Update app.py

app.py

@@ -9,15 +9,8 @@ For more information on `huggingface_hub` Inference API support, please check th
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
 
-tableau_de_mots=mot_cle("mots_clés.txt")
-mots_a_verifier = tableau_de_mots
-docs_text, docs_embeddings = load_data()
-question="give me the advantage of djezzy legend for 2500 DA ?"
-prompt=pip(question,docs_text, docs_embeddings,mots_a_verifier,vector_db)
-print(prompt)
-
 def respond(
-    prompt,
+    message,
     history: list[tuple[str, str]],
     system_message,
     max_tokens,
@@ -32,7 +25,7 @@ def respond(
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
 
-    messages.append({"role": "user", "content": prompt=pip(message,docs_text, docs_embeddings,mots_a_verifier,vector_db)})
+    messages.append({"role": "user", "content": message)
 
     response = ""
 
@@ -54,7 +47,7 @@ For information on how to customize the ChatInterface, peruse the gradio docs: h
 tableau_de_mots=mot_cle("mots_clés.txt")
 mots_a_verifier = tableau_de_mots
 docs_text, docs_embeddings = load_data()
-question=stt(message)
+question=message
 prompt=pip(question,docs_text, docs_embeddings,mots_a_verifier,vector_db)
 print(prompt)
 
@@ -71,6 +64,7 @@ demo = gr.ChatInterface(
             step=0.05,
             label="Top-p (nucleus sampling)",
         ),
+        gr.Textbox(value=prompt, label="Prompt"),
     ],
 )