Interface improvements

app.py

@@ -30,62 +30,40 @@ class KeyphraseExtractionPipeline(TokenClassificationPipeline):
 model_name = "ml6team/keyphrase-extraction-kbir-inspec"
 extractor = KeyphraseExtractionPipeline(model=model_name)
 
-text = """
-Keyphrase extraction is a technique in text analysis where you extract the
-important keyphrases from a document. Thanks to these keyphrases humans can
-understand the content of a text very quickly and easily without reading it
-completely. Keyphrase extraction was first done primarily by human annotators,
-who read the text in detail and then wrote down the most important keyphrases.
-The disadvantage is that if you work with a lot of documents, this process
-can take a lot of time. 
-
-Here is where Artificial Intelligence comes in. Currently, classical machine
-learning methods, that use statistical and linguistic features, are widely used
-for the extraction process. Now with deep learning, it is possible to capture
-the semantic meaning of a text even better than these classical methods.
-Classical methods look at the frequency, occurrence and order of words
-in the text, whereas these neural approaches can capture long-term
-semantic dependencies and context of words in a text.
-""".replace("\n", " ")
-
-keyphrases = extractor(text)
-
-print(keyphrases)
-
-
-def keyphrases_out(input):
-    input = input.replace("\n", " ")
-    keyphrases = extractor(input)
-    out = "The Key Phrases in your text are:\n\n"
-    for k in keyphrases:
-        out += k + "\n"
+#TODO: add further preprocessing
+def keyphrases_extraction(text: str) -> str:
+    keyphrases = extractor(text)
     return keyphrases
 
-def wikipedia_search(input):
+def wikipedia_search(input: str) -> str:
     input = input.replace("\n", " ")
-    keyphrases = extractor(input)
+    keyphrases = keyphrases_extraction(input)
     wiki = wk.Wikipedia('en')
-
-    page = wiki.page("")
-    return page.summary
-
-
-
-
-    # for k in keyphrases:
-    #     page = wiki.page(k)
-    #     if page.exists():
-    #         break
-    # return page.summary
+    
+    try :
+        #TODO: add better extraction and search
+        page = wiki.page(keyphrases[0])
+        return  page.summary
+    except:
+        return "I cannot answer this question"
 
 # =====[ DEFINE INTERFACE ]===== #'
-# demo = gr.Interface(fn=wikipedia_search, inputs = "text", outputs = "text")
-# demo.launch(share=True)
-
-
-
+title = "Azza Chatbot"
+examples = [
+    ["Where is the Eiffel Tower?"],
+    ["What is the population of France?"]
+]
 
 
+demo = gr.Interface(
+    title = title,
 
+    fn=wikipedia_search,
+    inputs = "text", 
+    outputs = "text",
 
+    examples=examples
+    )
 
+if __name__ == "__main__":
+    demo.launch(share=True)

requirements.txt

@@ -0,0 +1,5 @@
+os
+gradio 
+wikipedia-api
+transformers
+transformers.pipelines