add new fields

app.py

@@ -34,7 +34,7 @@ def add_text(history, text):
     return history, gr.Textbox(value="", interactive=False)
 
 
-def bot(history, api_kind):
+def bot(history, api_kind, chunk_table, embedding_model, llm_model, eross_encoder, top_k_param):
     query = history[-1][0]
 
     if not query:
@@ -86,26 +86,67 @@ with gr.Blocks() as demo:
                 )
         txt_btn = gr.Button(value="Submit text", scale=1)
 
-    api_kind = gr.Radio(choices=["HuggingFace", "OpenAI"], value="HuggingFace")
-    chunk_table = gr.Radio(choices=["BGE_CharacterTextSplitter", "BGE_FixedSizeSplitter",
-                                    "BGE_RecursiveCharacterTextSplitter", "MiniLM_CharacterTextSplitter",
-                                    "MiniLM_CharacterTextSplitter", "MiniLM_FixedSizeSplitter",
-                                    "MiniLM_RecursiveCharacterSplitter"], 
+    api_kind = gr.Radio(choices=["HuggingFace",
+                                 "OpenAI"], value="HuggingFace")
+    
+    chunk_table = gr.Radio(choices=["BGE_CharacterTextSplitter", 
+                                    "BGE_FixedSizeSplitter",
+                                    "BGE_RecursiveCharacterTextSplitter",
+                                    "MiniLM_CharacterTextSplitter", 
+                                    "MiniLM_FixedSizeSplitter",
+                                    "MiniLM_RecursiveCharacterSplitter"
+                                    ], 
                                     value="MiniLM_CharacterTextSplitter",
                                     label="Chunk table")
+    embedding_model = gr.Radio(
+                choices=[
+                    "BAAI/bge-large-en-v1.5",
+                    "sentence-transformers/all-MiniLM-L6-v2",
+                ],
+                value="sentence-transformers/all-MiniLM-L6-v2",
+                label='Embedding model'
+            )
+    llm_model = gr.Radio(
+                choices=[
+                    "gpt-3.5-turbo",
+                    "gpt-4-turbo-preview",
+                    "mistralai/Mistral-7B-v0.1",
+                    "mistralai/Mixtral-8x7B-Instruct-v0.1"
+                ],
+                value="gpt-3.5-turbo",
+                label='LLM'
+            )    
+    eross_encoder = gr.Radio(
+                choices=[
+                    "BAAI/bge-reranker-large",
+                    "cross-encoder/ms-marco-MiniLM-L-6-v2",
+                ],
+                value="cross-encoder/ms-marco-MiniLM-L-6-v2",
+                label='Cross-encoder model'
+            )
+    top_k_param = gr.Radio(
+                choices=[
+                    "5",
+                    "10",
+                    "20",
+                    "50",
+                ],
+                value="5",
+                label='top-K'
+            ) 
 
 
     prompt_html = gr.HTML()
     # Turn off interactivity while generating if you click
     txt_msg = txt_btn.click(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
-            bot, [chatbot, api_kind, chunk_table], [chatbot, prompt_html])
+            bot, [chatbot, api_kind, chunk_table, embedding_model, llm_model, eross_encoder, top_k_param], [chatbot, prompt_html])
 
     # Turn it back on
     txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
 
     # Turn off interactivity while generating if you hit enter
     txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
-            bot, [chatbot, api_kind, chunk_table], [chatbot, prompt_html])
+            bot, [chatbot, api_kind, chunk_table, embedding_model, llm_model, eross_encoder, top_k_param], [chatbot, prompt_html])
 
     # Turn it back on
     txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)