From cdc12090612395995f8de4039570749e105963a4 Mon Sep 17 00:00:00 2001
From: James Briggs <james.briggs@hotmail.com>
Date: Sat, 31 Aug 2024 17:55:56 +0200
Subject: [PATCH 1/7] chore: change docs workflow temp

---
 .github/workflows/docs.yml | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index 38ad89a0..e382b9cd 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -1,9 +1,10 @@
 name: Release Docs
 
 on:
-  push:
-    tags:
-      - '*'
+  pull_request:
+  # push:
+  #   tags:
+  #     - '*'
 
 jobs:
   build-docs:

From 64298167d8f500dc5b0af8e4b1213a1716b6e7fb Mon Sep 17 00:00:00 2001
From: James Briggs <james.briggs@hotmail.com>
Date: Sat, 31 Aug 2024 18:54:17 +0200
Subject: [PATCH 2/7] chore: docs workflow

---
 .github/workflows/docs.yml |    5 +-
 poetry.lock                | 1419 +++++++++++++++++++-----------------
 pyproject.toml             |    5 +-
 3 files changed, 749 insertions(+), 680 deletions(-)

diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index e382b9cd..a32d5ed6 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -38,11 +38,10 @@ jobs:
           cache: poetry
       - name: Install dependencies
         run: |
-          poetry install
-          pip install -r docs/source/requirements.txt
+          poetry install --all-extras
       - name: Build docs
         run: |
-          sphinx-build -M html docs/source docs/build
+          poetry run sphinx-build -M html docs/source docs/build
       - name: Authenticate to Google Cloud
         id: auth
         uses: google-github-actions/auth@v2
diff --git a/poetry.lock b/poetry.lock
index a6d4c7d7..e13210e7 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,99 +1,114 @@
-# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.3.5"
+version = "2.4.0"
 description = "Happy Eyeballs for asyncio"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "aiohappyeyeballs-2.3.5-py3-none-any.whl", hash = "sha256:4d6dea59215537dbc746e93e779caea8178c866856a721c9c660d7a5a7b8be03"},
-    {file = "aiohappyeyeballs-2.3.5.tar.gz", hash = "sha256:6fa48b9f1317254f122a07a131a86b71ca6946ca989ce6326fff54a99a920105"},
+    {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"},
+    {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"},
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.10.2"
+version = "3.10.5"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
@@ -126,7 +141,7 @@ frozenlist = ">=1.1.0"
 name = "alabaster"
 version = "0.7.16"
 description = "A light, configurable Sphinx theme"
-optional = false
+optional = true
 python-versions = ">=3.9"
 files = [
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@@ -229,7 +244,7 @@ tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
 name = "babel"
 version = "2.16.0"
 description = "Internationalization utilities"
-optional = false
+optional = true
 python-versions = ">=3.8"
 files = [
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@@ -243,7 +258,7 @@ dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
 name = "beautifulsoup4"
 version = "4.12.3"
 description = "Screen-scraping library"
-optional = false
+optional = true
 python-versions = ">=3.6.0"
 files = [
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@@ -310,17 +325,17 @@ uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
 name = "boto3"
-version = "1.34.157"
+version = "1.35.10"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "boto3-1.35.10.tar.gz", hash = "sha256:189ab1e2b4cd86df56f82438d89b4040eb140c92683f1bda7cb2e62624f20ea5"},
 ]
 
 [package.dependencies]
-botocore = ">=1.34.157,<1.35.0"
+botocore = ">=1.35.10,<1.36.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -329,13 +344,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.34.157"
+version = "1.35.10"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -351,24 +366,24 @@ crt = ["awscrt (==0.21.2)"]
 
 [[package]]
 name = "cachetools"
-version = "5.4.0"
+version = "5.5.0"
 description = "Extensible memoizing collections and decorators"
 optional = true
 python-versions = ">=3.7"
 files = [
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 ]
 
 [[package]]
 name = "certifi"
-version = "2024.7.4"
+version = "2024.8.30"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [[package]]
@@ -565,22 +580,23 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [[package]]
 name = "cohere"
-version = "5.6.2"
+version = "5.9.0"
 description = ""
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
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 fastavro = ">=1.9.4,<2.0.0"
 httpx = ">=0.21.2"
-httpx-sse = ">=0.4.0,<0.5.0"
+httpx-sse = "0.4.0"
 parameterized = ">=0.9.0,<0.10.0"
 pydantic = ">=1.9.2"
+pydantic-core = ">=2.18.2,<3.0.0"
 requests = ">=2.0.0,<3.0.0"
 tokenizers = ">=0.15,<1"
 types-requests = ">=2.0.0,<3.0.0"
@@ -650,66 +666,87 @@ test = ["pytest"]
 
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-version = "1.2.1"
+version = "1.3.0"
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 python-versions = ">=3.9"
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 ]
 
 [package.dependencies]
-numpy = ">=1.20"
+numpy = ">=1.23"
 
 [package.extras]
 bokeh = ["bokeh", "selenium"]
 docs = ["furo", "sphinx (>=7.2)", "sphinx-copybutton"]
-mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.8.0)", "types-Pillow"]
+mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.11.1)", "types-Pillow"]
 test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
-test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
+test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist", "wurlitzer"]
 
 [[package]]
 name = "coverage"
@@ -892,7 +929,7 @@ files = [
 name = "docutils"
 version = "0.21.2"
 description = "Docutils -- Python Documentation Utilities"
-optional = false
+optional = true
 python-versions = ">=3.9"
 files = [
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@@ -989,13 +1026,13 @@ zstandard = ["zstandard"]
 
 [[package]]
 name = "fastembed"
-version = "0.3.4"
+version = "0.3.6"
 description = "Fast, light, accurate library built for retrieval embedding generation"
 optional = true
 python-versions = "<3.13,>=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -1234,13 +1271,13 @@ tqdm = ["tqdm"]
 
 [[package]]
 name = "google-api-core"
-version = "2.19.1"
+version = "2.19.2"
 description = "Google API client core library"
 optional = true
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -1265,13 +1302,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.33.0"
+version = "2.34.0"
 description = "Google Authentication Library"
 optional = true
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -1281,20 +1318,20 @@ rsa = ">=3.1.4,<5"
 
 [package.extras]
 aiohttp = ["aiohttp (>=3.6.2,<4.0.0.dev0)", "requests (>=2.20.0,<3.0.0.dev0)"]
-enterprise-cert = ["cryptography (==36.0.2)", "pyopenssl (==22.0.0)"]
+enterprise-cert = ["cryptography", "pyopenssl"]
 pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
 requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-aiplatform"
-version = "1.61.0"
+version = "1.64.0"
 description = "Vertex AI API client library"
 optional = true
 python-versions = ">=3.8"
 files = [
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+    {file = "google-cloud-aiplatform-1.64.0.tar.gz", hash = "sha256:475a612829b283eb8f783e773d37115c30db42e2e50065c8653db0c9bd18b0da"},
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 ]
 
 [package.dependencies]
@@ -1315,16 +1352,16 @@ autologging = ["mlflow (>=1.27.0,<=2.1.1)"]
 cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
 datasets = ["pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)"]
 endpoint = ["requests (>=2.28.1)"]
+evaluation = ["immutabledict", "pandas (>=1.0.0,<2.2.0)", "tqdm (>=4.23.0)"]
 full = ["cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.109.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (>=0.1.6)", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "requests (>=2.28.1)", "setuptools (<70.0.0)", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "tqdm (>=4.23.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)"]
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+langchain = ["langchain (>=0.1.16,<0.3)", "langchain-core (<0.3)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "orjson (<=3.10.6)", "tenacity (<=8.3)"]
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 [package.dependencies]
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 ]
 
 [package.dependencies]
-grpcio = ">=1.65.4"
+grpcio = ">=1.66.1"
 protobuf = ">=5.26.1,<6.0dev"
 setuptools = "*"
 
@@ -1786,13 +1823,13 @@ files = [
 
 [[package]]
 name = "huggingface-hub"
-version = "0.24.5"
+version = "0.24.6"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -1845,20 +1882,20 @@ files = [
 
 [[package]]
 name = "idna"
-version = "3.7"
+version = "3.8"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
-python-versions = ">=3.5"
+python-versions = ">=3.6"
 files = [
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 ]
 
 [[package]]
 name = "imagesize"
 version = "1.4.1"
 description = "Getting image size from png/jpeg/jpeg2000/gif file"
-optional = false
+optional = true
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
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@@ -1867,13 +1904,13 @@ files = [
 
 [[package]]
 name = "importlib-metadata"
-version = "8.2.0"
+version = "8.4.0"
 description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1886,21 +1923,25 @@ test = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "p
 
 [[package]]
 name = "importlib-resources"
-version = "6.4.0"
+version = "6.4.4"
 description = "Read resources from Python packages"
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 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
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 [package.extras]
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+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
+cover = ["pytest-cov"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["jaraco.test (>=5.4)", "pytest (>=6,!=8.1.*)", "zipp (>=3.17)"]
+type = ["pytest-mypy"]
 
 [[package]]
 name = "iniconfig"
@@ -2006,7 +2047,7 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 name = "jinja2"
 version = "3.1.4"
 description = "A very fast and expressive template engine."
-optional = false
+optional = true
 python-versions = ">=3.7"
 files = [
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@@ -2311,7 +2352,7 @@ dev = ["Sphinx (==7.2.5)", "colorama (==0.4.5)", "colorama (==0.4.6)", "exceptio
 name = "markupsafe"
 version = "2.1.5"
 description = "Safely add untrusted strings to HTML/XML markup."
-optional = false
+optional = true
 python-versions = ">=3.7"
 files = [
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@@ -2378,40 +2419,51 @@ files = [
 
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 python-versions = ">=3.9"
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 [package.dependencies]
@@ -2945,14 +2997,14 @@ files = [
 
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 python-versions = ">=3"
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 [[package]]
@@ -3010,55 +3062,55 @@ reference = ["google-re2", "pillow"]
 
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 packaging = "*"
 protobuf = "*"
 sympy = "*"
 
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 [package.dependencies]
@@ -4049,13 +4101,13 @@ cffi = {version = "*", markers = "implementation_name == \"pypy\""}
 
 [[package]]
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-version = "1.10.1"
+version = "1.11.1"
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 python-versions = ">=3.8"
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 [package.dependencies]
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 urllib3 = ">=1.26.14,<3"
 
 [package.extras]
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-fastembed-gpu = ["fastembed-gpu (==0.2.7)"]
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 [[package]]
 name = "regex"
@@ -4391,63 +4443,73 @@ torch = ["safetensors[numpy]", "torch (>=1.10)"]
 
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 ]
 
 [package.dependencies]
@@ -4483,7 +4545,7 @@ files = [
 name = "snowballstemmer"
 version = "2.2.0"
 description = "This package provides 29 stemmers for 28 languages generated from Snowball algorithms."
-optional = false
+optional = true
 python-versions = "*"
 files = [
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@@ -4492,20 +4554,20 @@ files = [
 
 [[package]]
 name = "soupsieve"
-version = "2.5"
+version = "2.6"
 description = "A modern CSS selector implementation for Beautiful Soup."
-optional = false
+optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
 name = "sphinx"
 version = "7.3.7"
 description = "Python documentation generator"
-optional = false
+optional = true
 python-versions = ">=3.9"
 files = [
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@@ -4541,7 +4603,7 @@ test = ["cython (>=3.0)", "defusedxml (>=0.7.1)", "pytest (>=6.0)", "setuptools
 name = "sphinxawesome-theme"
 version = "5.2.0"
 description = "An awesome theme for the Sphinx documentation generator"
-optional = false
+optional = true
 python-versions = "<4.0,>=3.8"
 files = [
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@@ -4556,7 +4618,7 @@ sphinx = {version = ">=7.2,<7.4", markers = "python_version >= \"3.9\" and pytho
 name = "sphinxcontrib-applehelp"
 version = "2.0.0"
 description = "sphinxcontrib-applehelp is a Sphinx extension which outputs Apple help books"
-optional = false
+optional = true
 python-versions = ">=3.9"
 files = [
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@@ -4572,7 +4634,7 @@ test = ["pytest"]
 name = "sphinxcontrib-devhelp"
 version = "2.0.0"
 description = "sphinxcontrib-devhelp is a sphinx extension which outputs Devhelp documents"
-optional = false
+optional = true
 python-versions = ">=3.9"
 files = [
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@@ -4588,7 +4650,7 @@ test = ["pytest"]
 name = "sphinxcontrib-htmlhelp"
 version = "2.1.0"
 description = "sphinxcontrib-htmlhelp is a sphinx extension which renders HTML help files"
-optional = false
+optional = true
 python-versions = ">=3.9"
 files = [
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@@ -4604,7 +4666,7 @@ test = ["html5lib", "pytest"]
 name = "sphinxcontrib-jsmath"
 version = "1.0.1"
 description = "A sphinx extension which renders display math in HTML via JavaScript"
-optional = false
+optional = true
 python-versions = ">=3.5"
 files = [
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@@ -4618,7 +4680,7 @@ test = ["flake8", "mypy", "pytest"]
 name = "sphinxcontrib-qthelp"
 version = "2.0.0"
 description = "sphinxcontrib-qthelp is a sphinx extension which outputs QtHelp documents"
-optional = false
+optional = true
 python-versions = ">=3.9"
 files = [
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@@ -4634,7 +4696,7 @@ test = ["defusedxml (>=0.7.1)", "pytest"]
 name = "sphinxcontrib-serializinghtml"
 version = "2.0.0"
 description = "sphinxcontrib-serializinghtml is a sphinx extension which outputs \"serialized\" HTML files (json and pickle)"
-optional = false
+optional = true
 python-versions = ">=3.9"
 files = [
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@@ -4667,13 +4729,13 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
 [[package]]
 name = "sympy"
-version = "1.13.1"
+version = "1.13.2"
 description = "Computer algebra system (CAS) in Python"
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -5030,13 +5092,13 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "transformers"
-version = "4.44.0"
+version = "4.44.2"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = true
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -5182,13 +5244,13 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "1.26.19"
+version = "1.26.20"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
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 ]
 
 [package.extras]
@@ -5250,101 +5312,103 @@ dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"]
 
 [[package]]
 name = "yarl"
-version = "1.9.4"
+version = "1.9.6"
 description = "Yet another URL library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "yarl-1.9.6-py3-none-any.whl", hash = "sha256:d34a4c6fde4d49aab493214228d0e03f7e5a717f6da4fe65b879a3af3c22ad7b"},
+    {file = "yarl-1.9.6.tar.gz", hash = "sha256:0bdc6a7b59efa0c34c90ef3da864f0c53e81a4640fbc461bfde9f1b0c64c3c81"},
 ]
 
 [package.dependencies]
@@ -5353,21 +5417,26 @@ multidict = ">=4.0"
 
 [[package]]
 name = "zipp"
-version = "3.19.2"
+version = "3.20.1"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.19.2-py3-none-any.whl", hash = "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c"},
-    {file = "zipp-3.19.2.tar.gz", hash = "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19"},
+    {file = "zipp-3.20.1-py3-none-any.whl", hash = "sha256:9960cd8967c8f85a56f920d5d507274e74f9ff813a0ab8889a5b5be2daf44064"},
+    {file = "zipp-3.20.1.tar.gz", hash = "sha256:c22b14cc4763c5a5b04134207736c107db42e9d3ef2d9779d465f5f1bcba572b"},
 ]
 
 [package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
+cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
+type = ["pytest-mypy"]
 
 [extras]
 bedrock = ["boto3", "botocore"]
+docs = ["sphinx", "sphinxawesome-theme"]
 fastembed = ["fastembed"]
 google = ["google-cloud-aiplatform"]
 hybrid = ["pinecone-text"]
@@ -5382,4 +5451,4 @@ vision = ["pillow", "torch", "torchvision", "transformers"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.13"
-content-hash = "32e1158d0742323cf5e3a7262ceec1229829d80df399caa62b5b693bc430932a"
+content-hash = "f90d88d616159aba6b1bb960a620a514ab65e0c74a7467bc4dc2625697d79a06"
diff --git a/pyproject.toml b/pyproject.toml
index 3708ff4c..156d4aac 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -45,6 +45,8 @@ botocore = {version = "^1.34.110", optional = true}
 aiohttp = "^3.9.5"
 fastembed = {version = "^0.3.0", optional = true}
 psycopg2 = {version = "^2.9.9", optional = true}
+sphinx = {version = "^7.0.0", optional = true}
+sphinxawesome-theme = {version = "^5.2.0", optional = true}
 
 [tool.poetry.extras]
 hybrid = ["pinecone-text"]
@@ -58,6 +60,7 @@ google = ["google-cloud-aiplatform"]
 bedrock = ["boto3", "botocore"]
 postgres = ["psycopg2"]
 fastembed = ["fastembed"]
+docs = ["sphinx", "sphinxawesome-theme"]
 
 [tool.poetry.group.dev.dependencies]
 ipykernel = "^6.25.0"
@@ -70,8 +73,6 @@ mypy = "^1.7.1"
 types-pyyaml = "^6.0.12.12"
 types-requests = "^2.31.0"
 black = {extras = ["jupyter"], version = ">=23.12.1,<24.5.0"}
-sphinx = "^7.0.0"
-sphinxawesome-theme = "^5.2.0"
 
 [build-system]
 requires = ["poetry-core"]

From 722086e5b1cedfb49d85ea0a5add5e6c2dec7ce9 Mon Sep 17 00:00:00 2001
From: James Briggs <james.briggs@hotmail.com>
Date: Sat, 31 Aug 2024 19:53:38 +0200
Subject: [PATCH 3/7] feat: new docs

---
 docs/source/route_layer/dynamic-routes.rst    | 748 ++++++++++++++++++
 docs/source/route_layer/local-execution.rst   | 663 ++++++++++++++++
 docs/source/route_layer/route-filter.rst      | 198 +++++
 docs/source/route_layer/route_filter.rst      |   5 -
 .../route_layer/save-load-from-file.rst       | 237 ++++++
 .../route_layer/threshold-optimization.rst    | 371 +++++++++
 6 files changed, 2217 insertions(+), 5 deletions(-)
 create mode 100644 docs/source/route_layer/dynamic-routes.rst
 create mode 100644 docs/source/route_layer/local-execution.rst
 create mode 100644 docs/source/route_layer/route-filter.rst
 delete mode 100644 docs/source/route_layer/route_filter.rst
 create mode 100644 docs/source/route_layer/save-load-from-file.rst
 create mode 100644 docs/source/route_layer/threshold-optimization.rst

diff --git a/docs/source/route_layer/dynamic-routes.rst b/docs/source/route_layer/dynamic-routes.rst
new file mode 100644
index 00000000..9856bbc2
--- /dev/null
+++ b/docs/source/route_layer/dynamic-routes.rst
@@ -0,0 +1,748 @@
+Dynamic Routes
+==============
+
+In semantic-router there are two types of routes that can be chosen.
+Both routes belong to the ``Route`` object, the only difference between
+them is that *static* routes return a ``Route.name`` when chosen,
+whereas *dynamic* routes use an LLM call to produce parameter input
+values.
+
+For example, a *static* route will tell us if a query is talking about
+mathematics by returning the route name (which could be ``"math"`` for
+example). A *dynamic* route does the same thing, but it also extracts
+key information from the input utterance to be used in a function
+associated with that route.
+
+For example we could provide a dynamic route with associated utterances:
+
+::
+
+   "what is x to the power of y?"
+   "what is 9 to the power of 4?"
+   "calculate the result of base x and exponent y"
+   "calculate the result of base 10 and exponent 3"
+   "return x to the power of y"
+
+and we could also provide the route with a schema outlining key features
+of the function:
+
+::
+
+   def power(base: float, exponent: float) -> float:
+       """Raise base to the power of exponent.
+
+       Args:
+           base (float): The base number.
+           exponent (float): The exponent to which the base is raised.
+
+       Returns:
+           float: The result of base raised to the power of exponent.
+       """
+       return base ** exponent
+
+Then, if the users input utterance is “What is 2 to the power of 3?”,
+the route will be triggered, as the input utterance is semantically
+similar to the route utterances. Furthermore, the route utilizes an LLM
+to identify that ``base=2`` and ``expoenent=3``. These values are
+returned in such a way that they can be used in the above ``power``
+function. That is, the dynamic router automates the process of calling
+relevant functions from natural language inputs.
+
+As with static routes, we must create a dynamic route before adding it
+to our route layer. To make a route dynamic, we need to provide the
+``function_schemas`` as a list. Each function schema provides
+instructions on what a function is, so that an LLM can decide how to use
+it correctly.
+
+.. code:: ipython3
+
+    from datetime import datetime
+    from zoneinfo import ZoneInfo
+    
+    
+    def get_time(timezone: str) -> str:
+        """Finds the current time in a specific timezone.
+    
+        :param timezone: The timezone to find the current time in, should
+            be a valid timezone from the IANA Time Zone Database like
+            "America/New_York" or "Europe/London". Do NOT put the place
+            name itself like "rome", or "new york", you must provide
+            the IANA format.
+        :type timezone: str
+        :return: The current time in the specified timezone."""
+        now = datetime.now(ZoneInfo(timezone))
+        return now.strftime("%H:%M")
+
+.. code:: ipython3
+
+    get_time("America/New_York")
+
+
+
+
+.. parsed-literal::
+
+    '17:57'
+
+
+
+To get the function schema we can use the ``get_schemas_openai`` function.
+
+.. code:: ipython3
+
+    from semantic_router.llms.openai import get_schemas_openai
+    
+    schemas = get_schemas_openai([get_time])
+    schemas
+
+
+
+
+.. parsed-literal::
+
+    [{'type': 'function',
+      'function': {'name': 'get_time',
+       'description': 'Finds the current time in a specific timezone.\n\n:param timezone: The timezone to find the current time in, should\n    be a valid timezone from the IANA Time Zone Database like\n    "America/New_York" or "Europe/London". Do NOT put the place\n    name itself like "rome", or "new york", you must provide\n    the IANA format.\n:type timezone: str\n:return: The current time in the specified timezone.',
+       'parameters': {'type': 'object',
+        'properties': {'timezone': {'type': 'string',
+          'description': 'The timezone to find the current time in, should\n    be a valid timezone from the IANA Time Zone Database like\n    "America/New_York" or "Europe/London". Do NOT put the place\n    name itself like "rome", or "new york", you must provide\n    the IANA format.'}},
+        'required': ['timezone']}}}]
+
+
+
+We use this to define our dynamic route:
+
+.. code:: ipython3
+
+    time_route = Route(
+        name="get_time",
+        utterances=[
+            "what is the time in new york city?",
+            "what is the time in london?",
+            "I live in Rome, what time is it?",
+        ],
+        function_schemas=schemas,
+    )
+
+Then add the new route to a route layer.
+
+Full Example
+------------
+
+|Open In Colab| |Open nbviewer|
+
+.. |Open In Colab| image:: https://colab.research.google.com/assets/colab-badge.svg
+   :target: https://colab.research.google.com/github/aurelio-labs/semantic-router/blob/main/docs/02-dynamic-routes.ipynb
+.. |Open nbviewer| image:: https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg
+   :target: https://nbviewer.org/github/aurelio-labs/semantic-router/blob/main/docs/02-dynamic-routes.ipynb
+
+
+Installing the Library
+----------------------
+
+.. code:: ipython3
+
+    !pip install tzdata
+    !pip install -qU semantic-router
+
+
+Initializing Routes and RouteLayer
+----------------------------------
+
+Dynamic routes are treated in the same way as static routes, let's begin
+by initializing a ``RouteLayer`` consisting of static routes.
+
+**⚠️ Note: We have a fully local version of dynamic routes available
+at**
+`docs/05-local-execution.ipynb <https://github.com/aurelio-labs/semantic-router/blob/main/docs/05-local-execution.ipynb>`__\ **\ .
+The local 05 version tends to outperform the OpenAI version we demo in
+this notebook, so we'd recommend trying**
+`05 <https://github.com/aurelio-labs/semantic-router/blob/main/docs/05-local-execution.ipynb>`__\ **\ !**
+
+.. code:: ipython3
+
+    from semantic_router import Route
+    
+    politics = Route(
+        name="politics",
+        utterances=[
+            "isn't politics the best thing ever",
+            "why don't you tell me about your political opinions",
+            "don't you just love the president" "don't you just hate the president",
+            "they're going to destroy this country!",
+            "they will save the country!",
+        ],
+    )
+    chitchat = Route(
+        name="chitchat",
+        utterances=[
+            "how's the weather today?",
+            "how are things going?",
+            "lovely weather today",
+            "the weather is horrendous",
+            "let's go to the chippy",
+        ],
+    )
+    
+    routes = [politics, chitchat]
+
+
+.. parsed-literal::
+
+    c:\Users\Siraj\Documents\Personal\Work\Aurelio\Virtual Environments\semantic_router_3\Lib\site-packages\tqdm\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
+      from .autonotebook import tqdm as notebook_tqdm
+
+
+We initialize our ``RouteLayer`` with our ``encoder`` and ``routes``. We
+can use popular encoder APIs like ``CohereEncoder`` and
+``OpenAIEncoder``, or local alternatives like ``FastEmbedEncoder``.
+
+.. code:: ipython3
+
+    import os
+    from semantic_router import RouteLayer
+    from semantic_router.encoders import OpenAIEncoder
+    
+    # platform.openai.com
+    os.environ["OPENAI_API_KEY"] = "<YOUR_API_KEY>"
+    
+    encoder = OpenAIEncoder()
+    
+    rl = RouteLayer(encoder=encoder, routes=routes)
+
+
+We run the solely static routes layer:
+
+.. code:: ipython3
+
+    rl("how's the weather today?")
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='chitchat', function_call=None, similarity_score=None)
+
+
+
+Creating a Dynamic Route
+------------------------
+
+As with static routes, we must create a dynamic route before adding it
+to our route layer. To make a route dynamic, we need to provide the
+``function_schemas`` as a list. Each function schema provides
+instructions on what a function is, so that an LLM can decide how to use
+it correctly.
+
+.. code:: ipython3
+
+    from datetime import datetime
+    from zoneinfo import ZoneInfo
+    
+    
+    def get_time(timezone: str) -> str:
+        """Finds the current time in a specific timezone.
+    
+        :param timezone: The timezone to find the current time in, should
+            be a valid timezone from the IANA Time Zone Database like
+            "America/New_York" or "Europe/London". Do NOT put the place
+            name itself like "rome", or "new york", you must provide
+            the IANA format.
+        :type timezone: str
+        :return: The current time in the specified timezone."""
+        now = datetime.now(ZoneInfo(timezone))
+        return now.strftime("%H:%M")
+
+.. code:: ipython3
+
+    get_time("America/New_York")
+
+
+
+
+.. parsed-literal::
+
+    '17:57'
+
+
+
+To get the function schema we can use the ``get_schema`` function from
+the ``function_call`` module.
+
+.. code:: ipython3
+
+    from semantic_router.llms.openai import get_schemas_openai
+    
+    schemas = get_schemas_openai([get_time])
+    schemas
+
+
+
+
+.. parsed-literal::
+
+    [{'type': 'function',
+      'function': {'name': 'get_time',
+       'description': 'Finds the current time in a specific timezone.\n\n:param timezone: The timezone to find the current time in, should\n    be a valid timezone from the IANA Time Zone Database like\n    "America/New_York" or "Europe/London". Do NOT put the place\n    name itself like "rome", or "new york", you must provide\n    the IANA format.\n:type timezone: str\n:return: The current time in the specified timezone.',
+       'parameters': {'type': 'object',
+        'properties': {'timezone': {'type': 'string',
+          'description': 'The timezone to find the current time in, should\n    be a valid timezone from the IANA Time Zone Database like\n    "America/New_York" or "Europe/London". Do NOT put the place\n    name itself like "rome", or "new york", you must provide\n    the IANA format.'}},
+        'required': ['timezone']}}}]
+
+
+
+We use this to define our dynamic route:
+
+.. code:: ipython3
+
+    time_route = Route(
+        name="get_time",
+        utterances=[
+            "what is the time in new york city?",
+            "what is the time in london?",
+            "I live in Rome, what time is it?",
+        ],
+        function_schemas=schemas,
+    )
+
+.. code:: ipython3
+
+    time_route.llm
+
+Add the new route to our ``layer``:
+
+.. code:: ipython3
+
+    rl.add(time_route)
+
+
+.. parsed-literal::
+
+    2024-05-08 01:57:56 INFO semantic_router.utils.logger Adding `get_time` route
+
+
+.. code:: ipython3
+
+    time_route.llm
+
+Now we can ask our layer a time related question to trigger our new
+dynamic route.
+
+.. code:: ipython3
+
+    response = rl("what is the time in new york city?")
+    response
+
+
+.. parsed-literal::
+
+    2024-05-08 01:57:57 WARNING semantic_router.utils.logger No LLM provided for dynamic route, will use OpenAI LLM default. Ensure API key is set in OPENAI_API_KEY environment variable.
+    2024-05-08 01:57:58 INFO semantic_router.utils.logger Function inputs: [{'function_name': 'get_time', 'arguments': {'timezone': 'America/New_York'}}]
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='get_time', function_call=[{'function_name': 'get_time', 'arguments': {'timezone': 'America/New_York'}}], similarity_score=None)
+
+
+
+.. code:: ipython3
+
+    print(response.function_call)
+
+
+.. parsed-literal::
+
+    [{'function_name': 'get_time', 'arguments': {'timezone': 'America/New_York'}}]
+
+
+.. code:: ipython3
+
+    import json
+    
+    for call in response.function_call:
+        if call["function_name"] == "get_time":
+            args = call["arguments"]
+            result = get_time(**args)
+    print(result)
+
+
+.. parsed-literal::
+
+    17:57
+
+
+Our dynamic route provides both the route itself *and* the input
+parameters required to use the route.
+
+Dynamic Routes with Multiple Functions
+--------------------------------------
+
+Routes can be assigned multiple functions. Then, when that particular
+Route is selected by the Route Layer, a number of those functions might
+be invoked due to the users utterance containing relevant information
+that fits their arguments.
+
+Let's define a Route that has multiple functions.
+
+.. code:: ipython3
+
+    from datetime import datetime, timedelta
+    from zoneinfo import ZoneInfo
+    
+    
+    # Function with one argument
+    def get_time(timezone: str) -> str:
+        """Finds the current time in a specific timezone.
+    
+        :param timezone: The timezone to find the current time in, should
+            be a valid timezone from the IANA Time Zone Database like
+            "America/New_York" or "Europe/London". Do NOT put the place
+            name itself like "rome", or "new york", you must provide
+            the IANA format.
+        :type timezone: str
+        :return: The current time in the specified timezone."""
+        now = datetime.now(ZoneInfo(timezone))
+        return now.strftime("%H:%M")
+    
+    
+    def get_time_difference(timezone1: str, timezone2: str) -> str:
+        """Calculates the time difference between two timezones.
+        :param timezone1: The first timezone, should be a valid timezone from the IANA Time Zone Database like "America/New_York" or "Europe/London".
+        :param timezone2: The second timezone, should be a valid timezone from the IANA Time Zone Database like "America/New_York" or "Europe/London".
+        :type timezone1: str
+        :type timezone2: str
+        :return: The time difference in hours between the two timezones."""
+        # Get the current time in UTC
+        now_utc = datetime.utcnow().replace(tzinfo=ZoneInfo("UTC"))
+    
+        # Convert the UTC time to the specified timezones
+        tz1_time = now_utc.astimezone(ZoneInfo(timezone1))
+        tz2_time = now_utc.astimezone(ZoneInfo(timezone2))
+    
+        # Calculate the difference in offsets from UTC
+        tz1_offset = tz1_time.utcoffset().total_seconds()
+        tz2_offset = tz2_time.utcoffset().total_seconds()
+    
+        # Calculate the difference in hours
+        hours_difference = (tz2_offset - tz1_offset) / 3600
+    
+        return f"The time difference between {timezone1} and {timezone2} is {hours_difference} hours."
+    
+    
+    # Function with three arguments
+    def convert_time(time: str, from_timezone: str, to_timezone: str) -> str:
+        """Converts a specific time from one timezone to another.
+        :param time: The time to convert in HH:MM format.
+        :param from_timezone: The original timezone of the time, should be a valid IANA timezone.
+        :param to_timezone: The target timezone for the time, should be a valid IANA timezone.
+        :type time: str
+        :type from_timezone: str
+        :type to_timezone: str
+        :return: The converted time in the target timezone.
+        :raises ValueError: If the time format or timezone strings are invalid.
+    
+        Example:
+            convert_time("12:30", "America/New_York", "Asia/Tokyo") -> "03:30"
+        """
+        try:
+            # Use today's date to avoid historical timezone issues
+            today = datetime.now().date()
+            datetime_string = f"{today} {time}"
+            time_obj = datetime.strptime(datetime_string, "%Y-%m-%d %H:%M").replace(
+                tzinfo=ZoneInfo(from_timezone)
+            )
+    
+            converted_time = time_obj.astimezone(ZoneInfo(to_timezone))
+    
+            formatted_time = converted_time.strftime("%H:%M")
+            return formatted_time
+        except Exception as e:
+            raise ValueError(f"Error converting time: {e}")
+
+.. code:: ipython3
+
+    functions = [get_time, get_time_difference, convert_time]
+
+.. code:: ipython3
+
+    # Generate schemas for all functions
+    from semantic_router.llms.openai import get_schemas_openai
+    
+    schemas = get_schemas_openai(functions)
+    schemas
+
+
+
+
+.. parsed-literal::
+
+    [{'type': 'function',
+      'function': {'name': 'get_time',
+       'description': 'Finds the current time in a specific timezone.\n\n:param timezone: The timezone to find the current time in, should\n    be a valid timezone from the IANA Time Zone Database like\n    "America/New_York" or "Europe/London". Do NOT put the place\n    name itself like "rome", or "new york", you must provide\n    the IANA format.\n:type timezone: str\n:return: The current time in the specified timezone.',
+       'parameters': {'type': 'object',
+        'properties': {'timezone': {'type': 'string',
+          'description': 'The timezone to find the current time in, should\n    be a valid timezone from the IANA Time Zone Database like\n    "America/New_York" or "Europe/London". Do NOT put the place\n    name itself like "rome", or "new york", you must provide\n    the IANA format.'}},
+        'required': ['timezone']}}},
+     {'type': 'function',
+      'function': {'name': 'get_time_difference',
+       'description': 'Calculates the time difference between two timezones.\n:param timezone1: The first timezone, should be a valid timezone from the IANA Time Zone Database like "America/New_York" or "Europe/London".\n:param timezone2: The second timezone, should be a valid timezone from the IANA Time Zone Database like "America/New_York" or "Europe/London".\n:type timezone1: str\n:type timezone2: str\n:return: The time difference in hours between the two timezones.',
+       'parameters': {'type': 'object',
+        'properties': {'timezone1': {'type': 'string',
+          'description': 'The first timezone, should be a valid timezone from the IANA Time Zone Database like "America/New_York" or "Europe/London".'},
+         'timezone2': {'type': 'string',
+          'description': 'The second timezone, should be a valid timezone from the IANA Time Zone Database like "America/New_York" or "Europe/London".'}},
+        'required': ['timezone1', 'timezone2']}}},
+     {'type': 'function',
+      'function': {'name': 'convert_time',
+       'description': 'Converts a specific time from one timezone to another.\n:param time: The time to convert in HH:MM format.\n:param from_timezone: The original timezone of the time, should be a valid IANA timezone.\n:param to_timezone: The target timezone for the time, should be a valid IANA timezone.\n:type time: str\n:type from_timezone: str\n:type to_timezone: str\n:return: The converted time in the target timezone.\n:raises ValueError: If the time format or timezone strings are invalid.\n\nExample:\n    convert_time("12:30", "America/New_York", "Asia/Tokyo") -> "03:30"',
+       'parameters': {'type': 'object',
+        'properties': {'time': {'type': 'string',
+          'description': 'The time to convert in HH:MM format.'},
+         'from_timezone': {'type': 'string',
+          'description': 'The original timezone of the time, should be a valid IANA timezone.'},
+         'to_timezone': {'type': 'string',
+          'description': 'The target timezone for the time, should be a valid IANA timezone.'}},
+        'required': ['time', 'from_timezone', 'to_timezone']}}}]
+
+
+
+.. code:: ipython3
+
+    # Define the dynamic route with multiple functions
+    multi_function_route = Route(
+        name="timezone_management",
+        utterances=[
+            # Utterances for get_time function
+            "what is the time in New York?",
+            "current time in Berlin?",
+            "tell me the time in Moscow right now",
+            "can you show me the current time in Tokyo?",
+            "please provide the current time in London",
+            # Utterances for get_time_difference function
+            "how many hours ahead is Tokyo from London?",
+            "time difference between Sydney and Cairo",
+            "what's the time gap between Los Angeles and New York?",
+            "how much time difference is there between Paris and Sydney?",
+            "calculate the time difference between Dubai and Toronto",
+            # Utterances for convert_time function
+            "convert 15:00 from New York time to Berlin time",
+            "change 09:00 from Paris time to Moscow time",
+            "adjust 20:00 from Rome time to London time",
+            "convert 12:00 from Madrid time to Chicago time",
+            "change 18:00 from Beijing time to Los Angeles time"
+            # All three functions
+            "What is the time in Seattle? What is the time difference between Mumbai and Tokyo? What is 5:53 Toronto time in Sydney time?",
+        ],
+        function_schemas=schemas,
+    )
+
+.. code:: ipython3
+
+    routes = [politics, chitchat, multi_function_route]
+
+.. code:: ipython3
+
+    rl2 = RouteLayer(encoder=encoder, routes=routes)
+
+
+.. parsed-literal::
+
+    2024-05-08 01:57:58 INFO semantic_router.utils.logger local
+
+
+Function to Parse Route Layer Responses
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code:: ipython3
+
+    def parse_response(response: str):
+        for call in response.function_call:
+            args = call["arguments"]
+            if call["function_name"] == "get_time":
+                result = get_time(**args)
+                print(result)
+            if call["function_name"] == "get_time_difference":
+                result = get_time_difference(**args)
+                print(result)
+            if call["function_name"] == "convert_time":
+                result = convert_time(**args)
+                print(result)
+
+Checking that Politics Non-Dynamic Route Still Works
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code:: ipython3
+
+    response = rl2("What is your political leaning?")
+    response
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='politics', function_call=None, similarity_score=None)
+
+
+
+Checking that Chitchat Non-Dynamic Route Still Works
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code:: ipython3
+
+    response = rl2("Hello bot, how are you today?")
+    response
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='chitchat', function_call=None, similarity_score=None)
+
+
+
+Testing the ``multi_function_route`` - The ``get_time`` Function
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code:: ipython3
+
+    response = rl2("what is the time in New York?")
+    response
+
+
+.. parsed-literal::
+
+    2024-05-08 01:58:00 WARNING semantic_router.utils.logger No LLM provided for dynamic route, will use OpenAI LLM default. Ensure API key is set in OPENAI_API_KEY environment variable.
+    2024-05-08 01:58:01 INFO semantic_router.utils.logger Function inputs: [{'function_name': 'get_time', 'arguments': {'timezone': 'America/New_York'}}]
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='timezone_management', function_call=[{'function_name': 'get_time', 'arguments': {'timezone': 'America/New_York'}}], similarity_score=None)
+
+
+
+.. code:: ipython3
+
+    parse_response(response)
+
+
+.. parsed-literal::
+
+    17:58
+
+
+Testing the ``multi_function_route`` - The ``get_time_difference`` Function
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code:: ipython3
+
+    response = rl2("What is the time difference between Los Angeles and Istanbul?")
+    response
+
+
+.. parsed-literal::
+
+    2024-05-08 01:58:02 INFO semantic_router.utils.logger Function inputs: [{'function_name': 'get_time_difference', 'arguments': {'timezone1': 'America/Los_Angeles', 'timezone2': 'Europe/Istanbul'}}]
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='timezone_management', function_call=[{'function_name': 'get_time_difference', 'arguments': {'timezone1': 'America/Los_Angeles', 'timezone2': 'Europe/Istanbul'}}], similarity_score=None)
+
+
+
+.. code:: ipython3
+
+    parse_response(response)
+
+
+.. parsed-literal::
+
+    The time difference between America/Los_Angeles and Europe/Istanbul is 10.0 hours.
+
+
+Testing the ``multi_function_route`` - The ``convert_time`` Function
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code:: ipython3
+
+    response = rl2("What is 23:02 Dubai time in Tokyo time? Please and thank you.")
+    response
+
+
+.. parsed-literal::
+
+    2024-05-08 01:58:04 INFO semantic_router.utils.logger Function inputs: [{'function_name': 'convert_time', 'arguments': {'time': '23:02', 'from_timezone': 'Asia/Dubai', 'to_timezone': 'Asia/Tokyo'}}]
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='timezone_management', function_call=[{'function_name': 'convert_time', 'arguments': {'time': '23:02', 'from_timezone': 'Asia/Dubai', 'to_timezone': 'Asia/Tokyo'}}], similarity_score=None)
+
+
+
+.. code:: ipython3
+
+    parse_response(response)
+
+
+.. parsed-literal::
+
+    04:02
+
+
+The Cool Bit - Testing ``multi_function_route`` - Multiple Functions at Once
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code:: ipython3
+
+    response = rl2(
+        """
+        What is the time in Prague?
+        What is the time difference between Frankfurt and Beijing?
+        What is 5:53 Lisbon time in Bangkok time?
+    """
+    )
+
+
+.. parsed-literal::
+
+    2024-05-08 01:58:07 INFO semantic_router.utils.logger Function inputs: [{'function_name': 'get_time', 'arguments': {'timezone': 'Europe/Prague'}}, {'function_name': 'get_time_difference', 'arguments': {'timezone1': 'Europe/Berlin', 'timezone2': 'Asia/Shanghai'}}, {'function_name': 'convert_time', 'arguments': {'time': '05:53', 'from_timezone': 'Europe/Lisbon', 'to_timezone': 'Asia/Bangkok'}}]
+
+
+.. code:: ipython3
+
+    response
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='timezone_management', function_call=[{'function_name': 'get_time', 'arguments': {'timezone': 'Europe/Prague'}}, {'function_name': 'get_time_difference', 'arguments': {'timezone1': 'Europe/Berlin', 'timezone2': 'Asia/Shanghai'}}, {'function_name': 'convert_time', 'arguments': {'time': '05:53', 'from_timezone': 'Europe/Lisbon', 'to_timezone': 'Asia/Bangkok'}}], similarity_score=None)
+
+
+
+.. code:: ipython3
+
+    parse_response(response)
+
+
+.. parsed-literal::
+
+    23:58
+    The time difference between Europe/Berlin and Asia/Shanghai is 6.0 hours.
+    11:53
+
diff --git a/docs/source/route_layer/local-execution.rst b/docs/source/route_layer/local-execution.rst
new file mode 100644
index 00000000..d1e2364e
--- /dev/null
+++ b/docs/source/route_layer/local-execution.rst
@@ -0,0 +1,663 @@
+Local Dynamic Routes
+====================
+
+Fully local Semantic Router with ``llama.cpp`` and HuggingFace Encoder
+----------------------------------------------------------------------
+
+There are many reasons users might choose to roll their own LLMs rather
+than use a third-party service. Whether it's due to cost, privacy or
+compliance, Semantic Router supports the use of “local” LLMs through
+``llama.cpp``.
+
+Using ``llama.cpp`` also enables the use of quantized GGUF models,
+reducing the memory footprint of deployed models, allowing even
+13-billion parameter models to run with hardware acceleration on an
+Apple M1 Pro chip.
+
+Full Example
+------------
+
+|Open In Colab| |Open nbviewer|
+
+.. |Open In Colab| image:: https://colab.research.google.com/assets/colab-badge.svg
+   :target: https://colab.research.google.com/github/aurelio-labs/semantic-router/blob/main/docs/05-local-execution.ipynb
+.. |Open nbviewer| image:: https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg
+   :target: https://nbviewer.org/github/aurelio-labs/semantic-router/blob/main/docs/05-local-execution.ipynb
+
+Below is an example of using semantic router with
+**Mistral-7B-Instruct**, quantized i.
+
+Installing the library
+----------------------
+
+   Note: if you require hardware acceleration via BLAS, CUDA, Metal,
+   etc. please refer to the
+   `abetlen/llama-cpp-python <https://github.com/abetlen/llama-cpp-python#installation-with-specific-hardware-acceleration-blas-cuda-metal-etc>`__
+   repository README.md
+
+.. code:: ipython3
+
+    !pip install -qU "semantic-router[local]"
+
+If you’re running on Apple silicon you can run the following to run with
+Metal hardware acceleration:
+
+.. code:: ipython3
+
+    !CMAKE_ARGS="-DLLAMA_METAL=on"
+
+
+.. parsed-literal::
+
+    'CMAKE_ARGS' is not recognized as an internal or external command,
+    operable program or batch file.
+
+
+Download the Mistral 7B Instruct 4-bit GGUF files
+-------------------------------------------------
+
+We will be using Mistral 7B Instruct, quantized as a 4-bit GGUF file, a
+good balance between performance and ability to deploy on consumer
+hardware
+
+.. code:: ipython3
+
+    ! curl -L "https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GGUF/resolve/main/mistral-7b-instruct-v0.2.Q4_0.gguf?download=true" -o ./mistral-7b-instruct-v0.2.Q4_0.gguf
+    ! ls mistral-7b-instruct-v0.2.Q4_0.gguf
+
+
+.. parsed-literal::
+
+      % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
+                                     Dload  Upload   Total   Spent    Left  Speed
+    
+      0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
+    100  1168  100  1168    0     0   4171      0 --:--:-- --:--:-- --:--:--  4186
+    
+      0 3918M    0 6382k    0     0  7990k      0  0:08:22 --:--:--  0:08:22 7990k
+      0 3918M    0 35.0M    0     0  19.4M      0  0:03:21  0:00:01  0:03:20 28.7M
+      2 3918M    2 78.7M    0     0  28.1M      0  0:02:19  0:00:02  0:02:17 36.2M
+      3 3918M    3  123M    0     0  32.4M      0  0:02:00  0:00:03  0:01:57 39.0M
+      4 3918M    4  171M    0     0  35.6M      0  0:01:49  0:00:04  0:01:45 41.2M
+      5 3918M    5  219M    0     0  37.7M      0  0:01:43  0:00:05  0:01:38 42.5M
+      6 3918M    6  271M    0     0  39.9M      0  0:01:38  0:00:06  0:01:32 47.3M
+      8 3918M    8  326M    0     0  41.8M      0  0:01:33  0:00:07  0:01:26 49.4M
+      9 3918M    9  379M    0     0  42.5M      0  0:01:31  0:00:08  0:01:23 50.1M
+     10 3918M   10  428M    0     0  43.7M      0  0:01:29  0:00:09  0:01:20 51.5M
+     12 3918M   12  490M    0     0  45.3M      0  0:01:26  0:00:10  0:01:16 54.2M
+     13 3918M   13  543M    0     0  46.0M      0  0:01:25  0:00:11  0:01:14 54.4M
+     15 3918M   15  609M    0     0  47.6M      0  0:01:22  0:00:12  0:01:10 56.6M
+     17 3918M   17  672M    0     0  48.7M      0  0:01:20  0:00:13  0:01:07 59.8M
+     18 3918M   18  733M    0     0  49.5M      0  0:01:19  0:00:14  0:01:05 60.8M
+     20 3918M   20  800M    0     0  50.6M      0  0:01:17  0:00:15  0:01:02 62.0M
+     21 3918M   21  861M    0     0  51.2M      0  0:01:16  0:00:16  0:01:00 63.4M
+     23 3918M   23  923M    0     0  51.8M      0  0:01:15  0:00:17  0:00:58 62.7M
+     24 3918M   24  973M    0     0  51.7M      0  0:01:15  0:00:18  0:00:57 60.1M
+     26 3918M   26 1039M    0     0  52.4M      0  0:01:14  0:00:19  0:00:55 61.2M
+     28 3918M   28 1101M    0     0  52.9M      0  0:01:14  0:00:20  0:00:54 60.1M
+     29 3918M   29 1156M    0     0  53.0M      0  0:01:13  0:00:21  0:00:52 59.0M
+     30 3918M   30 1208M    0     0  53.0M      0  0:01:13  0:00:22  0:00:51 57.0M
+     32 3918M   32 1272M    0     0  53.4M      0  0:01:13  0:00:23  0:00:50 59.9M
+     34 3918M   34 1337M    0     0  53.9M      0  0:01:12  0:00:24  0:00:48 59.5M
+     35 3918M   35 1397M    0     0  54.1M      0  0:01:12  0:00:25  0:00:47 59.1M
+     36 3918M   36 1444M    0     0  53.9M      0  0:01:12  0:00:26  0:00:46 57.6M
+     38 3918M   38 1506M    0     0  54.1M      0  0:01:12  0:00:27  0:00:45 59.2M
+     40 3918M   40 1569M    0     0  54.4M      0  0:01:11  0:00:28  0:00:43 59.3M
+     41 3918M   41 1630M    0     0  54.7M      0  0:01:11  0:00:29  0:00:42 58.7M
+     43 3918M   43 1697M    0     0  55.1M      0  0:01:11  0:00:30  0:00:41 60.0M
+     44 3918M   44 1759M    0     0  55.3M      0  0:01:10  0:00:31  0:00:39 63.0M
+     45 3918M   45 1798M    0     0  54.8M      0  0:01:11  0:00:32  0:00:39 58.6M
+     47 3918M   47 1866M    0     0  55.2M      0  0:01:10  0:00:33  0:00:37 59.4M
+     49 3918M   49 1930M    0     0  55.4M      0  0:01:10  0:00:34  0:00:36 59.9M
+     50 3918M   50 1994M    0     0  55.7M      0  0:01:10  0:00:35  0:00:35 59.4M
+     52 3918M   52 2062M    0     0  56.0M      0  0:01:09  0:00:36  0:00:33 60.4M
+     54 3918M   54 2121M    0     0  56.1M      0  0:01:09  0:00:37  0:00:32 64.6M
+     55 3918M   55 2186M    0     0  56.3M      0  0:01:09  0:00:38  0:00:31 63.9M
+     57 3918M   57 2248M    0     0  56.5M      0  0:01:09  0:00:39  0:00:30 63.6M
+     59 3918M   59 2317M    0     0  56.8M      0  0:01:08  0:00:40  0:00:28 64.6M
+     60 3918M   60 2382M    0     0  57.0M      0  0:01:08  0:00:41  0:00:27 64.1M
+     62 3918M   62 2435M    0     0  56.8M      0  0:01:08  0:00:42  0:00:26 62.7M
+     63 3918M   63 2496M    0     0  56.9M      0  0:01:08  0:00:43  0:00:25 62.0M
+     64 3918M   64 2546M    0     0  56.8M      0  0:01:08  0:00:44  0:00:24 59.5M
+     66 3918M   66 2596M    0     0  56.6M      0  0:01:09  0:00:45  0:00:24 55.7M
+     67 3918M   67 2646M    0     0  56.5M      0  0:01:09  0:00:46  0:00:23 52.7M
+     69 3918M   69 2708M    0     0  56.6M      0  0:01:09  0:00:47  0:00:22 54.7M
+     70 3918M   70 2773M    0     0  56.8M      0  0:01:08  0:00:48  0:00:20 55.4M
+     72 3918M   72 2833M    0     0  56.9M      0  0:01:08  0:00:49  0:00:19 57.4M
+     73 3918M   73 2896M    0     0  56.9M      0  0:01:08  0:00:50  0:00:18 59.7M
+     75 3918M   75 2952M    0     0  56.9M      0  0:01:08  0:00:51  0:00:17 61.1M
+     76 3918M   76 3012M    0     0  57.0M      0  0:01:08  0:00:52  0:00:16 60.3M
+     78 3918M   78 3078M    0     0  57.2M      0  0:01:08  0:00:53  0:00:15 60.9M
+     80 3918M   80 3140M    0     0  57.3M      0  0:01:08  0:00:54  0:00:14 61.3M
+     81 3918M   81 3196M    0     0  57.2M      0  0:01:08  0:00:55  0:00:13 60.1M
+     83 3918M   83 3261M    0     0  57.4M      0  0:01:08  0:00:56  0:00:12 61.7M
+     84 3918M   84 3324M    0     0  57.5M      0  0:01:08  0:00:57  0:00:11 62.8M
+     86 3918M   86 3390M    0     0  57.6M      0  0:01:07  0:00:58  0:00:09 62.4M
+     88 3918M   88 3456M    0     0  57.7M      0  0:01:07  0:00:59  0:00:08 63.1M
+     89 3918M   89 3520M    0     0  57.9M      0  0:01:07  0:01:00  0:00:07 64.8M
+     91 3918M   91 3585M    0     0  58.0M      0  0:01:07  0:01:01  0:00:06 64.9M
+     93 3918M   93 3654M    0     0  58.1M      0  0:01:07  0:01:02  0:00:05 65.8M
+     94 3918M   94 3719M    0     0  58.2M      0  0:01:07  0:01:03  0:00:04 65.7M
+     96 3918M   96 3778M    0     0  58.3M      0  0:01:07  0:01:04  0:00:03 64.5M
+     97 3918M   97 3828M    0     0  58.1M      0  0:01:07  0:01:05  0:00:02 61.6M
+     99 3918M   99 3888M    0     0  58.2M      0  0:01:07  0:01:06  0:00:01 60.6M
+    100 3918M  100 3918M    0     0  58.2M      0  0:01:07  0:01:07 --:--:-- 58.8M
+    'ls' is not recognized as an internal or external command,
+    operable program or batch file.
+
+
+Initializing Dynamic Routes
+===========================
+
+Similar to the ``02-dynamic-routes.ipynb`` notebook, we will be
+initializing some dynamic routes that make use of LLMs for function
+calling
+
+.. code:: ipython3
+
+    from datetime import datetime
+    from zoneinfo import ZoneInfo
+    
+    from semantic_router import Route
+    from semantic_router.utils.function_call import get_schema
+    
+    
+    def get_time(timezone: str) -> str:
+        """Finds the current time in a specific timezone.
+    
+        :param timezone: The timezone to find the current time in, should
+            be a valid timezone from the IANA Time Zone Database like
+            "America/New_York" or "Europe/London". Do NOT put the place
+            name itself like "rome", or "new york", you must provide
+            the IANA format.
+        :type timezone: str
+        :return: The current time in the specified timezone."""
+        now = datetime.now(ZoneInfo(timezone))
+        return now.strftime("%H:%M")
+    
+    
+    time_schema = get_schema(get_time)
+    time_schema
+    time = Route(
+        name="get_time",
+        utterances=[
+            "what is the time in new york city?",
+            "what is the time in london?",
+            "I live in Rome, what time is it?",
+        ],
+        function_schemas=[time_schema],
+    )
+    
+    politics = Route(
+        name="politics",
+        utterances=[
+            "isn't politics the best thing ever",
+            "why don't you tell me about your political opinions",
+            "don't you just love the president" "don't you just hate the president",
+            "they're going to destroy this country!",
+            "they will save the country!",
+        ],
+    )
+    chitchat = Route(
+        name="chitchat",
+        utterances=[
+            "how's the weather today?",
+            "how are things going?",
+            "lovely weather today",
+            "the weather is horrendous",
+            "let's go to the chippy",
+        ],
+    )
+    
+    routes = [politics, chitchat, time]
+
+
+.. parsed-literal::
+
+    c:\Users\Siraj\Documents\Personal\Work\Aurelio\Virtual Environments\semantic_router_3\Lib\site-packages\tqdm\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
+      from .autonotebook import tqdm as notebook_tqdm
+
+
+.. code:: ipython3
+
+    time_schema
+
+
+
+
+.. parsed-literal::
+
+    {'name': 'get_time',
+     'description': 'Finds the current time in a specific timezone.\n\n:param timezone: The timezone to find the current time in, should\n    be a valid timezone from the IANA Time Zone Database like\n    "America/New_York" or "Europe/London". Do NOT put the place\n    name itself like "rome", or "new york", you must provide\n    the IANA format.\n:type timezone: str\n:return: The current time in the specified timezone.',
+     'signature': '(timezone: str) -> str',
+     'output': "<class 'str'>"}
+
+
+
+Encoders
+========
+
+You can use alternative Encoders, however, in this example we want to
+showcase a fully-local Semantic Router execution, so we are going to use
+a ``HuggingFaceEncoder`` with ``sentence-transformers/all-MiniLM-L6-v2``
+(the default) as an embedding model.
+
+.. code:: ipython3
+
+    from semantic_router.encoders import HuggingFaceEncoder
+    
+    encoder = HuggingFaceEncoder()
+
+``llama.cpp`` LLM
+=================
+
+From here, we can go ahead and instantiate our ``llama-cpp-python``
+``llama_cpp.Llama`` LLM, and then pass it to the
+``semantic_router.llms.LlamaCppLLM`` wrapper class.
+
+For ``llama_cpp.Llama``, there are a couple of parameters you should pay
+attention to:
+
+-  ``n_gpu_layers``: how many LLM layers to offload to the GPU (if you
+   want to offload the entire model, pass ``-1``, and for CPU execution,
+   pass ``0``)
+-  ``n_ctx``: context size, limit the number of tokens that can be
+   passed to the LLM (this is bounded by the model’s internal maximum
+   context size, in this case for Mistral-7B-Instruct, 8000 tokens)
+-  ``verbose``: if ``False``, silences output from ``llama.cpp``
+
+..
+
+   For other parameter explanation, refer to the ``llama-cpp-python``
+   `API
+   Reference <https://llama-cpp-python.readthedocs.io/en/latest/api-reference/>`__
+
+.. code:: ipython3
+
+    from semantic_router import RouteLayer
+    
+    from llama_cpp import Llama
+    from semantic_router.llms.llamacpp import LlamaCppLLM
+    
+    enable_gpu = True  # offload LLM layers to the GPU (must fit in memory)
+    
+    _llm = Llama(
+        model_path="./mistral-7b-instruct-v0.2.Q4_0.gguf",
+        n_gpu_layers=-1 if enable_gpu else 0,
+        n_ctx=2048,
+    )
+    _llm.verbose = False
+    llm = LlamaCppLLM(name="Mistral-7B-v0.2-Instruct", llm=_llm, max_tokens=None)
+    
+    rl = RouteLayer(encoder=encoder, routes=routes, llm=llm)
+
+
+.. parsed-literal::
+
+    llama_model_loader: loaded meta data with 24 key-value pairs and 291 tensors from ./mistral-7b-instruct-v0.2.Q4_0.gguf (version GGUF V3 (latest))
+    llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
+    llama_model_loader: - kv   0:                       general.architecture str              = llama
+    llama_model_loader: - kv   1:                               general.name str              = mistralai_mistral-7b-instruct-v0.2
+    llama_model_loader: - kv   2:                       llama.context_length u32              = 32768
+    llama_model_loader: - kv   3:                     llama.embedding_length u32              = 4096
+    llama_model_loader: - kv   4:                          llama.block_count u32              = 32
+    llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
+    llama_model_loader: - kv   6:                 llama.rope.dimension_count u32              = 128
+    llama_model_loader: - kv   7:                 llama.attention.head_count u32              = 32
+    llama_model_loader: - kv   8:              llama.attention.head_count_kv u32              = 8
+    llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
+    llama_model_loader: - kv  10:                       llama.rope.freq_base f32              = 1000000.000000
+    llama_model_loader: - kv  11:                          general.file_type u32              = 2
+    llama_model_loader: - kv  12:                       tokenizer.ggml.model str              = llama
+    llama_model_loader: - kv  13:                      tokenizer.ggml.tokens arr[str,32000]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
+    llama_model_loader: - kv  14:                      tokenizer.ggml.scores arr[f32,32000]   = [0.000000, 0.000000, 0.000000, 0.0000...
+    llama_model_loader: - kv  15:                  tokenizer.ggml.token_type arr[i32,32000]   = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
+    llama_model_loader: - kv  16:                tokenizer.ggml.bos_token_id u32              = 1
+    llama_model_loader: - kv  17:                tokenizer.ggml.eos_token_id u32              = 2
+    llama_model_loader: - kv  18:            tokenizer.ggml.unknown_token_id u32              = 0
+    llama_model_loader: - kv  19:            tokenizer.ggml.padding_token_id u32              = 0
+    llama_model_loader: - kv  20:               tokenizer.ggml.add_bos_token bool             = true
+    llama_model_loader: - kv  21:               tokenizer.ggml.add_eos_token bool             = false
+    llama_model_loader: - kv  22:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
+    llama_model_loader: - kv  23:               general.quantization_version u32              = 2
+    llama_model_loader: - type  f32:   65 tensors
+    llama_model_loader: - type q4_0:  225 tensors
+    llama_model_loader: - type q6_K:    1 tensors
+    llm_load_vocab: special tokens definition check successful ( 259/32000 ).
+    llm_load_print_meta: format           = GGUF V3 (latest)
+    llm_load_print_meta: arch             = llama
+    llm_load_print_meta: vocab type       = SPM
+    llm_load_print_meta: n_vocab          = 32000
+    llm_load_print_meta: n_merges         = 0
+    llm_load_print_meta: n_ctx_train      = 32768
+    llm_load_print_meta: n_embd           = 4096
+    llm_load_print_meta: n_head           = 32
+    llm_load_print_meta: n_head_kv        = 8
+    llm_load_print_meta: n_layer          = 32
+    llm_load_print_meta: n_rot            = 128
+    llm_load_print_meta: n_embd_head_k    = 128
+    llm_load_print_meta: n_embd_head_v    = 128
+    llm_load_print_meta: n_gqa            = 4
+    llm_load_print_meta: n_embd_k_gqa     = 1024
+    llm_load_print_meta: n_embd_v_gqa     = 1024
+    llm_load_print_meta: f_norm_eps       = 0.0e+00
+    llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
+    llm_load_print_meta: f_clamp_kqv      = 0.0e+00
+    llm_load_print_meta: f_max_alibi_bias = 0.0e+00
+    llm_load_print_meta: f_logit_scale    = 0.0e+00
+    llm_load_print_meta: n_ff             = 14336
+    llm_load_print_meta: n_expert         = 0
+    llm_load_print_meta: n_expert_used    = 0
+    llm_load_print_meta: causal attn      = 1
+    llm_load_print_meta: pooling type     = 0
+    llm_load_print_meta: rope type        = 0
+    llm_load_print_meta: rope scaling     = linear
+    llm_load_print_meta: freq_base_train  = 1000000.0
+    llm_load_print_meta: freq_scale_train = 1
+    llm_load_print_meta: n_yarn_orig_ctx  = 32768
+    llm_load_print_meta: rope_finetuned   = unknown
+    llm_load_print_meta: ssm_d_conv       = 0
+    llm_load_print_meta: ssm_d_inner      = 0
+    llm_load_print_meta: ssm_d_state      = 0
+    llm_load_print_meta: ssm_dt_rank      = 0
+    llm_load_print_meta: model type       = 8B
+    llm_load_print_meta: model ftype      = Q4_0
+    llm_load_print_meta: model params     = 7.24 B
+    llm_load_print_meta: model size       = 3.83 GiB (4.54 BPW) 
+    llm_load_print_meta: general.name     = mistralai_mistral-7b-instruct-v0.2
+    llm_load_print_meta: BOS token        = 1 '<s>'
+    llm_load_print_meta: EOS token        = 2 '</s>'
+    llm_load_print_meta: UNK token        = 0 '<unk>'
+    llm_load_print_meta: PAD token        = 0 '<unk>'
+    llm_load_print_meta: LF token         = 13 '<0x0A>'
+    llm_load_tensors: ggml ctx size =    0.15 MiB
+    llm_load_tensors:        CPU buffer size =  3917.87 MiB
+    ..................................................................................................
+    llama_new_context_with_model: n_ctx      = 2048
+    llama_new_context_with_model: n_batch    = 512
+    llama_new_context_with_model: n_ubatch   = 512
+    llama_new_context_with_model: flash_attn = 0
+    llama_new_context_with_model: freq_base  = 1000000.0
+    llama_new_context_with_model: freq_scale = 1
+    llama_kv_cache_init:        CPU KV buffer size =   256.00 MiB
+    llama_new_context_with_model: KV self size  =  256.00 MiB, K (f16):  128.00 MiB, V (f16):  128.00 MiB
+    llama_new_context_with_model:        CPU  output buffer size =     0.12 MiB
+    llama_new_context_with_model:        CPU compute buffer size =   164.01 MiB
+    llama_new_context_with_model: graph nodes  = 1030
+    llama_new_context_with_model: graph splits = 1
+    AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | 
+    Model metadata: {'general.name': 'mistralai_mistral-7b-instruct-v0.2', 'general.architecture': 'llama', 'llama.context_length': '32768', 'llama.rope.dimension_count': '128', 'llama.embedding_length': '4096', 'llama.block_count': '32', 'llama.feed_forward_length': '14336', 'llama.attention.head_count': '32', 'tokenizer.ggml.eos_token_id': '2', 'general.file_type': '2', 'llama.attention.head_count_kv': '8', 'llama.attention.layer_norm_rms_epsilon': '0.000010', 'llama.rope.freq_base': '1000000.000000', 'tokenizer.ggml.model': 'llama', 'general.quantization_version': '2', 'tokenizer.ggml.bos_token_id': '1', 'tokenizer.ggml.unknown_token_id': '0', 'tokenizer.ggml.padding_token_id': '0', 'tokenizer.ggml.add_bos_token': 'true', 'tokenizer.ggml.add_eos_token': 'false', 'tokenizer.chat_template': "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}"}
+    Guessed chat format: mistral-instruct
+    2024-05-07 15:50:07 INFO semantic_router.utils.logger local
+
+
+.. code:: ipython3
+
+    rl("how's the weather today?")
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='chitchat', function_call=None, similarity_score=None)
+
+
+
+.. code:: ipython3
+
+    out = rl("what's the time in New York right now?")
+    print(out)
+    get_time(**out.function_call[0])
+
+
+.. parsed-literal::
+
+    from_string grammar:
+    root ::= object 
+    object ::= [{] ws object_11 [}] ws 
+    value ::= object | array | string | number | value_6 ws 
+    array ::= [[] ws array_15 []] ws 
+    string ::= ["] string_18 ["] ws 
+    number ::= number_19 number_25 number_29 ws 
+    value_6 ::= [t] [r] [u] [e] | [f] [a] [l] [s] [e] | [n] [u] [l] [l] 
+    ws ::= ws_31 
+    object_8 ::= string [:] ws value object_10 
+    object_9 ::= [,] ws string [:] ws value 
+    object_10 ::= object_9 object_10 | 
+    object_11 ::= object_8 | 
+    array_12 ::= value array_14 
+    array_13 ::= [,] ws value 
+    array_14 ::= array_13 array_14 | 
+    array_15 ::= array_12 | 
+    string_16 ::= [^"\] | [\] string_17 
+    string_17 ::= ["\/bfnrt] | [u] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] 
+    string_18 ::= string_16 string_18 | 
+    number_19 ::= number_20 number_21 
+    number_20 ::= [-] | 
+    number_21 ::= [0-9] | [1-9] number_22 
+    number_22 ::= [0-9] number_22 | 
+    number_23 ::= [.] number_24 
+    number_24 ::= [0-9] number_24 | [0-9] 
+    number_25 ::= number_23 | 
+    number_26 ::= [eE] number_27 number_28 
+    number_27 ::= [-+] | 
+    number_28 ::= [0-9] number_28 | [0-9] 
+    number_29 ::= number_26 | 
+    ws_30 ::= [ <U+0009><U+000A>] ws 
+    ws_31 ::= ws_30 | 
+    
+    2024-05-07 15:50:08 INFO semantic_router.utils.logger Extracting function input...
+    2024-05-07 15:50:59 INFO semantic_router.utils.logger LLM output: {
+    	"timezone": "America/New_York"
+    }
+    2024-05-07 15:50:59 INFO semantic_router.utils.logger Function inputs: [{'timezone': 'America/New_York'}]
+
+
+.. parsed-literal::
+
+    name='get_time' function_call=[{'timezone': 'America/New_York'}] similarity_score=None
+
+
+
+
+.. parsed-literal::
+
+    '07:50'
+
+
+
+.. code:: ipython3
+
+    out = rl("what's the time in Rome right now?")
+    print(out)
+    get_time(**out.function_call[0])
+
+
+.. parsed-literal::
+
+    from_string grammar:
+    root ::= object 
+    object ::= [{] ws object_11 [}] ws 
+    value ::= object | array | string | number | value_6 ws 
+    array ::= [[] ws array_15 []] ws 
+    string ::= ["] string_18 ["] ws 
+    number ::= number_19 number_25 number_29 ws 
+    value_6 ::= [t] [r] [u] [e] | [f] [a] [l] [s] [e] | [n] [u] [l] [l] 
+    ws ::= ws_31 
+    object_8 ::= string [:] ws value object_10 
+    object_9 ::= [,] ws string [:] ws value 
+    object_10 ::= object_9 object_10 | 
+    object_11 ::= object_8 | 
+    array_12 ::= value array_14 
+    array_13 ::= [,] ws value 
+    array_14 ::= array_13 array_14 | 
+    array_15 ::= array_12 | 
+    string_16 ::= [^"\] | [\] string_17 
+    string_17 ::= ["\/bfnrt] | [u] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] 
+    string_18 ::= string_16 string_18 | 
+    number_19 ::= number_20 number_21 
+    number_20 ::= [-] | 
+    number_21 ::= [0-9] | [1-9] number_22 
+    number_22 ::= [0-9] number_22 | 
+    number_23 ::= [.] number_24 
+    number_24 ::= [0-9] number_24 | [0-9] 
+    number_25 ::= number_23 | 
+    number_26 ::= [eE] number_27 number_28 
+    number_27 ::= [-+] | 
+    number_28 ::= [0-9] number_28 | [0-9] 
+    number_29 ::= number_26 | 
+    ws_30 ::= [ <U+0009><U+000A>] ws 
+    ws_31 ::= ws_30 | 
+    
+    2024-05-07 15:50:59 INFO semantic_router.utils.logger Extracting function input...
+    2024-05-07 15:51:27 INFO semantic_router.utils.logger LLM output: {"timezone": "Europe/Rome"}
+    2024-05-07 15:51:27 INFO semantic_router.utils.logger Function inputs: [{'timezone': 'Europe/Rome'}]
+
+
+.. parsed-literal::
+
+    name='get_time' function_call=[{'timezone': 'Europe/Rome'}] similarity_score=None
+
+
+
+
+.. parsed-literal::
+
+    '13:51'
+
+
+
+.. code:: ipython3
+
+    out = rl("what's the time in Bangkok right now?")
+    print(out)
+    get_time(**out.function_call[0])
+
+
+.. parsed-literal::
+
+    from_string grammar:
+    root ::= object 
+    object ::= [{] ws object_11 [}] ws 
+    value ::= object | array | string | number | value_6 ws 
+    array ::= [[] ws array_15 []] ws 
+    string ::= ["] string_18 ["] ws 
+    number ::= number_19 number_25 number_29 ws 
+    value_6 ::= [t] [r] [u] [e] | [f] [a] [l] [s] [e] | [n] [u] [l] [l] 
+    ws ::= ws_31 
+    object_8 ::= string [:] ws value object_10 
+    object_9 ::= [,] ws string [:] ws value 
+    object_10 ::= object_9 object_10 | 
+    object_11 ::= object_8 | 
+    array_12 ::= value array_14 
+    array_13 ::= [,] ws value 
+    array_14 ::= array_13 array_14 | 
+    array_15 ::= array_12 | 
+    string_16 ::= [^"\] | [\] string_17 
+    string_17 ::= ["\/bfnrt] | [u] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] 
+    string_18 ::= string_16 string_18 | 
+    number_19 ::= number_20 number_21 
+    number_20 ::= [-] | 
+    number_21 ::= [0-9] | [1-9] number_22 
+    number_22 ::= [0-9] number_22 | 
+    number_23 ::= [.] number_24 
+    number_24 ::= [0-9] number_24 | [0-9] 
+    number_25 ::= number_23 | 
+    number_26 ::= [eE] number_27 number_28 
+    number_27 ::= [-+] | 
+    number_28 ::= [0-9] number_28 | [0-9] 
+    number_29 ::= number_26 | 
+    ws_30 ::= [ <U+0009><U+000A>] ws 
+    ws_31 ::= ws_30 | 
+    
+    2024-05-07 15:51:27 INFO semantic_router.utils.logger Extracting function input...
+    2024-05-07 15:51:56 INFO semantic_router.utils.logger LLM output: {"timezone": "Asia/Bangkok"}
+    2024-05-07 15:51:56 INFO semantic_router.utils.logger Function inputs: [{'timezone': 'Asia/Bangkok'}]
+
+
+.. parsed-literal::
+
+    name='get_time' function_call=[{'timezone': 'Asia/Bangkok'}] similarity_score=None
+
+
+
+
+.. parsed-literal::
+
+    '18:51'
+
+
+
+.. code:: ipython3
+
+    out = rl("what's the time in Phuket right now?")
+    print(out)
+    get_time(**out.function_call[0])
+
+
+.. parsed-literal::
+
+    from_string grammar:
+    root ::= object 
+    object ::= [{] ws object_11 [}] ws 
+    value ::= object | array | string | number | value_6 ws 
+    array ::= [[] ws array_15 []] ws 
+    string ::= ["] string_18 ["] ws 
+    number ::= number_19 number_25 number_29 ws 
+    value_6 ::= [t] [r] [u] [e] | [f] [a] [l] [s] [e] | [n] [u] [l] [l] 
+    ws ::= ws_31 
+    object_8 ::= string [:] ws value object_10 
+    object_9 ::= [,] ws string [:] ws value 
+    object_10 ::= object_9 object_10 | 
+    object_11 ::= object_8 | 
+    array_12 ::= value array_14 
+    array_13 ::= [,] ws value 
+    array_14 ::= array_13 array_14 | 
+    array_15 ::= array_12 | 
+    string_16 ::= [^"\] | [\] string_17 
+    string_17 ::= ["\/bfnrt] | [u] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] [0-9a-fA-F] 
+    string_18 ::= string_16 string_18 | 
+    number_19 ::= number_20 number_21 
+    number_20 ::= [-] | 
+    number_21 ::= [0-9] | [1-9] number_22 
+    number_22 ::= [0-9] number_22 | 
+    number_23 ::= [.] number_24 
+    number_24 ::= [0-9] number_24 | [0-9] 
+    number_25 ::= number_23 | 
+    number_26 ::= [eE] number_27 number_28 
+    number_27 ::= [-+] | 
+    number_28 ::= [0-9] number_28 | [0-9] 
+    number_29 ::= number_26 | 
+    ws_30 ::= [ <U+0009><U+000A>] ws 
+    ws_31 ::= ws_30 | 
+    
+    2024-05-07 15:51:56 INFO semantic_router.utils.logger Extracting function input...
+    2024-05-07 15:52:25 INFO semantic_router.utils.logger LLM output: {
+    	"timezone": "Asia/Bangkok"
+    }
+    2024-05-07 15:52:25 INFO semantic_router.utils.logger Function inputs: [{'timezone': 'Asia/Bangkok'}]
+
+
+.. parsed-literal::
+
+    name='get_time' function_call=[{'timezone': 'Asia/Bangkok'}] similarity_score=None
+
+
+
+
+.. parsed-literal::
+
+    '18:52'
+
+
+
+Cleanup
+-------
+
+Once done, if you’d like to delete the downloaded model you can do so
+with the following:
+
+::
+
+   ! rm ./mistral-7b-instruct-v0.2.Q4_0.gguf
diff --git a/docs/source/route_layer/route-filter.rst b/docs/source/route_layer/route-filter.rst
new file mode 100644
index 00000000..cdc04b98
--- /dev/null
+++ b/docs/source/route_layer/route-filter.rst
@@ -0,0 +1,198 @@
+Semantic Router Filter
+======================
+
+We can filter the routes that the `RouteLayer` considers when making a
+classification. This can be useful if we want to restrict the scope of
+possible routes based on some context.
+
+For example, we may have a route layer with several routes, `politics`, 
+`weather`, `chitchat`, etc. We may want to restrict the scope of the 
+classification to only consider the `chitchat` route. We can do this by
+passing a `route_filter` argument to our `RouteLayer` calls like so:
+
+.. code:: python
+
+    rl("don't you love politics?", route_filter=["chitchat"])
+
+In this case, the `RouteLayer` will only consider the `chitchat` route
+for the classification.
+
+
+Full Example
+------------
+
+|Open In Colab| |Open nbviewer|
+
+.. |Open In Colab| image:: https://colab.research.google.com/assets/colab-badge.svg
+   :target: https://colab.research.google.com/github/aurelio-labs/semantic-router/blob/main/docs/09-route-filter.ipynb
+.. |Open nbviewer| image:: https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg
+   :target: https://nbviewer.org/github/aurelio-labs/semantic-router/blob/main/docs/00-introduction.ipynb
+
+We start by installing the library:
+
+.. code:: ipython3
+
+    !pip install -qU semantic-router
+
+We start by defining a dictionary mapping routes to example phrases that
+should trigger those routes.
+
+.. code:: ipython3
+
+    from semantic_router import Route
+    
+    politics = Route(
+        name="politics",
+        utterances=[
+            "isn't politics the best thing ever",
+            "why don't you tell me about your political opinions",
+            "don't you just love the president",
+            "don't you just hate the president",
+            "they're going to destroy this country!",
+            "they will save the country!",
+        ],
+    )
+
+
+Let's define another for good measure:
+
+.. code:: ipython3
+
+    chitchat = Route(
+        name="chitchat",
+        utterances=[
+            "how's the weather today?",
+            "how are things going?",
+            "lovely weather today",
+            "the weather is horrendous",
+            "let's go to the chippy",
+        ],
+    )
+    
+    routes = [politics, chitchat]
+
+Now we initialize our embedding model:
+
+.. code:: ipython3
+
+    import os
+    from getpass import getpass
+    from semantic_router.encoders import CohereEncoder, OpenAIEncoder
+    
+    os.environ["COHERE_API_KEY"] = os.getenv("COHERE_API_KEY") or getpass(
+        "Enter Cohere API Key: "
+    )
+    # os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY") or getpass(
+    #     "Enter OpenAI API Key: "
+    # )
+    
+    encoder = CohereEncoder()
+    # encoder = OpenAIEncoder()
+
+Now we define the ``RouteLayer``. When called, the route layer will
+consume text (a query) and output the category (``Route``) it belongs to
+— to initialize a ``RouteLayer`` we need our ``encoder`` model and a
+list of ``routes``.
+
+.. code:: ipython3
+
+    from semantic_router.layer import RouteLayer
+    
+    rl = RouteLayer(encoder=encoder, routes=routes)
+
+
+.. parsed-literal::
+
+    2024-05-07 16:02:43 INFO semantic_router.utils.logger local
+
+
+Now we can test it:
+
+.. code:: ipython3
+
+    rl("don't you love politics?")
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='politics', function_call=None, similarity_score=None)
+
+
+
+.. code:: ipython3
+
+    rl("how's the weather today?")
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='chitchat', function_call=None, similarity_score=None)
+
+
+
+Both are classified accurately, what if we send a query that is
+unrelated to our existing ``Route`` objects?
+
+.. code:: ipython3
+
+    rl("I'm interested in learning about llama 2")
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name=None, function_call=None, similarity_score=None)
+
+
+
+In this case, we return ``None`` because no matches were identified.
+
+Demonstrating the Filter Feature
+================================
+
+Now, le'’s demonstrate the filter feature. We can specify a subset of
+routes to consider when making a classification. This can be useful if
+we want to restrict the scope of possible routes based on some context.
+
+For example, let's say we only want to consider the “chitchat” route for
+a particular query:
+
+.. code:: ipython3
+
+    rl("don't you love politics?", route_filter=["chitchat"])
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='chitchat', function_call=None, similarity_score=None)
+
+
+
+Even though the query might be more related to the “politics” route, it
+will be classified as “chitchat” because we’ve restricted the routes to
+consider.
+
+Similarly, we can restrict it to the “politics” route:
+
+.. code:: ipython3
+
+    rl("how's the weather today?", route_filter=["politics"])
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name=None, function_call=None, similarity_score=None)
+
+
+
+In this case, it will return None because the query doesn’t match the
+“politics” route well enough to pass the threshold.
diff --git a/docs/source/route_layer/route_filter.rst b/docs/source/route_layer/route_filter.rst
deleted file mode 100644
index e4e43c2b..00000000
--- a/docs/source/route_layer/route_filter.rst
+++ /dev/null
@@ -1,5 +0,0 @@
-Calling the Route Layer
-=======================
-
-You can use the `route_filter` parameter with a list of route names to filter
-the routes that will be considered.
\ No newline at end of file
diff --git a/docs/source/route_layer/save-load-from-file.rst b/docs/source/route_layer/save-load-from-file.rst
new file mode 100644
index 00000000..6cce117f
--- /dev/null
+++ b/docs/source/route_layer/save-load-from-file.rst
@@ -0,0 +1,237 @@
+Route Layers from File
+======================
+
+Route layers can be saved to and loaded from files. This can be useful if
+we want to save a route layer to a file for later use, or if we want to
+load a route layer from a file.
+
+We can save and load route layers to/from YAML or JSON files. For JSON we
+do:
+
+.. code:: python
+
+    # save to JSON
+    rl.to_json("layer.json")
+    # load from JSON
+    new_rl = RouteLayer.from_json("layer.json")
+
+For YAML we do:
+
+.. code:: python
+
+    # save to YAML
+    rl.to_yaml("layer.yaml")
+    # load from YAML
+    new_rl = RouteLayer.from_yaml("layer.yaml")
+
+The saved files contain all the information needed to initialize new
+route layers. If we are using a remote index, we can use the
+`sync features`_ to keep the route layer in sync with the index.
+
+.. _sync features: sync.rst
+
+Full Example
+---------------
+
+|Open In Colab| |Open nbviewer|
+
+.. |Open In Colab| image:: https://colab.research.google.com/assets/colab-badge.svg
+   :target: https://colab.research.google.com/github/aurelio-labs/semantic-router/blob/main/docs/01-save-load-from-file.ipynb
+.. |Open nbviewer| image:: https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg
+   :target: https://nbviewer.org/github/aurelio-labs/semantic-router/blob/main/docs/01-save-load-from-file.ipynb
+
+Here we will show how to save routers to YAML or JSON files, and how to
+load a route layer from file.
+
+We start by installing the library:
+
+.. code:: ipython3
+
+    !pip install -qU semantic-router
+
+Define Route
+------------
+
+First let's create a list of routes:
+
+.. code:: ipython3
+
+    from semantic_router import Route
+    
+    politics = Route(
+        name="politics",
+        utterances=[
+            "isn't politics the best thing ever",
+            "why don't you tell me about your political opinions",
+            "don't you just love the president" "don't you just hate the president",
+            "they're going to destroy this country!",
+            "they will save the country!",
+        ],
+    )
+    chitchat = Route(
+        name="chitchat",
+        utterances=[
+            "how's the weather today?",
+            "how are things going?",
+            "lovely weather today",
+            "the weather is horrendous",
+            "let's go to the chippy",
+        ],
+    )
+    
+    routes = [politics, chitchat]
+
+
+We define a route layer using these routes and using the Cohere encoder.
+
+.. code:: ipython3
+
+    import os
+    from getpass import getpass
+    from semantic_router import RouteLayer
+    from semantic_router.encoders import CohereEncoder
+    
+    # dashboard.cohere.ai
+    os.environ["COHERE_API_KEY"] = os.getenv("COHERE_API_KEY") or getpass(
+        "Enter Cohere API Key: "
+    )
+    
+    encoder = CohereEncoder()
+    
+    rl = RouteLayer(encoder=encoder, routes=routes)
+
+
+.. parsed-literal::
+
+    2024-05-07 15:03:35 INFO semantic_router.utils.logger local
+
+
+Test Route
+----------
+
+.. code:: ipython3
+
+    rl("isn't politics the best thing ever")
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='politics', function_call=None, similarity_score=None)
+
+
+
+.. code:: ipython3
+
+    rl("how's the weather today?")
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='chitchat', function_call=None, similarity_score=None)
+
+
+
+Save To JSON
+------------
+
+To save our route layer we call the ``to_json`` method:
+
+.. code:: ipython3
+
+    rl.to_json("layer.json")
+
+
+.. parsed-literal::
+
+    2024-05-07 15:03:37 INFO semantic_router.utils.logger Saving route config to layer.json
+
+
+Loading from JSON
+-----------------
+
+We can view the router file we just saved to see what information is
+stored.
+
+.. code:: ipython3
+
+    import json
+    
+    with open("layer.json", "r") as f:
+        layer_json = json.load(f)
+    
+    print(layer_json)
+
+
+.. parsed-literal::
+
+    {'encoder_type': 'cohere', 'encoder_name': 'embed-english-v3.0', 'routes': [{'name': 'politics', 'utterances': ["isn't politics the best thing ever", "why don't you tell me about your political opinions", "don't you just love the presidentdon't you just hate the president", "they're going to destroy this country!", 'they will save the country!'], 'description': None, 'function_schemas': None, 'llm': None, 'score_threshold': 0.3}, {'name': 'chitchat', 'utterances': ["how's the weather today?", 'how are things going?', 'lovely weather today', 'the weather is horrendous', "let's go to the chippy"], 'description': None, 'function_schemas': None, 'llm': None, 'score_threshold': 0.3}]}
+
+
+It tells us our encoder type, encoder name, and routes. This is
+everything we need to initialize a new router. To do so, we use the
+``from_json`` method.
+
+.. code:: ipython3
+
+    rl = RouteLayer.from_json("layer.json")
+
+
+.. parsed-literal::
+
+    2024-05-07 15:03:37 INFO semantic_router.utils.logger Loading route config from layer.json
+    2024-05-07 15:03:37 INFO semantic_router.utils.logger local
+
+
+We can confirm that our layer has been initialized with the expected
+attributes by viewing the ``RouteLayer`` object:
+
+.. code:: ipython3
+
+    print(
+        f"""{rl.encoder.type=}
+    {rl.encoder.name=}
+    {rl.routes=}"""
+    )
+
+
+.. parsed-literal::
+
+    rl.encoder.type='cohere'
+    rl.encoder.name='embed-english-v3.0'
+    rl.routes=[Route(name='politics', utterances=["isn't politics the best thing ever", "why don't you tell me about your political opinions", "don't you just love the presidentdon't you just hate the president", "they're going to destroy this country!", 'they will save the country!'], description=None, function_schemas=None, llm=None, score_threshold=0.3), Route(name='chitchat', utterances=["how's the weather today?", 'how are things going?', 'lovely weather today', 'the weather is horrendous', "let's go to the chippy"], description=None, function_schemas=None, llm=None, score_threshold=0.3)]
+
+
+--------------
+
+Test Route Again
+----------------
+
+.. code:: ipython3
+
+    rl("isn't politics the best thing ever")
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='politics', function_call=None, similarity_score=None)
+
+
+
+.. code:: ipython3
+
+    rl("how's the weather today?")
+
+
+
+
+.. parsed-literal::
+
+    RouteChoice(name='chitchat', function_call=None, similarity_score=None)
+
+
diff --git a/docs/source/route_layer/threshold-optimization.rst b/docs/source/route_layer/threshold-optimization.rst
new file mode 100644
index 00000000..850c847a
--- /dev/null
+++ b/docs/source/route_layer/threshold-optimization.rst
@@ -0,0 +1,371 @@
+Route Threshold Optimization
+============================
+
+Route score thresholds are what defines whether a route should be
+chosen. If the score we identify for any given route is higher than the
+``Route.score_threshold`` it passes, otherwise it does not and *either*
+another route is chosen, or we return *no* route.
+
+Given that this one ``score_threshold`` parameter can define the choice
+of a route, it's important to get it right — but it's incredibly
+inefficient to do so manually. Instead, we can use the ``fit`` and
+``evaluate`` methods of our ``RouteLayer``. All we must do is pass a
+smaller number of *(utterance, target route)* examples to our methods,
+and with ``fit`` we will often see dramatically improved performance
+within seconds.
+
+
+Full Example
+------------
+
+|Open In Colab| |Open nbviewer|
+
+.. |Open In Colab| image:: https://colab.research.google.com/assets/colab-badge.svg
+   :target: https://colab.research.google.com/github/aurelio-labs/semantic-router/blob/main/docs/06-threshold-optimization.ipynb
+.. |Open nbviewer| image:: https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg
+   :target: https://nbviewer.org/github/aurelio-labs/semantic-router/blob/main/docs/06-threshold-optimization
+
+
+.. code:: ipython3
+
+    !pip install -qU "semantic-router[local]"
+
+Define RouteLayer
+-----------------
+
+As usual we will define our ``RouteLayer``. The ``RouteLayer`` requires
+just ``routes`` and an ``encoder``. If using dynamic routes you must
+also define an ``llm`` (or use the OpenAI default).
+
+We will start by defining four routes; *politics*, *chitchat*,
+*mathematics*, and *biology*.
+
+.. code:: ipython3
+
+    from semantic_router import Route
+    
+    # we could use this as a guide for our chatbot to avoid political conversations
+    politics = Route(
+        name="politics",
+        utterances=[
+            "isn't politics the best thing ever",
+            "why don't you tell me about your political opinions",
+            "don't you just love the president" "don't you just hate the president",
+            "they're going to destroy this country!",
+            "they will save the country!",
+        ],
+    )
+    
+    # this could be used as an indicator to our chatbot to switch to a more
+    # conversational prompt
+    chitchat = Route(
+        name="chitchat",
+        utterances=[
+            "Did you watch the game last night?",
+            "what's your favorite type of music?",
+            "Have you read any good books lately?",
+            "nice weather we're having",
+            "Do you have any plans for the weekend?",
+        ],
+    )
+    
+    # we can use this to switch to an agent with more math tools, prompting, and LLMs
+    mathematics = Route(
+        name="mathematics",
+        utterances=[
+            "can you explain the concept of a derivative?",
+            "What is the formula for the area of a triangle?",
+            "how do you solve a system of linear equations?",
+            "What is the concept of a prime number?",
+            "Can you explain the Pythagorean theorem?",
+        ],
+    )
+    
+    # we can use this to switch to an agent with more biology knowledge
+    biology = Route(
+        name="biology",
+        utterances=[
+            "what is the process of osmosis?",
+            "can you explain the structure of a cell?",
+            "What is the role of RNA?",
+            "What is genetic mutation?",
+            "Can you explain the process of photosynthesis?",
+        ],
+    )
+    
+    # we place all of our decisions together into single list
+    routes = [politics, chitchat, mathematics, biology]
+
+
+.. parsed-literal::
+
+    c:\Users\Siraj\Documents\Personal\Work\Aurelio\Virtual Environments\semantic_router_3\Lib\site-packages\tqdm\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
+      from .autonotebook import tqdm as notebook_tqdm
+
+
+For our encoder we will use the local ``HuggingFaceEncoder``. Other
+popular encoders include ``CohereEncoder``, ``FastEmbedEncoder``,
+``OpenAIEncoder``, and ``AzureOpenAIEncoder``.
+
+.. code:: ipython3
+
+    from semantic_router.encoders import HuggingFaceEncoder
+    
+    encoder = HuggingFaceEncoder()
+
+Now we initialize our ``RouteLayer``.
+
+.. code:: ipython3
+
+    from semantic_router.layer import RouteLayer
+    
+    rl = RouteLayer(encoder=encoder, routes=routes)
+
+
+.. parsed-literal::
+
+    2024-05-07 15:53:24 INFO semantic_router.utils.logger local
+
+
+By default, we should get reasonable performance:
+
+.. code:: ipython3
+
+    for utterance in [
+        "don't you love politics?",
+        "how's the weather today?",
+        "What's DNA?",
+        "I'm interested in learning about llama 2",
+    ]:
+        print(f"{utterance} -> {rl(utterance).name}")
+
+
+.. parsed-literal::
+
+    don't you love politics? -> politics
+    how's the weather today? -> chitchat
+    What's DNA? -> biology
+    I'm interested in learning about llama 2 -> None
+
+
+We can evaluate the performance of our route layer using the
+``evaluate`` method. All we need is to pass a list of utterances and
+target route labels:
+
+.. code:: ipython3
+
+    test_data = [
+        ("don't you love politics?", "politics"),
+        ("how's the weather today?", "chitchat"),
+        ("What's DNA?", "biology"),
+        ("I'm interested in learning about llama 2", None),
+    ]
+    
+    # unpack the test data
+    X, y = zip(*test_data)
+    
+    # evaluate using the default thresholds
+    accuracy = rl.evaluate(X=X, y=y)
+    print(f"Accuracy: {accuracy*100:.2f}%")
+
+
+.. parsed-literal::
+
+    Generating embeddings: 100%|██████████| 1/1 [00:00<00:00, 76.91it/s]
+
+.. parsed-literal::
+
+    Accuracy: 100.00%
+
+
+.. parsed-literal::
+
+    
+
+
+On this small subset we get perfect accuracy — but what if we try we a
+larger, more robust dataset?
+
+*Hint: try using GPT-4 or another LLM to generate some examples for your
+own use-cases. The more accurate examples you provide, the better you
+can expect the routes to perform on your actual use-case.*
+
+.. code:: ipython3
+
+    test_data = [
+        # politics
+        ("What's your opinion on the current government?", "politics"),
+        ("Who do you think will win the next election?", "politics"),
+        ("What are your thoughts on the new policy?", "politics"),
+        ("How do you feel about the political situation?", "politics"),
+        ("Do you agree with the president's actions?", "politics"),
+        ("What's your stance on the political debate?", "politics"),
+        ("How do you see the future of our country?", "politics"),
+        ("What do you think about the opposition party?", "politics"),
+        ("Do you believe the government is doing enough?", "politics"),
+        ("What's your opinion on the political scandal?", "politics"),
+        ("Do you think the new law will make a difference?", "politics"),
+        ("What are your thoughts on the political reform?", "politics"),
+        ("Do you agree with the government's foreign policy?", "politics"),
+        # chitchat
+        ("What's the weather like?", "chitchat"),
+        ("It's a beautiful day today.", "chitchat"),
+        ("How's your day going?", "chitchat"),
+        ("It's raining cats and dogs.", "chitchat"),
+        ("Let's grab a coffee.", "chitchat"),
+        ("What's up?", "chitchat"),
+        ("It's a bit chilly today.", "chitchat"),
+        ("How's it going?", "chitchat"),
+        ("Nice weather we're having.", "chitchat"),
+        ("It's a bit windy today.", "chitchat"),
+        ("Let's go for a walk.", "chitchat"),
+        ("How's your week been?", "chitchat"),
+        ("It's quite sunny today.", "chitchat"),
+        ("How are you feeling?", "chitchat"),
+        ("It's a bit cloudy today.", "chitchat"),
+        # mathematics
+        ("What is the Pythagorean theorem?", "mathematics"),
+        ("Can you solve this quadratic equation?", "mathematics"),
+        ("What is the derivative of x squared?", "mathematics"),
+        ("Explain the concept of integration.", "mathematics"),
+        ("What is the area of a circle?", "mathematics"),
+        ("How do you calculate the volume of a sphere?", "mathematics"),
+        ("What is the difference between a vector and a scalar?", "mathematics"),
+        ("Explain the concept of a matrix.", "mathematics"),
+        ("What is the Fibonacci sequence?", "mathematics"),
+        ("How do you calculate permutations?", "mathematics"),
+        ("What is the concept of probability?", "mathematics"),
+        ("Explain the binomial theorem.", "mathematics"),
+        ("What is the difference between discrete and continuous data?", "mathematics"),
+        ("What is a complex number?", "mathematics"),
+        ("Explain the concept of limits.", "mathematics"),
+        # biology
+        ("What is photosynthesis?", "biology"),
+        ("Explain the process of cell division.", "biology"),
+        ("What is the function of mitochondria?", "biology"),
+        ("What is DNA?", "biology"),
+        ("What is the difference between prokaryotic and eukaryotic cells?", "biology"),
+        ("What is an ecosystem?", "biology"),
+        ("Explain the theory of evolution.", "biology"),
+        ("What is a species?", "biology"),
+        ("What is the role of enzymes?", "biology"),
+        ("What is the circulatory system?", "biology"),
+        ("Explain the process of respiration.", "biology"),
+        ("What is a gene?", "biology"),
+        ("What is the function of the nervous system?", "biology"),
+        ("What is homeostasis?", "biology"),
+        ("What is the difference between a virus and a bacteria?", "biology"),
+        ("What is the role of the immune system?", "biology"),
+        # add some None routes to prevent excessively small thresholds
+        ("What is the capital of France?", None),
+        ("how many people live in the US?", None),
+        ("when is the best time to visit Bali?", None),
+        ("how do I learn a language", None),
+        ("tell me an interesting fact", None),
+        ("what is the best programming language?", None),
+        ("I'm interested in learning about llama 2", None),
+    ]
+
+.. code:: ipython3
+
+    # unpack the test data
+    X, y = zip(*test_data)
+    
+    # evaluate using the default thresholds
+    accuracy = rl.evaluate(X=X, y=y)
+    print(f"Accuracy: {accuracy*100:.2f}%")
+
+
+.. parsed-literal::
+
+    Generating embeddings: 100%|██████████| 1/1 [00:00<00:00,  9.23it/s]
+
+.. parsed-literal::
+
+    Accuracy: 34.85%
+
+
+.. parsed-literal::
+
+    
+
+
+Ouch, that’s not so good! Fortunately, we can easily improve our
+performance here.
+
+Route Layer Optimization
+------------------------
+
+Our optimization works by finding the best route thresholds for each
+``Route`` in our ``RouteLayer``. We can see the current, default
+thresholds by calling the ``get_thresholds`` method:
+
+.. code:: ipython3
+
+    route_thresholds = rl.get_thresholds()
+    print("Default route thresholds:", route_thresholds)
+
+
+.. parsed-literal::
+
+    Default route thresholds: {'politics': 0.5, 'chitchat': 0.5, 'mathematics': 0.5, 'biology': 0.5}
+
+
+These are all preset route threshold values. Fortunately, it’s very easy
+to optimize these — we simply call the ``fit`` method and provide our
+training utterances ``X``, and target route labels ``y``:
+
+.. code:: ipython3
+
+    # Call the fit method
+    rl.fit(X=X, y=y)
+
+
+.. parsed-literal::
+
+    Generating embeddings: 100%|██████████| 1/1 [00:00<00:00,  9.21it/s]
+    Training: 100%|██████████| 500/500 [00:01<00:00, 419.45it/s, acc=0.89]
+
+
+Let’s see what our new thresholds look like:
+
+.. code:: ipython3
+
+    route_thresholds = rl.get_thresholds()
+    print("Updated route thresholds:", route_thresholds)
+
+
+.. parsed-literal::
+
+    Updated route thresholds: {'politics': 0.05050505050505051, 'chitchat': 0.32323232323232326, 'mathematics': 0.18181818181818182, 'biology': 0.21212121212121213}
+
+
+These are vastly different thresholds to what we were seeing before —
+it’s worth noting that *optimal* values for different encoders can vary
+greatly. For example, OpenAI’s Ada 002 model, when used with our
+encoders will tend to output much larger numbers in the ``0.5`` to
+``0.8`` range.
+
+After training we have a final performance of:
+
+.. code:: ipython3
+
+    accuracy = rl.evaluate(X=X, y=y)
+    print(f"Accuracy: {accuracy*100:.2f}%")
+
+
+.. parsed-literal::
+
+    Generating embeddings: 100%|██████████| 1/1 [00:00<00:00,  8.89it/s]
+
+
+.. parsed-literal::
+
+    Accuracy: 89.39%
+
+
+That is *much* better. If we wanted to optimize this further we can
+focus on adding more utterances to our existing routes, analyzing
+*where* exactly our failures are, and modifying our routes around those.
+This extended optimzation process is much more manual, but with it we
+can continue optimizing routes to get even better performance.

From d4d359096c219362a21f9173a89018754a7b0b79 Mon Sep 17 00:00:00 2001
From: James Briggs <james.briggs@hotmail.com>
Date: Sun, 1 Sep 2024 17:37:31 +0200
Subject: [PATCH 4/7] feat: delete unmatched docs

---
 .github/workflows/docs.yml                        | 15 +++++++++------
 docs/source/route_layer/local-execution.rst       |  2 +-
 docs/source/route_layer/route-filter.rst          |  4 ++--
 .../source/route_layer/threshold-optimization.rst | 12 +-----------
 4 files changed, 13 insertions(+), 20 deletions(-)

diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index a32d5ed6..f9474a9f 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -48,9 +48,12 @@ jobs:
         with:
           credentials_json: ${{ secrets.GOOGLE_CREDENTIALS }}
       - name: Upload Docs
-        id: upload-directory
-        uses: google-github-actions/upload-cloud-storage@v2
-        with:
-          path: docs/build/html
-          destination: docs-bucket-production/semantic-router
-          parent: false
\ No newline at end of file
+        run: |
+          gcloud storage rsync docs/build/html gs://docs-bucket-production/semantic-router --recursive --delete-unmatched-destination
+      # - name: Upload Docs
+      #   id: upload-directory
+      #   uses: google-github-actions/upload-cloud-storage@v2
+      #   with:
+      #     path: docs/build/html
+      #     destination: docs-bucket-production/semantic-router
+      #     parent: false
\ No newline at end of file
diff --git a/docs/source/route_layer/local-execution.rst b/docs/source/route_layer/local-execution.rst
index d1e2364e..6e7696ef 100644
--- a/docs/source/route_layer/local-execution.rst
+++ b/docs/source/route_layer/local-execution.rst
@@ -235,7 +235,7 @@ calling
 
 
 Encoders
-========
+--------
 
 You can use alternative Encoders, however, in this example we want to
 showcase a fully-local Semantic Router execution, so we are going to use
diff --git a/docs/source/route_layer/route-filter.rst b/docs/source/route_layer/route-filter.rst
index cdc04b98..0bf1257a 100644
--- a/docs/source/route_layer/route-filter.rst
+++ b/docs/source/route_layer/route-filter.rst
@@ -153,9 +153,9 @@ unrelated to our existing ``Route`` objects?
 In this case, we return ``None`` because no matches were identified.
 
 Demonstrating the Filter Feature
-================================
+--------------------------------
 
-Now, le'’s demonstrate the filter feature. We can specify a subset of
+Now, let's demonstrate the filter feature. We can specify a subset of
 routes to consider when making a classification. This can be useful if
 we want to restrict the scope of possible routes based on some context.
 
diff --git a/docs/source/route_layer/threshold-optimization.rst b/docs/source/route_layer/threshold-optimization.rst
index 850c847a..c035dd87 100644
--- a/docs/source/route_layer/threshold-optimization.rst
+++ b/docs/source/route_layer/threshold-optimization.rst
@@ -178,11 +178,6 @@ target route labels:
     Accuracy: 100.00%
 
 
-.. parsed-literal::
-
-    
-
-
 On this small subset we get perfect accuracy — but what if we try we a
 larger, more robust dataset?
 
@@ -285,12 +280,7 @@ can expect the routes to perform on your actual use-case.*
     Accuracy: 34.85%
 
 
-.. parsed-literal::
-
-    
-
-
-Ouch, that’s not so good! Fortunately, we can easily improve our
+Ouch, that's not so good! Fortunately, we can easily improve our
 performance here.
 
 Route Layer Optimization

From 97a9620ae07a6faf6cd41c2ca565df84b27fcfb4 Mon Sep 17 00:00:00 2001
From: James Briggs <james.briggs@hotmail.com>
Date: Sun, 1 Sep 2024 17:54:29 +0200
Subject: [PATCH 5/7] fix: formatting issues

---
 docs/source/route_layer/dynamic-routes.rst      | 5 ++---
 docs/source/route_layer/local-execution.rst     | 4 ++--
 docs/source/route_layer/save-load-from-file.rst | 6 +++---
 docs/source/route_layer/sync.rst                | 2 ++
 4 files changed, 9 insertions(+), 8 deletions(-)

diff --git a/docs/source/route_layer/dynamic-routes.rst b/docs/source/route_layer/dynamic-routes.rst
index 9856bbc2..7b144d03 100644
--- a/docs/source/route_layer/dynamic-routes.rst
+++ b/docs/source/route_layer/dynamic-routes.rst
@@ -15,7 +15,7 @@ associated with that route.
 
 For example we could provide a dynamic route with associated utterances:
 
-::
+.. code:: python
 
    "what is x to the power of y?"
    "what is 9 to the power of 4?"
@@ -26,7 +26,7 @@ For example we could provide a dynamic route with associated utterances:
 and we could also provide the route with a schema outlining key features
 of the function:
 
-::
+.. code:: python
 
    def power(base: float, exponent: float) -> float:
        """Raise base to the power of exponent.
@@ -79,7 +79,6 @@ it correctly.
 
 
 
-
 .. parsed-literal::
 
     '17:57'
diff --git a/docs/source/route_layer/local-execution.rst b/docs/source/route_layer/local-execution.rst
index 6e7696ef..b20aade8 100644
--- a/docs/source/route_layer/local-execution.rst
+++ b/docs/source/route_layer/local-execution.rst
@@ -147,7 +147,7 @@ hardware
 
 
 Initializing Dynamic Routes
-===========================
+---------------------------
 
 Similar to the ``02-dynamic-routes.ipynb`` notebook, we will be
 initializing some dynamic routes that make use of LLMs for function
@@ -249,7 +249,7 @@ a ``HuggingFaceEncoder`` with ``sentence-transformers/all-MiniLM-L6-v2``
     encoder = HuggingFaceEncoder()
 
 ``llama.cpp`` LLM
-=================
+-----------------
 
 From here, we can go ahead and instantiate our ``llama-cpp-python``
 ``llama_cpp.Llama`` LLM, and then pass it to the
diff --git a/docs/source/route_layer/save-load-from-file.rst b/docs/source/route_layer/save-load-from-file.rst
index 6cce117f..2f13247c 100644
--- a/docs/source/route_layer/save-load-from-file.rst
+++ b/docs/source/route_layer/save-load-from-file.rst
@@ -28,7 +28,7 @@ The saved files contain all the information needed to initialize new
 route layers. If we are using a remote index, we can use the
 `sync features`_ to keep the route layer in sync with the index.
 
-.. _sync features: sync.rst
+.. _sync features: sync.html
 
 Full Example
 ---------------
@@ -45,7 +45,7 @@ load a route layer from file.
 
 We start by installing the library:
 
-.. code:: ipython3
+.. code:: none
 
     !pip install -qU semantic-router
 
@@ -54,7 +54,7 @@ Define Route
 
 First let's create a list of routes:
 
-.. code:: ipython3
+.. code:: python
 
     from semantic_router import Route
     
diff --git a/docs/source/route_layer/sync.rst b/docs/source/route_layer/sync.rst
index ee471dc2..03204917 100644
--- a/docs/source/route_layer/sync.rst
+++ b/docs/source/route_layer/sync.rst
@@ -66,3 +66,5 @@ You can try this yourself by running the following:
     )
 
     rl = RouteLayer(encoder=encoder, routes=routes, index=pc_index)
+
+When initializing the `PineconeIndex` object, we can specify the `sync` parameter.
\ No newline at end of file

From 950b56fa2c5c18ecf3eda354350239f65a7c9c26 Mon Sep 17 00:00:00 2001
From: James Briggs <james.briggs@hotmail.com>
Date: Sun, 1 Sep 2024 18:18:45 +0200
Subject: [PATCH 6/7] fix: arg for updating docs

---
 .github/workflows/docs.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index f9474a9f..4dd9a21b 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -49,7 +49,7 @@ jobs:
           credentials_json: ${{ secrets.GOOGLE_CREDENTIALS }}
       - name: Upload Docs
         run: |
-          gcloud storage rsync docs/build/html gs://docs-bucket-production/semantic-router --recursive --delete-unmatched-destination
+          gcloud storage rsync docs/build/html gs://docs-bucket-production/semantic-router --recursive --delete-unmatched-destination-objects
       # - name: Upload Docs
       #   id: upload-directory
       #   uses: google-github-actions/upload-cloud-storage@v2

From 2a5cd6de0dd16ef8fa402f3f54c16b709e9e6395 Mon Sep 17 00:00:00 2001
From: James Briggs <james.briggs@hotmail.com>
Date: Sun, 1 Sep 2024 18:31:33 +0200
Subject: [PATCH 7/7] fix: condition for docs workflow

---
 .github/workflows/docs.yml | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index 4dd9a21b..5b9f2903 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -1,10 +1,9 @@
 name: Release Docs
 
 on:
-  pull_request:
-  # push:
-  #   tags:
-  #     - '*'
+  push:
+    branches:
+      - main
 
 jobs:
   build-docs: