model as a pipeline, bug fixes in index loader function

app.py

@@ -4,6 +4,8 @@ import faiss
 
 from transformers import pipeline
 
+import requests
+
 
 sample_text = """Europejscy astronomowie odkryli planetę
 pozasłoneczną pochodzącą spoza naszej galaktyki, czyli 
@@ -23,14 +25,13 @@ def load_index(index_data: str = "clarin-knext/entity-linking-index"):
         idx: (e_id, e_text) for idx, (e_id, e_text) in
         enumerate(zip(ds['entities'], ds['texts']))
     }
-    faiss_index = faiss.load_index("./encoder.faissindex")
+    faiss_index = faiss.read_index("./encoder.faissindex", faiss.IO_FLAG_MMAP)
     return index_data, faiss_index
-    
 
 
 def load_model(model_name: str = "clarin-knext/entity-linking-encoder"):
-    model = pipeline(task=model_name)
-    return model
+    pipe = pipeline("feature-extraction", model=model_name)
+    return pipe
 
 
 def predict(model, index, query: str = sample_text, top_k: int=3):

space.py

@@ -1,50 +0,0 @@
-import gradio as gr
-import datasets
-import faiss
-
-from transformers import pipeline
-
-
-sample_text = """Europejscy astronomowie odkryli planetę
-pozasłoneczną pochodzącą spoza naszej galaktyki, czyli 
-[START_ENT] Drogi Mlecznej [END_ENT]. Obserwacji dokonali
-2,2-metrowym teleskopem MPG/ESO."""
-
-
-textbox = gr.Textbox(
-    label="Type your query here.",
-    placeholder=sample_text, lines=10
-)
-
-
-def load_index(index_data: str = "clarin-knext/entity-linking-index"):
-    ds = datasets.load_dataset(index_data)['train']
-    index_data = {
-        idx: (e_id, e_text) for idx, (e_id, e_text) in
-        enumerate(zip(ds['entities'], ds['texts']))
-    }
-    faiss_index = faiss.load_index("./encoder.faissindex")
-    return index_data, faiss_index
-    
-
-
-def load_model(model_name: str = "clarin-knext/entity-linking-encoder"):
-    model = pipeline(task=model_name)
-    return model
-
-
-def predict(model, index, query: str = sample_text, top_k: int=3):
-    index_data, faiss_index = index
-    query = model(query)
-    
-    scores, indices = faiss_index.search(query, top_k)
-    results = [index_data[idx] for row in indices for idx in row]
-    
-    return "\n".join(str(results))
-
-
-model = load_model()
-index = load_index()
-
-
-demo = gr.Interface(fn=predict, inputs=textbox, outputs="text").launch()