Use conda for faiss

guestrin-lab · Nov 9, 2024 · 96d7810 · 96d7810
1 parent c6c73ef
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Showing 8 changed files with 13 additions and 6 deletions.
diff --git a/.readthedocs.yaml b/.readthedocs.yaml
@@ -15,6 +15,9 @@ sphinx:
 formats:
    - pdf
 
+conda:
+   file: environment.yml
+
 # Optionally declare the Python requirements required to build your docs
 python:
    install:

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
@@ -4,7 +4,7 @@
 
 To set up for development, create a conda environment, install lotus, and install additional dev dependencies.
 ```
-conda create -n lotus python=3.10 -y
+conda env create -f environment.yml
 conda activate lotus
 git clone [email protected]:stanford-futuredata/lotus.git
 pip install -e .

diff --git a/README.md b/README.md
@@ -35,7 +35,7 @@ LOTUS offers a number of semantic operators in a Pandas-like API, some of which
 
 # Installation
 ```
-conda create -n lotus python=3.10 -y
+conda env create -f environment.yml
 conda activate lotus
 pip install lotus-ai
 ```

diff --git a/docs/installation.rst b/docs/installation.rst
@@ -16,6 +16,6 @@ You can install Lotus using pip:
 
 .. code-block:: console
 
-    $ conda create -n lotus python=3.10 -y
+    $ conda env create -f environment.yml
     $ conda activate lotus
     $ pip install lotus-ai
diff --git a/docs/requirements-docs.txt b/docs/requirements-docs.txt
@@ -2,7 +2,6 @@ sphinx==7.3.7
 sphinx-rtd-theme==2.0.0
 
 backoff==2.2.1
-faiss-cpu==1.8.0.post1
 litellm==1.51.0
 numpy==1.26.4
 pandas==2.2.2

diff --git a/environment.yml b/environment.yml
@@ -0,0 +1,7 @@
+name: lotus
+channels:
+  - conda-forge
+  - pytorch
+dependencies:
+  - python=3.10
+  - faiss-cpu=1.8.0
diff --git a/pyproject.toml b/pyproject.toml
@@ -23,7 +23,6 @@ classifiers = [
 
 dependencies = [
     "backoff>=2.2.1,<3.0.0",
-    "faiss-cpu>=1.8.0.post1,<2.0.0",
     "litellm>=1.51.0,<2.0.0",
     "numpy>=1.25.0,<2.0.0",
     "pandas>=2.0.0,<3.0.0",

diff --git a/requirements.txt b/requirements.txt
@@ -1,5 +1,4 @@
 backoff==2.2.1
-faiss-cpu==1.8.0.post1
 litellm==1.51.0
 numpy==1.26.4
 pandas==2.2.2