Update app.py

app.py

@@ -24,6 +24,12 @@ ENTITY_COLORS = {
     "ORG": "#f39c12",
     "PER": "#3498db"
 }
+MAP_MODELS = {
+    "":"",
+    "fr_ner4archives_V3_camembert_base": "https://huggingface.co/ner4archives/fr_ner4archives_V3_camembert_base/resolve/main/fr_ner4archives_V3_camembert_base-any-py3-none-any.whl#sha256=919aca257e4b2342a3773e7dcc3442b30f2ac50c4a3466d5ecda5e0e337ea396",
+    "fr_ner4archives_v3_default": "https://huggingface.co/ner4archives/fr_ner4archives_v3_default/resolve/main/fr_ner4archives_v3_default-any-py3-none-any.whl#sha256=040a5c67a7e5a14e0125b2600e6aff1323f8ba9d800d5ab49446faeaf2dad6e6",
+    "fr_ner4archives_v3_with_vectors":"https://huggingface.co/ner4archives/fr_ner4archives_v3_with_vectors/resolve/main/fr_ner4archives_v3_with_vectors-any-py3-none-any.whl#sha256=4c938618ce84a919008d17822980cfd914f9ad8f73231a64cd1ffcaa80ab09f2"
+}
 
 # Read configuration
 with open(CONFIG_FILE, mode="r") as json_file:
@@ -123,59 +129,68 @@ def main():
         plain = "\n".join(sentences)
         col2.text_area("Plain Text View (read-only)", value=plain, height=500, disabled=True)
         flag_view = True
+        flag_model = False
 
         if flag_view:
             streamlit.write("## ⚙️ Configure NER pipeline and options:")
             streamlit.write("⚠️ Using Bert based model and/or linking may increase considerably the processing time.")
             # Normaly: Load from PIP or directory (install issues with HF spaces)
-            models = ["fr_ner4archives_v3_with_vectors", "fr_ner4archives_v3", "fr_ner4archives_V3_camembert_base"]
-            #for pipe in spacy.info()["pipelines"]:
-            #    models.append(pipe)
+            models = [str(key) for key in MAP_MODELS.keys()]
             option = streamlit.selectbox(
                 'Choose a NER model you want to apply in the list: ',
-                models)
+                models,
+                index=0)
             model = option
-            map_model = {
-                "fr_ner4archives_V3_camembert_base": "https://huggingface.co/ner4archives/fr_ner4archives_V3_camembert_base/resolve/main/fr_ner4archives_V3_camembert_base-any-py3-none-any.whl#sha256=919aca257e4b2342a3773e7dcc3442b30f2ac50c4a3466d5ecda5e0e337ea396",
-                "fr_ner4archives_v3": "https://huggingface.co/ner4archives/fr_ner4archives_v3_default/resolve/main/fr_ner4archives_v3_default-any-py3-none-any.whl#sha256=040a5c67a7e5a14e0125b2600e6aff1323f8ba9d800d5ab49446faeaf2dad6e6",
-                "fr_ner4archives_v3_with_vectors":"https://huggingface.co/ner4archives/fr_ner4archives_v3_with_vectors/resolve/main/fr_ner4archives_v3_with_vectors-any-py3-none-any.whl#sha256=4c938618ce84a919008d17822980cfd914f9ad8f73231a64cd1ffcaa80ab09f2"
-            }
-            try:
-                spacy.load(model)
-            except:
-                streamlit.write(f"Download model: {model} in progress...")
-                subprocess.run(["pip", "install", map_model[model]])
+            model_loaded = None
             if model != "":
-                flag_model = True
-
-            gpu = streamlit.checkbox('Check to use GPU (if available)', value=False)
-            gpu_icon = "❌"
-            if gpu:
-                spacy.prefer_gpu()
-                gpu_icon = "✅️"
-            else:
-                spacy.require_cpu()
-
-            if is_entity_fishing_online():
-                streamlit.write("Entity-fishing server status: 🟢 (you can use linking feature)")
-                linking = streamlit.checkbox('Check to apply named entity linking (entity-fishing component)',
-                                             value=False)
-                linkingicon = "✅️"
-                if linking is False:
+                try:
+                    model_loaded = spacy.load(model)
+                    flag_model = True
+                    streamlit.write(f"{model} is available locally.")
+                except:
+                    placeholder = streamlit.empty()
+                    button = streamlit.button(f"Download model: {model}")
+                    with placeholder.container():
+                        if button:
+                            streamlit.write(f"Download model: {model} in progress...")
+                            p1 = subprocess.Popen(["pip", "install", MAP_MODELS[model]])
+                            o = p1.wait()
+                            if o == 0:
+                                streamlit.write(f"Download model: {model} done.")
+                                model_loaded = spacy.load(model)
+                                flag_model = True
+                                streamlit.write(f"{model} is available locally.")
+                    placeholder.empty()
+
+            if flag_model:
+                gpu = streamlit.checkbox('Check to use GPU (if available)', value=False)
+                gpu_icon = "❌"
+                if gpu:
+                    spacy.prefer_gpu()
+                    gpu_icon = "✅️"
+                else:
+                    spacy.require_cpu()
+
+                if is_entity_fishing_online():
+                    streamlit.write("Entity-fishing server status: 🟢 (you can use linking feature)")
+                    linking = streamlit.checkbox('Check to apply named entity linking (entity-fishing component)',
+                                                 value=False)
+                    linkingicon = "✅️"
+                    if linking is False:
+                        linkingicon = "❌"
+                else:
+                    streamlit.write("Entity-fishing server status: 🔴 (you can't use linking feature)")
+                    linking = False
                     linkingicon = "❌"
-            else:
-                streamlit.write("Entity-fishing server status: 🔴 (you can't use linking feature)")
-                linking = False
-                linkingicon = "❌"
-            streamlit.write("#### Actual Parameters:")
-            streamlit.write(f'- NER model selected: {option}\n - Linking activated: {linkingicon} - GPU activated: {gpu_icon}')
+                streamlit.write("#### Actual Parameters:")
+                streamlit.write(f'- NER model selected: {option}\n - Linking activated: {linkingicon} - GPU activated: {gpu_icon}')
 
         # Launch NER process:
         if flag_model:
             if streamlit.button('Launch'):
                 plain = "\n".join(sentences)
                 with streamlit.spinner('Initialize NER...'):
-                    nlp = spacy.load(model)
+                    nlp = model_loaded
                     nlp.max_length = 5000000
                     if linking:
                         nlp.add_pipe('entityfishing',