Resolves dependency issues from latest streamlit

Resolves dependency issues introduced by the latest streamlit.
Not sure how interested you are in the following, but I also pinned the dependencies in `requirements.txt` and added `unpinned_requirements.txt` containing the unpinned dependencies. Pinned dependencies can now be resolved with `make update-requirements` and build a new virtualenv with `make virtualenv`.

Makefile

@@ -0,0 +1,35 @@
+#################################################################################
+# GLOBALS                                                                       #
+#################################################################################
+
+PYTHON_VERSION = python3.10
+VIRTUALENV := .venv
+
+#################################################################################
+# COMMANDS                                                                      #
+#################################################################################
+
+# Set the default location for the virtualenv to be stored
+# Create the virtualenv by installing the requirements and test requirements
+
+
+.PHONY: virtualenv
+virtualenv: requirements.txt
+	@if [ -d $(VIRTUALENV) ]; then rm -rf $(VIRTUALENV); fi
+	@mkdir -p $(VIRTUALENV)
+	$(PYTHON_VERSION) -m venv $(VIRTUALENV)
+	$(VIRTUALENV)/bin/pip install --upgrade pip
+	$(VIRTUALENV)/bin/pip install --upgrade -r requirements.txt
+	touch $@
+
+.PHONY: update-requirements-txt
+update-requirements-txt: unpinned_requirements.txt
+update-requirements-txt: VIRTUALENV := /tmp/update-requirements-virtualenv
+update-requirements-txt:
+	@if [ -d $(VIRTUALENV) ]; then rm -rf $(VIRTUALENV); fi
+	@mkdir -p $(VIRTUALENV)
+	virtualenv --python $(PYTHON_VERSION) $(VIRTUALENV)
+	$(VIRTUALENV)/bin/pip install --upgrade pip
+	$(VIRTUALENV)/bin/pip install --upgrade -r unpinned_requirements.txt
+	echo "# Created by 'make update-requirements-txt'. DO NOT EDIT!" > requirements.txt
+	$(VIRTUALENV)/bin/pip freeze | grep -v pkg_resources==0.0.0 >> requirements.txt

app.py

@@ -1,12 +1,14 @@
+import os
+
+import jax
+import jax.numpy as jnp
 import nmslib
 import numpy as np
 import streamlit as st
+from PIL import Image
 from transformers import AutoTokenizer, CLIPProcessor
+
 from model import FlaxHybridCLIP
-from PIL import Image
-import jax.numpy as jnp
-import os
-import jax
 
 # st.header('Under construction')
 
@@ -14,17 +16,17 @@ import jax
 st.sidebar.title("CLIP React Demo")
 
 st.sidebar.write("[Model Card](https://huggingface.co/flax-community/clip-reply)")
-sc= st.sidebar.columns(2)
+sc = st.sidebar.columns(2)
 
-sc[0].image("./huggingface_explode3.png",width=150)
+sc[0].image("./huggingface_explode3.png", width=150)
 sc[1].write(" ")
 sc[1].write(" ")
 sc[1].markdown("## Researching fun")
 
-with st.sidebar.expander("Motivation",expanded=True):
+with st.sidebar.expander("Motivation", expanded=True):
     st.markdown(
         """
-        Reaction GIFs became an integral part of communication. 
+        Reaction GIFs became an integral part of communication.
         They convey complex emotions with many levels, in a short compact format.
 
         If a picture is worth a thousand words then a GIF is worth more.
@@ -32,37 +34,44 @@ with st.sidebar.expander("Motivation",expanded=True):
         This is just a first step in the more ambitious goal of GIF/Image generation.
         """
     )
-top_k=st.sidebar.slider("Show top-K", min_value=1, max_value=50, value=20)
-col_count=4
-file_names=os.listdir("./jpg")
+top_k = st.sidebar.slider("Show top-K", min_value=1, max_value=50, value=20)
+col_count = 4
+file_names = os.listdir("./jpg")
 file_names.sort()
 
-show_val=st.sidebar.button("show all validation set images")
+show_val = st.sidebar.button("show all validation set images")
+
 if show_val:
-    cols=st.sidebar.columns(col_count)
-    for i,im in enumerate(file_names):
-        j=i%col_count
-        cols[j].image("./jpg/"+im)
+    cols = st.sidebar.columns(col_count)
+
+    for i, im in enumerate(file_names):
+        j = i % col_count
+        cols[j].image("./jpg/" + im)
 
 st.write("# Search Reaction GIFs with CLIP ")
 st.write("    ")
 st.write("    ")
-@st.cache(allow_output_mutation=True)
+
+
+@st.cache_resource()
 def load_model():
     model = FlaxHybridCLIP.from_pretrained("ceyda/clip-reply")
     processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
-    processor.tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base")
+    processor.tokenizer = AutoTokenizer.from_pretrained(
+        "cardiffnlp/twitter-roberta-base"
+    )
+
     return model, processor
 
-@st.cache(allow_output_mutation=True)
+
+@st.cache_resource()
 def load_image_index():
-    index = nmslib.init(method='hnsw', space='cosinesimil')
+    index = nmslib.init(method="hnsw", space="cosinesimil")
     index.loadIndex("./features/image_embeddings", load_data=True)
 
     return index
 
 
-
 image_index = load_image_index()
 model, processor = load_model()
 
@@ -72,22 +81,26 @@ def add_image_emb(image):
     image = Image.open(image).convert("RGB")
 
     inputs = processor(text=[""], images=image, return_tensors="jax", padding=True)
-              
+
     inputs["pixel_values"] = jnp.transpose(inputs["pixel_values"], axes=[0, 2, 3, 1])
     features = model(**inputs).image_embeds
-    
+
     image_index.addDataPoint(features)
 
 
-def query_with_images(query_images,query_text):
-    images=[]
-    for im in query_images: 
-        img=Image.open(im).convert("RGB")
+def query_with_images(query_images, query_text):
+    images = []
+
+    for im in query_images:
+        img = Image.open(im).convert("RGB")
+
         if im.name.endswith(".gif"):
             img.seek(0)
         images.append(img)
 
-    inputs = processor(text=[query_text], images=images, return_tensors="jax", padding=True)
+    inputs = processor(
+        text=[query_text], images=images, return_tensors="jax", padding=True
+    )
     inputs["pixel_values"] = jnp.transpose(inputs["pixel_values"], axes=[0, 2, 3, 1])
     outputs = model(**inputs)
     logits_per_image = outputs.logits_per_image.reshape(-1)
@@ -95,53 +108,79 @@ def query_with_images(query_images,query_text):
     probs = jax.nn.softmax(logits_per_image)
     # st.write(probs)
     # st.write(list(zip(images,probs)))
-    results = sorted(list(zip(images,probs)),key=lambda x: x[1], reverse=True)
+    results = sorted(list(zip(images, probs)), key=lambda x: x[1], reverse=True)
     # st.write(results)
+
     return zip(*results)
 
-q_cols=st.columns([5,2,5])    
 
-examples = ["OMG that is disgusting","I'm so scared right now"," I got the job 🎉","Congratulations to all the flax-community week teams","You're awesome","I love you ❤️"]
-example_input = q_cols[0].radio("Example Queries :",examples,index=4,help="These are examples I wrote off the top of my head. They don't occur in the dataset")
+q_cols = st.columns([5, 2, 5])
+
+examples = [
+    "OMG that is disgusting",
+    "I'm so scared right now",
+    " I got the job 🎉",
+    "Congratulations to all the flax-community week teams",
+    "You're awesome",
+    "I love you ❤️",
+]
+example_input = q_cols[0].radio(
+    "Example Queries :",
+    examples,
+    index=4,
+    help="These are examples I wrote off the top of my head. They don't occur in the dataset",
+)
 q_cols[2].markdown(
-    """   
+    """
     Searches among the validation set images if not specified
-    
+
     (There may be non-exact duplicates)
 
 """
 )
 
-query_text = q_cols[0].text_input("Write text you want to get reaction for", value=example_input)
-query_images = q_cols[2].file_uploader("(optional) Upload images to rank them",type=['jpg','jpeg','gif'], accept_multiple_files=True)
+query_text = q_cols[0].text_input(
+    "Write text you want to get reaction for", value=example_input
+)
+query_images = q_cols[2].file_uploader(
+    "(optional) Upload images to rank them",
+    type=["jpg", "jpeg", "gif"],
+    accept_multiple_files=True,
+)
 
 if query_images:
     st.write("Ranking your uploaded images with respect to input text:")
     with st.spinner("Calculating..."):
-        ids, dists = query_with_images(query_images,query_text)
+        ids, dists = query_with_images(query_images, query_text)
 else:
     st.write("Found these images within validation set:")
     with st.spinner("Calculating..."):
-        proc = processor(text=[query_text], images=None, return_tensors="jax", padding=True)
+        proc = processor(
+            text=[query_text], images=None, return_tensors="jax", padding=True
+        )
         vec = np.asarray(model.get_text_features(**proc))
         ids, dists = image_index.knnQuery(vec, k=top_k)
 
-show_gif=st.checkbox("Play GIFs",value=True,help="Will play the original animation. Only first frame is used in training!")
+show_gif = st.checkbox(
+    "Play GIFs",
+    value=True,
+    help="Will play the original animation. Only first frame is used in training!",
+)
 ext = "jpg" if not show_gif else "gif"
-res_cols=st.columns(col_count)
+res_cols = st.columns(col_count)
 
 
-for i,(id_, dist) in enumerate(zip(ids, dists)):
-    j=i%col_count
+for i, (id_, dist) in enumerate(zip(ids, dists)):
+    j = i % col_count
     with res_cols[j]:
         if isinstance(id_, np.int32):
             st.image(f"./{ext}/{file_names[id_][:-4]}.{ext}")
             # st.write(file_names[id_])
-            st.write(1.0 - dist, help="score")
+            st.write(1.0 - dist)
         else:
             st.image(id_)
-            st.write(dist, help="score")
-            
-            
-# Credits   
+            st.write(dist)
+
+
+# Credits
 st.sidebar.caption("Made by [Ceyda Cinarel](https://huggingface.co/ceyda)")

requirements.txt

@@ -1,8 +1,77 @@
-jax
-jaxlib
-flax
-tqdm
-requests
-nmslib
-numpy
-transformers
+# Created by 'make update-requirements-txt'. DO NOT EDIT!
+absl-py==1.4.0
+altair==4.2.2
+attrs==23.1.0
+blinker==1.6.2
+cachetools==5.3.1
+certifi==2023.5.7
+charset-normalizer==3.2.0
+chex==0.1.82
+click==8.1.6
+decorator==5.1.1
+entrypoints==0.4
+etils==1.3.0
+filelock==3.12.2
+flax==0.7.0
+fsspec==2023.6.0
+gitdb==4.0.10
+GitPython==3.1.32
+huggingface-hub==0.16.4
+idna==3.4
+importlib-metadata==6.8.0
+importlib-resources==6.0.0
+jax==0.4.13
+jaxlib==0.4.13
+Jinja2==3.1.2
+jsonschema==4.18.4
+jsonschema-specifications==2023.7.1
+markdown-it-py==3.0.0
+MarkupSafe==2.1.3
+mdurl==0.1.2
+ml-dtypes==0.2.0
+msgpack==1.0.5
+nest-asyncio==1.5.6
+nmslib==2.1.1
+numpy==1.25.1
+opt-einsum==3.3.0
+optax==0.1.5
+orbax-checkpoint==0.2.7
+packaging==23.1
+pandas==2.0.3
+Pillow==9.5.0
+protobuf==4.23.4
+psutil==5.9.5
+pyarrow==12.0.1
+pybind11==2.6.1
+pydeck==0.8.0
+Pygments==2.15.1
+Pympler==1.0.1
+python-dateutil==2.8.2
+pytz==2023.3
+pytz-deprecation-shim==0.1.0.post0
+PyYAML==6.0.1
+referencing==0.30.0
+regex==2023.6.3
+requests==2.31.0
+rich==13.4.2
+rpds-py==0.9.2
+safetensors==0.3.1
+scipy==1.11.1
+six==1.16.0
+smmap==5.0.0
+streamlit==1.25.0
+tenacity==8.2.2
+tensorstore==0.1.40
+tokenizers==0.13.3
+toml==0.10.2
+toolz==0.12.0
+tornado==6.3.2
+tqdm==4.65.0
+transformers==4.31.0
+typing_extensions==4.7.1
+tzdata==2023.3
+tzlocal==4.3.1
+urllib3==2.0.4
+validators==0.20.0
+watchdog==3.0.0
+zipp==3.16.2

unpinned_requirements.txt

@@ -0,0 +1,10 @@
+jax
+jaxlib
+flax
+tqdm
+requests
+nmslib
+numpy
+transformers
+altair<5
+streamlit