Add threshold field

app.py

@@ -23,9 +23,6 @@ class ClapSSGradio():
         self.name = name
         self.k = k
 
-        print("Env?!")
-        print(os.getenv('HUGGINGFACE_API_TOKEN')[:2])
-
         self.model = ClapModel.from_pretrained(
             f"Audiogen/{name}", use_auth_token=os.getenv('HUGGINGFACE_API_TOKEN'))
         self.tokenizer = ClapProcessor.from_pretrained(
@@ -48,12 +45,12 @@ class ClapSSGradio():
             query, return_tensors="pt", padding='max_length', max_length=77, truncation=True)
         return self.model.get_text_features(**inputs).cpu().numpy().tolist()[0]
 
-    def _similarity_search(self, query):
+    def _similarity_search(self, query, threshold):
         results = self.client.search(
             collection_name=self.name,
             query_vector=self._embed_query(query),
             limit=self.k,
-            score_threshold=0.5,
+            score_threshold=threshold,
         )
 
         containers = [result.payload['container'] for result in results]
@@ -94,21 +91,17 @@ class ClapSSGradio():
     def launch(self, share=False):
         # gradio app structure
         with gr.Blocks(title='Clap Semantic Search') as ui:
-
             with gr.Row():
                 with gr.Column(variant='panel'):
                     search = gr.Textbox(placeholder='Search Samples')
-
+                    float_input = gr.Number(label='Similarity threshold [min: 0.1 max: 1]', default=0.5, minimum=0.1, maximum=1)
                 with gr.Column():
                     audioboxes = []
                     gr.Markdown("Output")
                     for i in range(self.k):
                         t = gr.components.Audio(label=f"{i}", visible=True)
                         audioboxes.append(t)
-
-            search.submit(fn=self._similarity_search, inputs=[
-                          search], outputs=audioboxes)
-
+            search.submit(fn=self._similarity_search, inputs=[search, float_input], outputs=audioboxes)
             ui.launch(share=share)