Create app.py

app.py

@@ -0,0 +1,64 @@
+from typing import Dict, Union
+from gliner import GLiNER
+import gradio as gr
+
+model = GLiNER.from_pretrained("xomad/gliner-model-merge-large-v1.0").to('cpu')
+
+
+def merge_entities(entities):
+    if not entities:
+        return []
+    merged = []
+    current = entities[0]
+    for next_entity in entities[1:]:
+        if next_entity['entity'] == current['entity'] and (next_entity['start'] == current['end'] + 1 or next_entity['start'] == current['end']):
+            current['word'] += ' ' + next_entity['word']
+            current['end'] = next_entity['end']
+        else:
+            merged.append(current)
+            current = next_entity
+    merged.append(current)
+    return merged
+
+def process(
+    prompt:str, text, threshold: float, nested_ner: bool, labels: str = ["match"]
+) -> Dict[str, Union[str, int, float]]:
+    text = prompt + "\n" + text
+    r = {
+        "text": text,
+        "entities": [
+            {
+                "entity": entity["label"],
+                "word": entity["text"],
+                "start": entity["start"],
+                "end": entity["end"],
+                "score": 0,
+            }
+            for entity in model.predict_entities(
+                text, labels, flat_ner=not nested_ner, threshold=threshold
+            )
+        ],
+    }
+    r["entities"] =  merge_entities(r["entities"])
+    return r
+
+with gr.Blocks(title="Open Information Extracting") as open_ie_interface:
+    prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here")
+    input_text = gr.Textbox(label="Text input", placeholder="Enter your text here")
+    threshold = gr.Slider(0, 1, value=0.3, step=0.01, label="Threshold", info="Lower the threshold to increase how many entities get predicted.")
+    nested_ner = gr.Checkbox(label="Nested NER", info="Allow for nested NER?")
+    output = gr.HighlightedText(label="Predicted Entities")
+    submit_btn = gr.Button("Submit")
+    
+    theme=gr.themes.Base()
+
+    input_text.submit(fn=process, inputs=[prompt, input_text, threshold, nested_ner], outputs=output)
+    prompt.submit(fn=process, inputs=[prompt, input_text, threshold, nested_ner], outputs=output)
+    threshold.release(fn=process, inputs=[prompt, input_text, threshold, nested_ner], outputs=output)
+    submit_btn.click(fn=process, inputs=[prompt, input_text, threshold, nested_ner], outputs=output)
+    nested_ner.change(fn=process, inputs=[prompt, input_text, threshold, nested_ner], outputs=output)
+
+
+if __name__ == "__main__":
+    
+    open_ie_interface.launch()