = _generate_dataset(
         filename=filename,
         sheet_indices=sheet_indices,
-        locale=cli_args["--locale"] or "French",
-        no_answer=cli_args["--no-answer"] or "NO_RAG_SENTENCE",
+        locale=cli_args['--locale'] or 'French',
+        no_answer=cli_args['--no-answer'] or 'NO_RAG_SENTENCE',
     )
 
     if output_path:
         _save_on_fs(dataset, output_path)
 
     if langsmith_dataset_name:
-        _send_to_langsmith(dataset, cli_args["--langsmith-dataset-name"])
+        _send_to_langsmith(dataset, cli_args['--langsmith-dataset-name'])
+
+    if langfuse_dataset_name:
+        _send_to_langfuse(dataset, cli_args['--langfuse-dataset-name'])
diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/poetry.lock b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/poetry.lock
index 6c1a131d4e..efb3310ad9 100644
--- a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/poetry.lock
+++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/poetry.lock
@@ -729,7 +729,7 @@ langchain = "^0.3.3"
 langchain-community = "^0.3.2"
 langchain-openai = "^0.2.2"
 langchain-postgres = "^0.0.12"
-langfuse = "^2.52.0"
+langfuse = "2.36.2"
 opensearch-py = "^2.7.1"
 path = "^17.0.0"
 psycopg = {version = "^3.2.3", extras = ["binary"]}
@@ -1172,84 +1172,84 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "jiter"
-version = "0.6.1"
+version = "0.7.0"
 description = "Fast iterable JSON parser."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "jiter-0.7.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:ae60ec89037a78d60bbf3d8b127f1567769c8fa24886e0abed3f622791dea478"},
+    {file = "jiter-0.7.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:836f03dea312967635233d826f783309b98cfd9ccc76ac776e224cfcef577862"},
+    {file = "jiter-0.7.0-cp39-none-win32.whl", hash = "sha256:ebc30ae2ce4bc4986e1764c404b4ea1924f926abf02ce92516485098f8545374"},
+    {file = "jiter-0.7.0-cp39-none-win_amd64.whl", hash = "sha256:abf596f951370c648f37aa9899deab296c42a3829736e598b0dd10b08f77a44d"},
+    {file = "jiter-0.7.0.tar.gz", hash = "sha256:c061d9738535497b5509f8970584f20de1e900806b239a39a9994fc191dad630"},
 ]
 
 [[package]]
@@ -1306,8 +1306,8 @@ langchain-core = ">=0.3.14,<0.4.0"
 langchain-text-splitters = ">=0.3.0,<0.4.0"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = [
-    {version = ">=1,<2", markers = "python_version < \"3.12\""},
     {version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""},
+    {version = ">=1,<2", markers = "python_version < \"3.12\""},
 ]
 pydantic = ">=2.7.4,<3.0.0"
 PyYAML = ">=5.3"
@@ -1334,8 +1334,8 @@ langchain = ">=0.3.6,<0.4.0"
 langchain-core = ">=0.3.14,<0.4.0"
 langsmith = ">=0.1.125,<0.2.0"
 numpy = [
-    {version = ">=1,<2", markers = "python_version < \"3.12\""},
     {version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""},
+    {version = ">=1,<2", markers = "python_version < \"3.12\""},
 ]
 pydantic-settings = ">=2.4.0,<3.0.0"
 PyYAML = ">=5.3"
@@ -1359,8 +1359,8 @@ jsonpatch = ">=1.33,<2.0"
 langsmith = ">=0.1.125,<0.2.0"
 packaging = ">=23.2,<25"
 pydantic = [
-    {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
     {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
+    {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
 ]
 PyYAML = ">=5.3"
 tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0"
@@ -1427,11 +1427,10 @@ files = [
 ]
 
 [package.dependencies]
-anyio = ">=4.4.0,<5.0.0"
 backoff = ">=1.10.0"
 httpx = ">=0.15.4,<1.0"
 idna = ">=3.7,<4.0"
-packaging = ">=23.2,<25.0"
+packaging = ">=23.2,<24.0"
 pydantic = ">=1.10.7,<3.0"
 wrapt = ">=1.14,<2.0"
 
@@ -1455,8 +1454,8 @@ files = [
 httpx = ">=0.23.0,<1"
 orjson = ">=3.9.14,<4.0.0"
 pydantic = [
-    {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
     {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
+    {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
 ]
 requests = ">=2,<3"
 requests-toolbelt = ">=1.0.0,<2.0.0"
@@ -1852,13 +1851,13 @@ files = [
 
 [[package]]
 name = "packaging"
-version = "24.1"
+version = "23.2"
 description = "Core utilities for Python packages"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.7"
 files = [
-    {file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"},
-    {file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"},
+    {file = "packaging-23.2-py3-none-any.whl", hash = "sha256:8c491190033a9af7e1d931d0b5dacc2ef47509b34dd0de67ed209b5203fc88c7"},
+    {file = "packaging-23.2.tar.gz", hash = "sha256:048fb0e9405036518eaaf48a55953c750c11e1a1b68e0dd1a9d62ed0c092cfc5"},
 ]
 
 [[package]]
@@ -1917,6 +1916,8 @@ numpy = [
     {version = ">=1.22.4", markers = "python_version < \"3.11\""},
     {version = ">=1.23.2", markers = "python_version == \"3.11\""},
     {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
+    {version = ">=1.22.4", markers = "python_version < \"3.11\""},
+    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -2304,8 +2305,8 @@ files = [
 annotated-types = ">=0.6.0"
 pydantic-core = "2.23.4"
 typing-extensions = [
-    {version = ">=4.6.1", markers = "python_version < \"3.13\""},
     {version = ">=4.12.2", markers = "python_version >= \"3.13\""},
+    {version = ">=4.6.1", markers = "python_version < \"3.13\""},
 ]
 
 [package.extras]
diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/pyproject.toml b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/pyproject.toml
index 5431503e23..92b10dab20 100644
--- a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/pyproject.toml
+++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/pyproject.toml
@@ -10,21 +10,22 @@ package-mode = false
 [tool.poetry.dependencies]
 python = "^3.10"
 docopt-ng = "^0.9.0"
-pandas = "^2.2.1"
-openpyxl = "^3.1.2"
+pandas = "^2.2.3"
+openpyxl = "^3.1.5"
 beautifulsoup4 = "^4.12.2"
-langchain = "^0.3.3"
-langsmith = "^0.1.134"
-python-dotenv = "^1.0.0"
-opensearch-py = "^2.4.2"
-gen_ai_orchestrator = {path = "../server", develop=true}
-langchain-community = "^0.3.2"
+langchain = "^0.3.7"
+langsmith = "^0.1.139"
+python-dotenv = "^1.0.1"
+opensearch-py = "^2.7.1"
+gen_ai_orchestrator = {path = "../server"}
+langchain-community = "^0.3.5"
 pre-commit = "^3.7.1"
 aiometer = "^0.5.0"
 aiohttp = "^3.10.10"
 aiohttp-socks = "^0.9.0"
-pydantic = "^2.9.0"
+pydantic = "^2.9.2"
 humanize = "^4.11.0"
+langfuse = "2.36.2"
 
 [build-system]
 requires = ["poetry-core"]
diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/rag_testing_tool.py b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/rag_testing_tool.py
index 9109e68561..2bf18f51b3 100644
--- a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/rag_testing_tool.py
+++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/rag_testing_tool.py
@@ -13,11 +13,11 @@
 #   limitations under the License.
 #
 """Retrieval-Augmented Generation (RAG) endpoint settings testing tool based
-on LangSmith's SDK: runs a specific RAG Settings configuration against a
+on LangSmith's or LangFuse's SDK: runs a specific RAG Settings configuration against a
 reference dataset.
 
 Usage:
-    rag_testing_tool.py [-v] <rag_query> <dataset_name> <test_name> [<delay>]
+    rag_testing_tool.py [-v] <rag_query> <dataset_provider> <dataset_name> <test_name> [<delay>]
     rag_testing_tool.py -h | --help
     rag_testing_tool.py --version
 
@@ -27,6 +27,7 @@
                     provider, indexation session's unique id, and 'k', i.e. nb
                     of retrieved docs (question and chat history are ignored,
                     as they will come from the dataset)
+    dataset_provider the dataset provider (langsmith or langfuse)
     dataset_name    the reference dataset name
     test_name       name of the test run
 
@@ -38,7 +39,7 @@
                 be silent but for errors)
 
 Build a RAG (Lang)chain from the RAG Query and runs it against the provided
-LangSmith dataset. The chain is created anew for each entry of the dataset, and
+LangSmith or LangFuse dataset. The chain is created anew for each entry of the dataset, and
 if a delay is provided, each chain creation will be delayed accordingly.
 """
 import json
@@ -52,10 +53,13 @@
 
 from docopt import docopt
 from dotenv import load_dotenv
-from langsmith import Client
-
 from gen_ai_orchestrator.routers.requests.requests import RagQuery
 from gen_ai_orchestrator.services.langchain.rag_chain import create_rag_chain
+from langsmith import Client
+from tenacity import (
+    retry,
+    stop_after_attempt,
+    wait_random_exponential, )
 
 
 def test_rag(args):
@@ -66,6 +70,7 @@ def test_rag(args):
 
         args (dict):    A dictionary containing command-line arguments.
                         Expecting keys: '<rag_query>'
+                                        '<dataset_provider>'
                                         '<dataset_name>'
                                         '<test_name>'
                                         '<delay>'
@@ -88,11 +93,43 @@ def _construct_chain():
             'chat_history': lambda x: x['chat_history'] if 'chat_history' in x else [],
         } | create_rag_chain(RagQuery(**rag_query))
 
-    client = Client()
+    @retry(wait=wait_random_exponential(min=10, max=60), stop=stop_after_attempt(5))
+    def run_dataset(run_name_dataset):
+
+        if args['<dataset_provider>'].lower() == 'langsmith':
+            client = Client()
+            client.run_on_dataset(
+
+                dataset_name=args['<dataset_name>'],
+                llm_or_chain_factory=_construct_chain,
+                project_name=run_name_dataset,
+                project_metadata={
+                    'document_index_name': document_index_name,
+                    'k': k,
+                },
+                concurrency_level=concurrency_level,
+            )
+        elif args['<dataset_provider>'].lower() == 'langfuse':
+            client = init_langfuse()
+            dataset = client.get_dataset(args['<dataset_name>'])
+
+            for item in dataset.items:
+                callback_handlers = []
+                handler = item.get_langchain_handler(
+                    run_name=run_name_dataset,
+                    run_metadata={
+                        'document_index_name': document_index_name,
+                        'k': k,
+                    },
+                )
+                callback_handlers.append(handler)
+                _construct_chain().invoke(
+                    item.input, config={'callbacks': callback_handlers}
+                )
+            client.flush()
+
+    document_index_name = rag_query['document_index_name']
     search_params = rag_query['document_search_params']
-    index_session_id = search_params['filter'][0]['term'][
-        'metadata.index_session_id.keyword'
-    ]
     k = search_params['k']
 
     # This is LangSmith's default concurrency level
@@ -101,24 +138,15 @@ def _construct_chain():
     # one at a time
     if args['<delay>']:
         concurrency_level = 1
-
-    client.run_on_dataset(
-        dataset_name=args['<dataset_name>'],
-        llm_or_chain_factory=_construct_chain,
-        project_name=args['<test_name>'] + '-' + str(uuid4())[:8],
-        project_metadata={
-            'index_session_id': index_session_id,
-            'k': k,
-        },
-        concurrency_level=concurrency_level,
-    )
+    run_name_dataset = args['<test_name>'] + '-' + str(uuid4())[:8]
+    run_dataset(run_name_dataset)
 
     duration = datetime.now() - start_time
     hours, remainder = divmod(duration.seconds, 3600)
     minutes, seconds = divmod(remainder, 60)
     formatted_duration = '{:02}:{:02}:{:02}'.format(hours, minutes, seconds)
     logging.debug(
-        f'Ran RAGQuery (k={k}, index_session_id={index_session_id}) on '
+        f'Ran RAGQuery (k={k}, document_index_name={document_index_name}) on '
         f"{args['<dataset_name>']} dataset (duration: {formatted_duration})"
     )
 
@@ -133,22 +161,38 @@ def _construct_chain():
     )
 
     load_dotenv()
-
-    # Check env (LangSmith)
-    langchain_endpoint = os.getenv('LANGCHAIN_ENDPOINT')
-    if not langchain_endpoint:
-        logging.error(
-            'Cannot proceed: LANGCHAIN_ENDPOINT env variable is not defined (define it in a .env file)'
-        )
-        sys.exit(1)
-
-    langchain_apikey = os.getenv('LANGCHAIN_API_KEY')
-    if not langchain_apikey:
+    if cli_args['<dataset_provider>'].lower() == 'langsmith':
+        # Check env (LangSmith)
+        langchain_apikey = os.getenv('LANGCHAIN_API_KEY')
+        if not langchain_apikey:
+            logging.error(
+                'Cannot proceed: LANGCHAIN_API_KEY env variable is not defined (define it in a .env file)'
+            )
+            sys.exit(1)
+    elif cli_args['<dataset_provider>'].lower() == 'langfuse':
+        langfuse_secret_key = os.getenv('LANGFUSE_SECRET_KEY')
+        if not langfuse_secret_key:
+            logging.error(
+                'Cannot proceed: LANGFUSE_SECRET_KEY env variable is not defined (define it in a .env file)'
+            )
+            sys.exit(1)
+        langchain_host = os.getenv('LANGFUSE_HOST')
+        if not langchain_host:
+            logging.error(
+                'Cannot proceed: LANGFUSE_HOST env variable is not defined (define it in a .env file)'
+            )
+            sys.exit(1)
+        langfuse_public_key = os.getenv('LANGFUSE_PUBLIC_KEY')
+        if not langfuse_public_key:
+            logging.error(
+                'Cannot proceed: LANGFUSE_PUBLIC_KEY env variable is not defined (define it in a .env file)'
+            )
+            sys.exit(1)
+    else:
         logging.error(
-            'Cannot proceed: LANGCHAIN_API_KEY env variable is not defined (define it in a .env file)'
+            'Cannot proceed: dataset_provider is not valid, only langfuse or langsmith'
         )
         sys.exit(1)
-
     # Check args:
     # - RAGQuery JSON file
     rag_query_file_path = Path(cli_args['<rag_query>'])
diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/ragquery.json.example b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/ragquery.json.example
new file mode 100644
index 0000000000..0780246006
--- /dev/null
+++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/ragquery.json.example
@@ -0,0 +1,55 @@
+{
+    "history": [],
+    "question_answering_llm_setting": {
+        "provider": "AzureOpenAIService",
+         "api_key": {
+             "type": "Raw",
+             "value": "*****************"
+            },
+        "model": "gpt-4o",
+        "deployment_name": "*******************",
+        "repetition_penalty":1.0,
+        "max_new_tokens":256,
+        "api_base": "******************************",
+        "api_version": "2024-03-01-preview",
+        "temperature": 0.4 ,
+        "prompt": "Use the following context to answer the question at the end.\nIf you don't know the answer, just say {no_answer}.\n Context: {context}\nQuestion: {question}  \n Answer in {locale}:"
+    },
+    "question_answering_prompt_inputs": {
+            "question": "How to get started playing guitar ?",
+            "no_answer": "Sorry, I don't know.",
+            "locale": "French"
+        },
+    "embedding_question_em_setting": {
+        "provider": "AzureOpenAIService",
+         "api_key": {
+             "type": "Raw",
+             "value": "*****************************"
+            },
+        "deployment_name":  "********************",
+        "api_base":         "***********************************",
+        "api_version":      "2024-03-01-preview",
+         "model": "text-embedding-ada-002"
+    },
+    "document_index_name": "ns-03-bot-cmso",
+    "document_search_params": {
+        "provider": "OpenSearch",
+        "filter": [
+            {
+                "term": {
+                    "metadata.index_session_id.keyword": "****************************************"
+                }
+            }
+        ],
+        "k": 4
+    },
+    "observability_setting": {
+        "provider": "Langfuse",
+        "url": "http://localhost:3000",
+        "secret_key":{
+            "type": "Raw",
+            "value": "************************"
+        },
+        "public_key":"********************************"
+    }
+}
\ No newline at end of file