From 7a07be7d53306a371b88a685e864f82dc7a1748a Mon Sep 17 00:00:00 2001
From: Vasilije <8619304+Vasilije1990@users.noreply.github.com>
Date: Sat, 28 Oct 2023 23:12:42 +0200
Subject: [PATCH 1/2] fixes to chunking logic and optimizations

---
 README.md                           |    5 +-
 level_3/poetry.lock                 | 1109 +++++++++++++--------------
 level_3/rag_test_manager.py         |  185 +++--
 level_3/vectordb/loaders/loaders.py |    2 +-
 4 files changed, 670 insertions(+), 631 deletions(-)

diff --git a/README.md b/README.md
index 9d454faff..2af3e4704 100644
--- a/README.md
+++ b/README.md
@@ -140,10 +140,11 @@ After that, you can run the RAG test manager.
 
 ``` 
     python rag_test_manager.py \
-    --url "https://www.ibiblio.org/ebooks/London/Call%20of%20Wild.pdf" \
+    --file ".data" \
     --test_set "example_data/test_set.json" \
     --user_id "666" \
-    --metadata "example_data/metadata.json"
+    --metadata "example_data/metadata.json" \
+    --retriever_type "single_document_context"
 
 ```
 
diff --git a/level_3/poetry.lock b/level_3/poetry.lock
index f26ff5239..5bda9ee7e 100644
--- a/level_3/poetry.lock
+++ b/level_3/poetry.lock
@@ -249,13 +249,13 @@ test = ["flake8 (>=5.0,<6.0)", "uvloop (>=0.15.3)"]
 
 [[package]]
 name = "atlassian-python-api"
-version = "3.41.2"
+version = "3.41.3"
 description = "Python Atlassian REST API Wrapper"
 optional = false
 python-versions = "*"
 files = [
-    {file = "atlassian-python-api-3.41.2.tar.gz", hash = "sha256:a2022977da5a395412ace8e29c2c541312f07d45fc750435dec036af53daceda"},
-    {file = "atlassian_python_api-3.41.2-py3-none-any.whl", hash = "sha256:27c2361a22ee8cc69988f67a591488cbfce09e5f284da000011af11944d2bc96"},
+    {file = "atlassian-python-api-3.41.3.tar.gz", hash = "sha256:a29aae8f456babe125e3371a0355018e9c1d37190333efc312bd81163bd96ffd"},
+    {file = "atlassian_python_api-3.41.3-py3-none-any.whl", hash = "sha256:7661d3ce3c80e887a7e5ec1c61c1e37d3eaacb4857e377b38ef4084d0f067757"},
 ]
 
 [package.dependencies]
@@ -329,6 +329,17 @@ soupsieve = ">1.2"
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
+[[package]]
+name = "blinker"
+version = "1.6.3"
+description = "Fast, simple object-to-object and broadcast signaling"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "blinker-1.6.3-py3-none-any.whl", hash = "sha256:296320d6c28b006eb5e32d4712202dbcdcbf5dc482da298c2f44881c43884aaa"},
+    {file = "blinker-1.6.3.tar.gz", hash = "sha256:152090d27c1c5c722ee7e48504b02d76502811ce02e1523553b4cf8c8b3d3a8d"},
+]
+
 [[package]]
 name = "blis"
 version = "0.7.11"
@@ -377,17 +388,17 @@ numpy = {version = ">=1.19.0", markers = "python_version >= \"3.9\""}
 
 [[package]]
 name = "boto3"
-version = "1.28.63"
+version = "1.28.73"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">= 3.7"
 files = [
-    {file = "boto3-1.28.63-py3-none-any.whl", hash = "sha256:65d052ec13197460586ee385aa2d6bba0e7378d2d2c7f3e93c044c43ae1ca782"},
-    {file = "boto3-1.28.63.tar.gz", hash = "sha256:94218aba2feb5b404b665b8d76c172dc654f79b4c5fa0e9e92459c098da87bf4"},
+    {file = "boto3-1.28.73-py3-none-any.whl", hash = "sha256:bbe377a288b6b12b526fae3b3d743318c6868626cf67e1e97f104345a5194b1e"},
+    {file = "boto3-1.28.73.tar.gz", hash = "sha256:a61cf96f7e196b1450afdf4856b7ea0e58080752e687b0011157be96934489be"},
 ]
 
 [package.dependencies]
-botocore = ">=1.31.63,<1.32.0"
+botocore = ">=1.31.73,<1.32.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.7.0,<0.8.0"
 
@@ -396,13 +407,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.31.63"
+version = "1.31.73"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">= 3.7"
 files = [
-    {file = "botocore-1.31.63-py3-none-any.whl", hash = "sha256:cb9db5db5af865b1fc2e1405b967db5d78dd0f4d84e5dc1974e082733c1034b7"},
-    {file = "botocore-1.31.63.tar.gz", hash = "sha256:6e582c811ea74f25bdb490ac372b2645de4a60286b42ddd8c69f3b6df82b6b12"},
+    {file = "botocore-1.31.73-py3-none-any.whl", hash = "sha256:6e9caaa7205e0c0505f4868a4053e96eaf3f4b6bce0368a46970a8efeeacb492"},
+    {file = "botocore-1.31.73.tar.gz", hash = "sha256:5334c22d5a3f4643931896137c57b2496fef005b039d87d8740e7a28eb31519d"},
 ]
 
 [package.dependencies]
@@ -415,13 +426,13 @@ crt = ["awscrt (==0.16.26)"]
 
 [[package]]
 name = "cachetools"
-version = "5.3.1"
+version = "5.3.2"
 description = "Extensible memoizing collections and decorators"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
-    {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
+    {file = "cachetools-5.3.2-py3-none-any.whl", hash = "sha256:861f35a13a451f94e301ce2bec7cac63e881232ccce7ed67fab9b5df4d3beaa1"},
+    {file = "cachetools-5.3.2.tar.gz", hash = "sha256:086ee420196f7b2ab9ca2db2520aca326318b68fe5ba8bc4d49cca91add450f2"},
 ]
 
 [[package]]
@@ -523,101 +534,101 @@ files = [
 
 [[package]]
 name = "charset-normalizer"
-version = "3.3.0"
+version = "3.3.1"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7.0"
 files = [
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-    {file = "charset_normalizer-3.3.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:4162918ef3098851fcd8a628bf9b6a98d10c380725df9e04caf5ca6dd48c847a"},
-    {file = "charset_normalizer-3.3.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0570d21da019941634a531444364f2482e8db0b3425fcd5ac0c36565a64142c8"},
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 ]
 
 [[package]]
@@ -832,34 +843,34 @@ test-no-images = ["pytest", "pytest-cov", "wurlitzer"]
 
 [[package]]
 name = "cryptography"
-version = "41.0.4"
+version = "41.0.5"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "cryptography-41.0.5.tar.gz", hash = "sha256:392cb88b597247177172e02da6b7a63deeff1937fa6fec3bbf902ebd75d97ec7"},
 ]
 
 [package.dependencies]
@@ -934,13 +945,13 @@ files = [
 
 [[package]]
 name = "dash"
-version = "2.14.0"
+version = "2.14.1"
 description = "A Python framework for building reactive web-apps. Developed by Plotly."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "dash-2.14.0-py3-none-any.whl", hash = "sha256:b88ffb53cb1bf54c12780ecf89943bb901c8914b3c075002e46519c9b17d7a72"},
-    {file = "dash-2.14.0.tar.gz", hash = "sha256:bd28be70be24ae1d1f764b8217a03da35e9ed895406686d24dfb6ed4e331e5a9"},
+    {file = "dash-2.14.1-py3-none-any.whl", hash = "sha256:ce440ef7416945c9daa8274948483a0aac928a4fec768c0384fd4e9a6196eaf2"},
+    {file = "dash-2.14.1.tar.gz", hash = "sha256:93dc9d665ec5d3720647d4cef4520a1c7cd1bde57e893ffeb7e6cd59781d3294"},
 ]
 
 [package.dependencies]
@@ -948,7 +959,7 @@ ansi2html = "*"
 dash-core-components = "2.0.0"
 dash-html-components = "2.0.0"
 dash-table = "5.0.0"
-Flask = ">=1.0.4,<2.3.0"
+Flask = ">=1.0.4,<3.1"
 importlib-metadata = {version = "*", markers = "python_version >= \"3.7\""}
 nest-asyncio = "*"
 plotly = ">=5.0.0"
@@ -956,7 +967,7 @@ requests = "*"
 retrying = "*"
 setuptools = "*"
 typing-extensions = ">=4.1.1"
-Werkzeug = "<2.3.0"
+Werkzeug = "<3.1"
 
 [package.extras]
 celery = ["celery[redis] (>=5.1.2)", "importlib-metadata (<5)", "redis (>=3.5.3)"]
@@ -1036,13 +1047,13 @@ pdf = ["pypdf (>=3.3.0,<4.0.0)"]
 
 [[package]]
 name = "deepeval"
-version = "0.20.8"
-description = "DeepEval provides evaluation and unit testing to accelerate development of LLMs and Agents."
+version = "0.20.13"
+description = "The open-source evaluation framework for LLMs."
 optional = false
 python-versions = "*"
 files = [
-    {file = "deepeval-0.20.8-py3-none-any.whl", hash = "sha256:db34f07e812db617cb5dc5a778134373a2f14109f4b072ab000f8fd65dd523bc"},
-    {file = "deepeval-0.20.8.tar.gz", hash = "sha256:10707f58dbd7bb03e17551b19f10c44a3a32d126b3ea2325ff604045c67bc325"},
+    {file = "deepeval-0.20.13-py3-none-any.whl", hash = "sha256:d73d8b3d1e81b49f02db58357b82f6be8787df0c3f8e52643129178534a47fb8"},
+    {file = "deepeval-0.20.13.tar.gz", hash = "sha256:dbec3d3f2e0b925421e35064811d544a5f709849b4389bc980bb190eb7471aaf"},
 ]
 
 [package.dependencies]
@@ -1083,20 +1094,20 @@ dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
 
 [[package]]
 name = "dlt"
-version = "0.3.20"
+version = "0.3.22"
 description = "dlt is an open-source python-first scalable data loading library that does not require any backend to run."
 optional = false
 python-versions = ">=3.8.1,<4.0"
 files = [
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-    {file = "dlt-0.3.20.tar.gz", hash = "sha256:930a347da2fddb6e9433a428437572ce0598a613ba1082aad8f132d774e60334"},
+    {file = "dlt-0.3.22-py3-none-any.whl", hash = "sha256:00e30cba8c601d57ea30671b01bf7bb6d9a9ebeb6456879f01774dd92869bb7a"},
+    {file = "dlt-0.3.22.tar.gz", hash = "sha256:ac987951a6cd1981bcc611208d5649ec63fccd2b44cc5bc9c3e3e3bf36e6a118"},
 ]
 
 [package.dependencies]
 astunparse = ">=1.6.3"
 click = ">=7.1"
 deprecated = ">=1.2.9"
-duckdb = {version = ">=0.6.1,<0.9.0", optional = true, markers = "extra == \"duckdb\" or extra == \"motherduck\""}
+duckdb = {version = ">=0.6.1,<0.10.0", optional = true, markers = "extra == \"duckdb\" or extra == \"motherduck\""}
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 [[package]]
@@ -1319,19 +1317,19 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
 
 [[package]]
 name = "filelock"
-version = "3.12.4"
+version = "3.13.0"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.8"
 files = [
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-typing = ["typing-extensions (>=4.7.1)"]
+docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.24)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
+typing = ["typing-extensions (>=4.8)"]
 
 [[package]]
 name = "filetype"
@@ -1346,20 +1344,21 @@ files = [
 
 [[package]]
 name = "flask"
-version = "2.2.5"
+version = "3.0.0"
 description = "A simple framework for building complex web applications."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 [package.dependencies]
-click = ">=8.0"
-itsdangerous = ">=2.0"
-Jinja2 = ">=3.0"
-Werkzeug = ">=2.2.2"
+blinker = ">=1.6.2"
+click = ">=8.1.3"
+itsdangerous = ">=2.1.2"
+Jinja2 = ">=3.1.2"
+Werkzeug = ">=3.0.0"
 
 [package.extras]
 async = ["asgiref (>=3.2)"]
@@ -1513,13 +1512,13 @@ files = [
 
 [[package]]
 name = "fsspec"
-version = "2023.9.2"
+version = "2023.10.0"
 description = "File-system specification"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
@@ -1548,13 +1547,13 @@ tqdm = ["tqdm"]
 
 [[package]]
 name = "gitdb"
-version = "4.0.10"
+version = "4.0.11"
 description = "Git Object Database"
 optional = false
 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
@@ -1562,20 +1561,20 @@ smmap = ">=3.0.1,<6"
 
 [[package]]
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-version = "3.1.37"
+version = "3.1.40"
 description = "GitPython is a Python library used to interact with Git repositories"
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 python-versions = ">=3.7"
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 [[package]]
 name = "giturlparse"
@@ -1632,75 +1631,77 @@ requests = "*"
 
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 description = "Lightweight in-process concurrent programming"
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 [package.extras]
-docs = ["Sphinx", "docutils (<0.18)"]
+docs = ["Sphinx"]
 test = ["objgraph", "psutil"]
 
 [[package]]
@@ -2197,13 +2198,13 @@ six = "*"
 
 [[package]]
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-version = "0.0.43"
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 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
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 python-versions = ">=3.8.1,<4.0"
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 [package.dependencies]
@@ -2531,13 +2532,13 @@ tests = ["pytest", "pytz", "simplejson"]
 
 [[package]]
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+version = "1.5.4"
 description = "A lightweight AI engineering framework for building natural language interfaces that are reliable, scalable, and easy to trust."
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 [package.dependencies]
@@ -2557,14 +2558,14 @@ uvicorn = ">=0.22.0"
 [package.extras]
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 [[package]]
 name = "matplotlib"
@@ -2792,21 +2793,21 @@ files = [
 
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-test = ["codecov (>=2.1)", "pytest (>=7.2)", "pytest-cov (>=4.0)"]
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 [[package]]
 name = "nltk"
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 [package.dependencies]
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 protobuf = ">=3.20.2"
-typing-extensions = ">=3.6.2.1"
 
 [package.extras]
-lint = ["lintrunner (>=0.10.0)", "lintrunner-adapters (>=0.3)"]
+reference = ["Pillow", "google-re2"]
 
 [[package]]
 name = "onnxruntime"
@@ -3034,72 +3028,72 @@ numpy = [
 
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@@ -3176,42 +3170,42 @@ xml = ["lxml (>=4.8.0)"]
 
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 [package.dependencies]
 numpy = [
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-    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
+    {version = ">=1.22.4,<2", markers = "python_version < \"3.11\""},
+    {version = ">=1.23.2,<2", markers = "python_version == \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -3256,28 +3250,6 @@ files = [
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 test = ["Faker (>=1.0.8)", "allpairspy (>=2)", "click (>=6.2)", "pytest (>=6.0.1)", "pytest-discord (>=0.1.4)", "pytest-md-report (>=0.4.1)"]
 
-[[package]]
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-version = "0.10.2"
-description = "pathlib.Path subclasses for local and cloud bucket storage"
-optional = false
-python-versions = ">= 3.6"
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-typer = ">=0.3.0,<1.0.0"
-
-[package.extras]
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-s3 = ["boto3"]
-test = ["mock", "pytest", "pytest-coverage", "typer-cli"]
-
 [[package]]
 name = "pdf2image"
 version = "1.16.3"
@@ -3314,13 +3286,13 @@ image = ["Pillow"]
 
 [[package]]
 name = "pdfplumber"
-version = "0.10.2"
+version = "0.10.3"
 description = "Plumb a PDF for detailed information about each char, rectangle, and line."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3470,33 +3442,33 @@ grpc = ["googleapis-common-protos (>=1.53.0)", "grpc-gateway-protoc-gen-openapiv
 
 [[package]]
 name = "playwright"
-version = "1.38.0"
+version = "1.39.0"
 description = "A high-level API to automate web browsers"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-greenlet = "2.0.2"
-pyee = "9.0.4"
+greenlet = "3.0.0"
+pyee = "11.0.1"
 
 [[package]]
 name = "plotly"
-version = "5.17.0"
+version = "5.18.0"
 description = "An open-source, interactive data visualization library for Python"
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [package.dependencies]
@@ -3794,18 +3766,21 @@ email = ["email-validator (>=1.0.3)"]
 
 [[package]]
 name = "pyee"
-version = "9.0.4"
-description = "A port of node.js's EventEmitter to python."
+version = "11.0.1"
+description = "A rough port of Node.js's EventEmitter to Python with a few tricks of its own"
 optional = false
-python-versions = "*"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
 typing-extensions = "*"
 
+[package.extras]
+dev = ["black", "flake8", "flake8-black", "isort", "jupyter-console", "mkdocs", "mkdocs-include-markdown-plugin", "mkdocstrings[python]", "pytest", "pytest-asyncio", "pytest-trio", "toml", "tox", "trio", "trio", "trio-typing", "twine", "twisted", "validate-pyproject[all]"]
+
 [[package]]
 name = "pygments"
 version = "2.16.1"
@@ -3912,23 +3887,24 @@ image = ["Pillow (>=8.0.0)"]
 
 [[package]]
 name = "pypdfium2"
-version = "4.21.0"
+version = "4.22.0"
 description = "Python bindings to PDFium"
 optional = false
 python-versions = ">= 3.6"
 files = [
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 [[package]]
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+version = "7.4.3"
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+    {file = "spacy-3.7.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9ccbffb7825c08c0586ef7384d0aa23196f9ac106b5c7b3c551907316930f94f"},
+    {file = "spacy-3.7.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:111955d7f4786b952672e9c5cfd9f8b74d81e64b62d479f71efe9cfc2a027a1d"},
+    {file = "spacy-3.7.2-cp39-cp39-win_amd64.whl", hash = "sha256:e8a7291e7e1cfcb6041b26f96d0a66b603725c1beff4e0391c3d9226fae16e04"},
+    {file = "spacy-3.7.2.tar.gz", hash = "sha256:cedf4927bf0d3fec773a6ce48d5d2c91bdb02fed3c7d5ec07bdb873f1126f1a0"},
 ]
 
 [package.dependencies]
@@ -5213,7 +5189,6 @@ langcodes = ">=3.2.0,<4.0.0"
 murmurhash = ">=0.28.0,<1.1.0"
 numpy = {version = ">=1.19.0", markers = "python_version >= \"3.9\""}
 packaging = ">=20.0"
-pathy = ">=0.10.0"
 preshed = ">=3.0.2,<3.1.0"
 pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<3.0.0"
 requests = ">=2.13.0,<3.0.0"
@@ -5618,13 +5593,13 @@ blobfile = ["blobfile (>=2)"]
 
 [[package]]
 name = "timm"
-version = "0.9.7"
+version = "0.9.8"
 description = "PyTorch Image Models"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "timm-0.9.7-py3-none-any.whl", hash = "sha256:1cf1082007aa1353550921804abe292292d51acc8631a140273f81f29b48059f"},
-    {file = "timm-0.9.7.tar.gz", hash = "sha256:2bfb1029e90b72e65eb9c75556169815f2e82257eaa1f6ebd623a4b4a52867a2"},
+    {file = "timm-0.9.8-py3-none-any.whl", hash = "sha256:198632472f470d69397088a5996823eff7f8900413a7616dc96ca7d7b7460026"},
+    {file = "timm-0.9.8.tar.gz", hash = "sha256:7d070a5ca8eea4e8c75bf79595a67efa0ea19bbcf2d5db2ee8e5d87417b70f2f"},
 ]
 
 [package.dependencies]
@@ -5871,13 +5846,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "transformers"
-version = "4.34.0"
+version = "4.34.1"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "transformers-4.34.0-py3-none-any.whl", hash = "sha256:3f0187183a7f22c51ecbbc9eac5145df666c5b86bec6feed10e11f0363f3a1f9"},
-    {file = "transformers-4.34.0.tar.gz", hash = "sha256:cc2ae61bfbfaa45337fd9017326669fc60e4f55125f589d50da47819e3d6f504"},
+    {file = "transformers-4.34.1-py3-none-any.whl", hash = "sha256:d06ac09151d7b845e4a4acd6b143a591d946031ee67b4cbb20693b241920ffc0"},
+    {file = "transformers-4.34.1.tar.gz", hash = "sha256:1d0258d5a18063b66005bbe1e3276ec5943d9ab4ab47f020db1fd485cc40ea22"},
 ]
 
 [package.dependencies]
@@ -6045,13 +6020,13 @@ files = [
 
 [[package]]
 name = "unstructured"
-version = "0.10.23"
+version = "0.10.27"
 description = "A library that prepares raw documents for downstream ML tasks."
 optional = false
 python-versions = ">=3.7.0"
 files = [
-    {file = "unstructured-0.10.23-py3-none-any.whl", hash = "sha256:0a289050b277993887a7dbddfe773f207b86144cfa8fda2200c35547c47b48e5"},
-    {file = "unstructured-0.10.23.tar.gz", hash = "sha256:180d00ecfddfda8621925ddebce7370fcf68a5976e5e6493b0d92447a3d4872b"},
+    {file = "unstructured-0.10.27-py3-none-any.whl", hash = "sha256:3a8a8e44302388ddc39c184059e8b4458f1cdc58032540b9af7d85f6c3eca3be"},
+    {file = "unstructured-0.10.27.tar.gz", hash = "sha256:f567b5c4385993a9ab48db5563dd7b413aac4f2002bb22e6250496ea8f440f5e"},
 ]
 
 [package.dependencies]
@@ -6073,14 +6048,16 @@ python-magic = "*"
 rapidfuzz = "*"
 requests = "*"
 tabulate = "*"
-unstructured-inference = {version = "0.7.5", optional = true, markers = "extra == \"pdf\""}
+typing-extensions = "*"
+unstructured-inference = {version = "0.7.10", optional = true, markers = "extra == \"pdf\""}
 "unstructured.pytesseract" = {version = ">=0.3.12", optional = true, markers = "extra == \"pdf\""}
 
 [package.extras]
 airtable = ["pyairtable"]
-all-docs = ["ebooklib", "markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.0.1)", "python-pptx (<=0.6.21)", "unstructured-inference (==0.7.5)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
+all-docs = ["markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.0.1)", "python-pptx (<=0.6.21)", "unstructured-inference (==0.7.10)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
 azure = ["adlfs", "fsspec (==2023.9.1)"]
 azure-cognitive-search = ["azure-search-documents"]
+bedrock = ["boto3", "langchain"]
 biomed = ["bs4"]
 box = ["boxfs", "fsspec (==2023.9.1)"]
 confluence = ["atlassian-python-api"]
@@ -6091,15 +6068,16 @@ doc = ["python-docx (>=1.0.1)"]
 docx = ["python-docx (>=1.0.1)"]
 dropbox = ["dropboxdrivefs", "fsspec (==2023.9.1)"]
 elasticsearch = ["elasticsearch", "jq"]
-epub = ["ebooklib"]
+embed-huggingface = ["huggingface", "langchain", "sentence-transformers"]
+epub = ["pypandoc"]
 gcs = ["bs4", "fsspec (==2023.9.1)", "gcsfs"]
 github = ["pygithub (>1.58.0)"]
 gitlab = ["python-gitlab"]
 google-drive = ["google-api-python-client"]
 huggingface = ["langdetect", "sacremoses", "sentencepiece", "torch", "transformers"]
-image = ["onnx", "pdf2image", "pdfminer.six", "unstructured-inference (==0.7.5)", "unstructured.pytesseract (>=0.3.12)"]
+image = ["onnx", "pdf2image", "pdfminer.six", "unstructured-inference (==0.7.10)", "unstructured.pytesseract (>=0.3.12)"]
 jira = ["atlassian-python-api"]
-local-inference = ["ebooklib", "markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.0.1)", "python-pptx (<=0.6.21)", "unstructured-inference (==0.7.5)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
+local-inference = ["markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.0.1)", "python-pptx (<=0.6.21)", "unstructured-inference (==0.7.10)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
 md = ["markdown"]
 msg = ["msg-parser"]
 notion = ["htmlBuilder", "notion-client"]
@@ -6109,7 +6087,7 @@ openai = ["langchain", "openai", "tiktoken"]
 org = ["pypandoc"]
 outlook = ["Office365-REST-Python-Client (<2.4.3)", "msal"]
 paddleocr = ["unstructured.paddleocr (==2.6.1.3)"]
-pdf = ["onnx", "pdf2image", "pdfminer.six", "unstructured-inference (==0.7.5)", "unstructured.pytesseract (>=0.3.12)"]
+pdf = ["onnx", "pdf2image", "pdfminer.six", "unstructured-inference (==0.7.10)", "unstructured.pytesseract (>=0.3.12)"]
 ppt = ["python-pptx (<=0.6.21)"]
 pptx = ["python-pptx (<=0.6.21)"]
 reddit = ["praw"]
@@ -6125,18 +6103,19 @@ xlsx = ["networkx", "openpyxl", "pandas", "xlrd"]
 
 [[package]]
 name = "unstructured-inference"
-version = "0.7.5"
+version = "0.7.10"
 description = "A library for performing inference using trained models."
 optional = false
 python-versions = ">=3.7.0"
 files = [
-    {file = "unstructured_inference-0.7.5-py3-none-any.whl", hash = "sha256:d9a6d618abdab94dcd4f5e05a646a0130389ff6c3701b8b4d24e04c005db8867"},
-    {file = "unstructured_inference-0.7.5.tar.gz", hash = "sha256:c94b98ec24c91600a1c90d0a372cc4697fb895113f9afc8cfabfd295eb6e0412"},
+    {file = "unstructured_inference-0.7.10-py3-none-any.whl", hash = "sha256:047d9fab0ed2a35f655f4b07faaf2422b4b93dd32daeb5f453744f534e51ea84"},
+    {file = "unstructured_inference-0.7.10.tar.gz", hash = "sha256:be46bc58832cfacf3472d8180479b67839cfeec2b0106ddaada3ce84a33f9780"},
 ]
 
 [package.dependencies]
 huggingface-hub = "*"
 layoutparser = {version = "*", extras = ["layoutmodels", "tesseract"]}
+onnx = "*"
 onnxruntime = "<1.16"
 opencv-python = "!=4.7.0.68"
 python-multipart = "*"
@@ -6163,13 +6142,13 @@ Pillow = ">=8.0.0"
 
 [[package]]
 name = "urllib3"
-version = "1.26.17"
+version = "1.26.18"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
-    {file = "urllib3-1.26.17-py2.py3-none-any.whl", hash = "sha256:94a757d178c9be92ef5539b8840d48dc9cf1b2709c9d6b588232a055c524458b"},
-    {file = "urllib3-1.26.17.tar.gz", hash = "sha256:24d6a242c28d29af46c3fae832c36db3bbebcc533dd1bb549172cd739c82df21"},
+    {file = "urllib3-1.26.18-py2.py3-none-any.whl", hash = "sha256:34b97092d7e0a3a8cf7cd10e386f401b3737364026c45e622aa02903dffe0f07"},
+    {file = "urllib3-1.26.18.tar.gz", hash = "sha256:f8ecc1bba5667413457c529ab955bf8c67b45db799d159066261719e328580a0"},
 ]
 
 [package.dependencies]
@@ -6258,13 +6237,13 @@ wasabi = ">=0.9.1,<1.2.0"
 
 [[package]]
 name = "weaviate-client"
-version = "3.24.2"
+version = "3.25.1"
 description = "A python native Weaviate client"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "weaviate-client-3.24.2.tar.gz", hash = "sha256:6914c48c9a7e5ad0be9399271f9cb85d6f59ab77476c6d4e56a3925bf149edaa"},
-    {file = "weaviate_client-3.24.2-py3-none-any.whl", hash = "sha256:bc50ca5fcebcd48de0d00f66700b0cf7c31a97c4cd3d29b4036d77c5d1d9479b"},
+    {file = "weaviate-client-3.25.1.tar.gz", hash = "sha256:cfa6435e365bae734d875013124baa14cada7e36af4f2d82def5a15b44374978"},
+    {file = "weaviate_client-3.25.1-py3-none-any.whl", hash = "sha256:94680aff46c3ad2748a7c6530c6466c6aee6d03b5b69c0c814f987f2fdefae36"},
 ]
 
 [package.dependencies]
@@ -6277,20 +6256,20 @@ grpc = ["grpcio (>=1.57.0,<2.0.0)", "grpcio-tools (>=1.57.0,<2.0.0)"]
 
 [[package]]
 name = "werkzeug"
-version = "2.2.3"
+version = "3.0.1"
 description = "The comprehensive WSGI web application library."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "Werkzeug-2.2.3-py3-none-any.whl", hash = "sha256:56433961bc1f12533306c624f3be5e744389ac61d722175d543e1751285da612"},
-    {file = "Werkzeug-2.2.3.tar.gz", hash = "sha256:2e1ccc9417d4da358b9de6f174e3ac094391ea1d4fbef2d667865d819dfd0afe"},
+    {file = "werkzeug-3.0.1-py3-none-any.whl", hash = "sha256:90a285dc0e42ad56b34e696398b8122ee4c681833fb35b8334a095d82c56da10"},
+    {file = "werkzeug-3.0.1.tar.gz", hash = "sha256:507e811ecea72b18a404947aded4b3390e1db8f826b494d76550ef45bb3b1dcc"},
 ]
 
 [package.dependencies]
 MarkupSafe = ">=2.1.1"
 
 [package.extras]
-watchdog = ["watchdog"]
+watchdog = ["watchdog (>=2.3)"]
 
 [[package]]
 name = "wheel"
diff --git a/level_3/rag_test_manager.py b/level_3/rag_test_manager.py
index 2d5eb38fd..9b87b73cf 100644
--- a/level_3/rag_test_manager.py
+++ b/level_3/rag_test_manager.py
@@ -78,7 +78,6 @@ async def retrieve_latest_test_case(session, user_id, memory_id):
 async def add_entity(session, entity):
     async with session_scope(session) as s:  # Use your async session_scope
         s.add(entity)  # No need to commit; session_scope takes care of it
-        s.commit()
 
         return "Successfully added entity"
 
@@ -278,8 +277,8 @@ async def eval_test(
         test_case = synthetic_test_set
     else:
         test_case = LLMTestCase(
-            query=query,
-            output=result_output,
+            input=query,
+            actual_output=result_output,
             expected_output=expected_output,
             context=context,
         )
@@ -323,8 +322,22 @@ def count_files_in_data_folder(data_folder_path=".data"):
     except Exception as e:
         print(f"An error occurred: {str(e)}")
         return -1  # Return -1 to indicate an error
+# def data_format_route(data_string: str):
+#     @ai_classifier
+#     class FormatRoute(Enum):
+#         """Represents classifier for the data format"""
+#
+#         PDF = "PDF"
+#         UNSTRUCTURED_WEB = "UNSTRUCTURED_WEB"
+#         GITHUB = "GITHUB"
+#         TEXT = "TEXT"
+#         CSV = "CSV"
+#         WIKIPEDIA = "WIKIPEDIA"
+#
+#     return FormatRoute(data_string).name
+
+
 def data_format_route(data_string: str):
-    @ai_classifier
     class FormatRoute(Enum):
         """Represents classifier for the data format"""
 
@@ -335,20 +348,59 @@ def data_format_route(data_string: str):
         CSV = "CSV"
         WIKIPEDIA = "WIKIPEDIA"
 
-    return FormatRoute(data_string).name
+    # Convert the input string to lowercase for case-insensitive matching
+    data_string = data_string.lower()
+
+    # Mapping of keywords to categories
+    keyword_mapping = {
+        "pdf": FormatRoute.PDF,
+        "web": FormatRoute.UNSTRUCTURED_WEB,
+        "github": FormatRoute.GITHUB,
+        "text": FormatRoute.TEXT,
+        "csv": FormatRoute.CSV,
+        "wikipedia": FormatRoute.WIKIPEDIA
+    }
+
+    # Try to match keywords in the data string
+    for keyword, category in keyword_mapping.items():
+        if keyword in data_string:
+            return category.name
+
+    # Return a default category if no match is found
+    return FormatRoute.PDF.name
 
 
+# def data_location_route(data_string: str):
+#     @ai_classifier
+#     class LocationRoute(Enum):
+#         """Represents classifier for the data location, if it is device, or database connections string or URL"""
+#
+#         DEVICE = "file_path_starting_with_.data_or_containing_it"
+#         URL = "url starting with http or https"
+#         DATABASE = "database_name_like_postgres_or_mysql"
+#
+#     return LocationRoute(data_string).name
 def data_location_route(data_string: str):
-    @ai_classifier
     class LocationRoute(Enum):
-        """Represents classifier for the data location, if it is device, or database connections string or URL"""
+        """Represents classifier for the data location, if it is device, or database connection string or URL"""
 
-        DEVICE = "file_path_starting_with_.data_or_containing_it"
-        # URL = "url starting with http or https"
-        DATABASE = "database_name_like_postgres_or_mysql"
+        DEVICE = "DEVICE"
+        URL = "URL"
+        DATABASE = "DATABASE"
 
-    return LocationRoute(data_string).name
+    # Convert the input string to lowercase for case-insensitive matching
+    data_string = data_string.lower()
 
+    # Check for specific patterns in the data string
+    if data_string.startswith(".data") or "data" in data_string:
+        return LocationRoute.DEVICE.name
+    elif data_string.startswith("http://") or data_string.startswith("https://"):
+        return LocationRoute.URL.name
+    elif "postgres" in data_string or "mysql" in data_string:
+        return LocationRoute.DATABASE.name
+
+    # Return a default category if no match is found
+    return "Unknown"
 
 def dynamic_test_manager(context=None):
     from deepeval.dataset import create_evaluation_query_answer_pairs
@@ -373,7 +425,6 @@ async def start_test(
     test_set=None,
     user_id=None,
     params=None,
-    job_id=None,
     metadata=None,
     generate_test_set=False,
     retriever_type: str = None,
@@ -381,6 +432,7 @@ async def start_test(
     """retriever_type = "llm_context, single_document_context, multi_document_context, "cognitive_architecture""" ""
 
     async with session_scope(session=AsyncSessionLocal()) as session:
+        job_id = ""
         job_id = await fetch_job_id(session, user_id=user_id, job_id=job_id)
         test_set_id = await fetch_test_set_id(session, user_id=user_id, content=str(test_set))
         memory = await Memory.create_memory(
@@ -416,7 +468,7 @@ async def start_test(
             )
             test_params = generate_param_variants(included_params=params)
 
-        print("Here are the test params", str(test_params))
+        logging.info("Here are the test params %s", str(test_params))
 
         loader_settings = {
             "format": f"{data_format}",
@@ -522,12 +574,13 @@ async def start_test(
 
             test_eval_pipeline = []
 
+
+
             if retriever_type == "llm_context":
                 for test_qa in test_set:
                     context = ""
                     logging.info("Loading and evaluating test set for LLM context")
                     test_result = await run_eval(test_qa, context)
-
                     test_eval_pipeline.append(test_result)
             elif retriever_type == "single_document_context":
                 if test_set:
@@ -556,7 +609,12 @@ async def start_test(
 
         results = []
 
+        logging.info("Validating the retriever type")
+
+        logging.info("Retriever type: %s", retriever_type)
+
         if retriever_type == "llm_context":
+            logging.info("Retriever type: llm_context")
             test_id, result = await run_test(
                 test=None,
                 loader_settings=loader_settings,
@@ -566,6 +624,7 @@ async def start_test(
             results.append([result, "No params"])
 
         elif retriever_type == "single_document_context":
+            logging.info("Retriever type: single document context")
             for param in test_params:
                 logging.info("Running for chunk size %s", param["chunk_size"])
                 test_id, result = await run_test(
@@ -636,55 +695,55 @@ async def main():
     ]
     # "https://www.ibiblio.org/ebooks/London/Call%20of%20Wild.pdf"
     # http://public-library.uk/ebooks/59/83.pdf
-    result = await start_test(
-        ".data/3ZCCCW.pdf",
-        test_set=test_set,
-        user_id="677",
-        params=["chunk_size", "search_type"],
-        metadata=metadata,
-        retriever_type="single_document_context",
-    )
-    #
-    # parser = argparse.ArgumentParser(description="Run tests against a document.")
-    # parser.add_argument("--url", required=True, help="URL of the document to test.")
-    # parser.add_argument("--test_set", required=True, help="Path to JSON file containing the test set.")
-    # parser.add_argument("--user_id", required=True, help="User ID.")
-    # parser.add_argument("--params", help="Additional parameters in JSON format.")
-    # parser.add_argument("--metadata", required=True, help="Path to JSON file containing metadata.")
-    # parser.add_argument("--generate_test_set", required=True, help="Make a test set.")
-    # parser.add_argument("--only_llm_context", required=True, help="Do a test only within the existing LLM context")
-    # args = parser.parse_args()
-    #
-    # try:
-    #     with open(args.test_set, "r") as file:
-    #         test_set = json.load(file)
-    #         if not isinstance(test_set, list):  # Expecting a list
-    #             raise TypeError("Parsed test_set JSON is not a list.")
-    # except Exception as e:
-    #     print(f"Error loading test_set: {str(e)}")
-    #     return
-    #
-    # try:
-    #     with open(args.metadata, "r") as file:
-    #         metadata = json.load(file)
-    #         if not isinstance(metadata, dict):
-    #             raise TypeError("Parsed metadata JSON is not a dictionary.")
-    # except Exception as e:
-    #     print(f"Error loading metadata: {str(e)}")
-    #     return
-    #
-    # if args.params:
-    #     try:
-    #         params = json.loads(args.params)
-    #         if not isinstance(params, dict):
-    #             raise TypeError("Parsed params JSON is not a dictionary.")
-    #     except json.JSONDecodeError as e:
-    #         print(f"Error parsing params: {str(e)}")
-    #         return
-    # else:
-    #     params = None
-    # #clean up params here
-    # await start_test(args.url, test_set, args.user_id, params=None, metadata=metadata)
+    # result = await start_test(
+    #     ".data/3ZCCCW.pdf",
+    #     test_set=test_set,
+    #     user_id="677",
+    #     params=["chunk_size", "search_type"],
+    #     metadata=metadata,
+    #     retriever_type="single_document_context",
+    # )
+
+    parser = argparse.ArgumentParser(description="Run tests against a document.")
+    parser.add_argument("--file", required=True, help="URL or location of the document to test.")
+    parser.add_argument("--test_set", required=True, help="Path to JSON file containing the test set.")
+    parser.add_argument("--user_id", required=True, help="User ID.")
+    parser.add_argument("--params", help="Additional parameters in JSON format.")
+    parser.add_argument("--metadata", required=True, help="Path to JSON file containing metadata.")
+    # parser.add_argument("--generate_test_set", required=False, help="Make a test set.")
+    parser.add_argument("--retriever_type", required=False, help="Do a test only within the existing LLM context")
+    args = parser.parse_args()
+
+    try:
+        with open(args.test_set, "r") as file:
+            test_set = json.load(file)
+            if not isinstance(test_set, list):  # Expecting a list
+                raise TypeError("Parsed test_set JSON is not a list.")
+    except Exception as e:
+        print(f"Error loading test_set: {str(e)}")
+        return
+
+    try:
+        with open(args.metadata, "r") as file:
+            metadata = json.load(file)
+            if not isinstance(metadata, dict):
+                raise TypeError("Parsed metadata JSON is not a dictionary.")
+    except Exception as e:
+        print(f"Error loading metadata: {str(e)}")
+        return
+
+    if args.params:
+        try:
+            params = json.loads(args.params)
+            if not isinstance(params, dict):
+                raise TypeError("Parsed params JSON is not a dictionary.")
+        except json.JSONDecodeError as e:
+            print(f"Error parsing params: {str(e)}")
+            return
+    else:
+        params = None
+    #clean up params here
+    await start_test(data=args.file, test_set=test_set, user_id= args.user_id, params= params, metadata =metadata, retriever_type=args.retriever_type)
 
 
 if __name__ == "__main__":
diff --git a/level_3/vectordb/loaders/loaders.py b/level_3/vectordb/loaders/loaders.py
index 8dad3a5d9..2ed80fe2b 100644
--- a/level_3/vectordb/loaders/loaders.py
+++ b/level_3/vectordb/loaders/loaders.py
@@ -45,7 +45,7 @@ async def _document_loader( observation: str, loader_settings: dict):
             # pages = documents.load_and_split()
             return documents
 
-    elif document_format == "text":
+    elif document_format == "TEXT":
         pages = chunk_data(chunk_strategy= loader_strategy, source_data=observation, chunk_size=chunk_size, chunk_overlap=chunk_overlap)
         return pages
 

From 12796a2ba10133fa5486207b7aff32531c34493f Mon Sep 17 00:00:00 2001
From: Vasilije <8619304+Vasilije1990@users.noreply.github.com>
Date: Sun, 29 Oct 2023 00:18:23 +0200
Subject: [PATCH 2/2] Added docs functionality

---
 level_3/api.py              | 22 ++++++++++++--
 level_3/docker-compose.yml  | 60 ++++++++++++++++++-------------------
 level_3/models/docs.py      | 18 +++++++++++
 level_3/rag_test_manager.py | 56 +++++++++++++++++++++++++++-------
 4 files changed, 113 insertions(+), 43 deletions(-)
 create mode 100644 level_3/models/docs.py

diff --git a/level_3/api.py b/level_3/api.py
index 10c640d0b..953150d61 100644
--- a/level_3/api.py
+++ b/level_3/api.py
@@ -7,8 +7,8 @@ from fastapi import FastAPI
 from fastapi.responses import JSONResponse
 from pydantic import BaseModel
 
-from level_3.database.database import AsyncSessionLocal
-from level_3.database.database_crud import session_scope
+from database.database import AsyncSessionLocal
+from database.database_crud import session_scope
 from vectorstore_manager import Memory
 from dotenv import load_dotenv
 
@@ -202,6 +202,24 @@ for memory_type in memory_list:
     memory_factory(memory_type)
 
 
+@app.post("/rag-test/rag_test_run", response_model=dict)
+async def rag_test_run(
+    payload: Payload,
+    # files: List[UploadFile] = File(...),
+):
+    try:
+        from rag_test_manager import start_test
+        logging.info(" Running RAG Test ")
+        decoded_payload = payload.payload
+        output = await start_test(data=decoded_payload['data'], test_set=decoded_payload['test_set'], user_id=decoded_payload['user_id'], params=decoded_payload['params'], metadata=decoded_payload['metadata'],
+                         retriever_type=decoded_payload['retriever_type'])
+        return JSONResponse(content={"response": output}, status_code=200)
+    except Exception as e:
+        return JSONResponse(
+            content={"response": {"error": str(e)}}, status_code=503
+        )
+
+
 # @app.get("/available-buffer-actions", response_model=dict)
 # async def available_buffer_actions(
 #     payload: Payload,
diff --git a/level_3/docker-compose.yml b/level_3/docker-compose.yml
index 7444aca82..8e7e56698 100644
--- a/level_3/docker-compose.yml
+++ b/level_3/docker-compose.yml
@@ -13,19 +13,19 @@ services:
 #    networks:
 #      - promethai_mem_backend
 
-#  promethai_mem:
-#    networks:
-#      - promethai_mem_backend
-#    build:
-#      context: ./
-#    volumes:
-#      - "./:/app"
-#    environment:
-#      - HOST=0.0.0.0
-#    profiles: ["exclude-from-up"]
-#    ports:
-#      - 8000:8000
-#      - 443:443
+  promethai_mem:
+    networks:
+      - promethai_mem_backend
+    build:
+      context: ./
+    volumes:
+      - "./:/app"
+    environment:
+      - HOST=0.0.0.0
+    profiles: ["exclude-from-up"]
+    ports:
+      - 8000:8000
+      - 443:443
 
   postgres:
     image: postgres
@@ -40,23 +40,23 @@ services:
     ports:
       - "5432:5432"
 
-  superset:
-    platform: linux/amd64
-    build:
-      context: ./superset
-      dockerfile: Dockerfile
-    container_name: superset
-    environment:
-      - ADMIN_USERNAME=admin
-      - ADMIN_EMAIL=vasilije@topoteretes.com
-      - ADMIN_PASSWORD=admin
-      - POSTGRES_USER=bla
-      - POSTGRES_PASSWORD=bla
-      - POSTGRES_DB=bubu
-    networks:
-      - promethai_mem_backend
-    ports:
-      - '8088:8088'
+#  superset:
+#    platform: linux/amd64
+#    build:
+#      context: ./superset
+#      dockerfile: Dockerfile
+#    container_name: superset
+#    environment:
+#      - ADMIN_USERNAME=admin
+#      - ADMIN_EMAIL=vasilije@topoteretes.com
+#      - ADMIN_PASSWORD=admin
+#      - POSTGRES_USER=bla
+#      - POSTGRES_PASSWORD=bla
+#      - POSTGRES_DB=bubu
+#    networks:
+#      - promethai_mem_backend
+#    ports:
+#      - '8088:8088'
 
 networks:
   promethai_mem_backend:
diff --git a/level_3/models/docs.py b/level_3/models/docs.py
new file mode 100644
index 000000000..95d98c485
--- /dev/null
+++ b/level_3/models/docs.py
@@ -0,0 +1,18 @@
+
+from datetime import datetime
+from sqlalchemy import Column, Integer, String, DateTime, ForeignKey
+from sqlalchemy.orm import relationship
+import os
+import sys
+sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+from database.database import Base
+class DocsModel(Base):
+    __tablename__ = 'docs'
+
+    id = Column(String, primary_key=True)
+    operation_id = Column(String, ForeignKey('operations.id'), index=True)
+    doc_name = Column(String, nullable=True)
+    created_at = Column(DateTime, default=datetime.utcnow)
+    updated_at = Column(DateTime, onupdate=datetime.utcnow)
+
+    operation = relationship("Operation", back_populates="docs")
diff --git a/level_3/rag_test_manager.py b/level_3/rag_test_manager.py
index 9b87b73cf..63ce1f388 100644
--- a/level_3/rag_test_manager.py
+++ b/level_3/rag_test_manager.py
@@ -73,7 +73,41 @@ async def retrieve_latest_test_case(session, user_id, memory_id):
             f"An error occurred while retrieving the latest test case: {str(e)}"
         )
         return None
+def get_document_names(doc_input):
+    """
+    Get a list of document names.
 
+    This function takes doc_input, which can be a folder path, a single document file path, or a document name as a string.
+    It returns a list of document names based on the doc_input.
+
+    Args:
+        doc_input (str): The doc_input can be a folder path, a single document file path, or a document name as a string.
+
+    Returns:
+        list: A list of document names.
+
+    Example usage:
+        - Folder path: get_document_names(".data")
+        - Single document file path: get_document_names(".data/example.pdf")
+        - Document name provided as a string: get_document_names("example.docx")
+    """
+    if os.path.isdir(doc_input):
+        # doc_input is a folder
+        folder_path = doc_input
+        document_names = []
+        for filename in os.listdir(folder_path):
+            if os.path.isfile(os.path.join(folder_path, filename)):
+                document_names.append(filename)
+        return document_names
+    elif os.path.isfile(doc_input):
+        # doc_input is a single document file
+        return [os.path.basename(doc_input)]
+    elif isinstance(doc_input, str):
+        # doc_input is a document name provided as a string
+        return [doc_input]
+    else:
+        # doc_input is not valid
+        return []
 
 async def add_entity(session, entity):
     async with session_scope(session) as s:  # Use your async session_scope
@@ -369,17 +403,6 @@ def data_format_route(data_string: str):
     # Return a default category if no match is found
     return FormatRoute.PDF.name
 
-
-# def data_location_route(data_string: str):
-#     @ai_classifier
-#     class LocationRoute(Enum):
-#         """Represents classifier for the data location, if it is device, or database connections string or URL"""
-#
-#         DEVICE = "file_path_starting_with_.data_or_containing_it"
-#         URL = "url starting with http or https"
-#         DATABASE = "database_name_like_postgres_or_mysql"
-#
-#     return LocationRoute(data_string).name
 def data_location_route(data_string: str):
     class LocationRoute(Enum):
         """Represents classifier for the data location, if it is device, or database connection string or URL"""
@@ -489,6 +512,17 @@ async def start_test(
                     test_set_id=test_set_id,
                 ),
             )
+            doc_names = get_document_names(data)
+            for doc in doc_names:
+
+                await add_entity(
+                    session,
+                    Docs(
+                        id=str(uuid.uuid4()),
+                        operation_id=job_id,
+                        doc_name = doc
+                    )
+                )
 
         async def run_test(
             test, loader_settings, metadata, test_id=None, retriever_type=False