Remove docs and installation of graphviz

Author: oskarhane

.github/workflows/pr-e2e-tests.yaml

@@ -49,8 +49,6 @@ jobs:
           - 6333:6333
 
     steps:
-      - name: Install graphviz package
-        run: sudo apt install graphviz graphviz-dev
       - name: Check out repository code
         uses: actions/checkout@v4
       - name: Docker Prune

.github/workflows/pr.yaml

@@ -8,8 +8,6 @@ jobs:
       matrix:
         python-version: [ '3.9', '3.10', '3.11', '3.12' ]
     steps:
-      - name: Install graphviz package
-        run: sudo apt install graphviz graphviz-dev
       - name: Check out repository code
         uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }}

.github/workflows/scheduled-e2e-tests.yaml

@@ -57,8 +57,6 @@ jobs:
           - 6333:6333
 
     steps:
-      - name: Install graphviz package
-        run: sudo apt install graphviz graphviz-dev
       - name: Check out repository code
         uses: actions/checkout@v4
       - name: Docker Prune

README.md

@@ -59,7 +59,6 @@ the extra dependencies described below:
     - **pinecone**: store vectors in Pinecone
     - **qdrant**: store vectors in Qdrant
 - **experimental**: experimental features mainly related to the Knowledge Graph creation pipelines.
-    - Warning: this dependency group requires `pygraphviz`. See below for installation instructions.
 
 
 Install package with optional dependencies with (for instance):
@@ -68,11 +67,6 @@ Install package with optional dependencies with (for instance):
 pip install "neo4j-graphrag[openai]"
 ```
 
-#### pygraphviz
-
-`pygraphviz` is used for visualizing pipelines.
-Installation instructions can be found [here](https://pygraphviz.github.io/documentation/stable/install.html).
-
 ## 💻 Example Usage
 
 The scripts below demonstrate how to get started with the package and make use of its key features.

docs/source/index.rst

@@ -98,7 +98,6 @@ List of extra dependencies:
     - **pinecone**: store vectors in Pinecone
     - **qdrant**: store vectors in Qdrant
 - **experimental**: experimental features mainly from the Knowledge Graph creation pipelines.
-    - Warning: this requires `pygraphviz`. Installation instructions can be found `here <https://pygraphviz.github.io/documentation/stable/install.html>`_.
 - nlp:
    - **spaCy**: load spaCy trained models for nlp pipelines, used by `SpaCySemanticMatchResolver` component from the Knowledge Graph creation pipelines.
 - fuzzy-matching: