Update app.py

app.py

@@ -2,7 +2,7 @@ from dotenv import load_dotenv
 import time
 import gradio as gr
 from PIL import Image
-from ChatCohere import chat_completion, summarize
+from ChatCohere import chat_completion, summarize, card_completion
 from PokemonCards import choose_random_cards
 from QdrantRag import NeuralSearcher, SemanticCache, qdrant_client, encoder, image_encoder, processor, sparse_encoder
 load_dotenv()
@@ -11,7 +11,7 @@ load_dotenv()
 searcher = NeuralSearcher("pokemon_texts", "pokemon_images", qdrant_client, encoder, image_encoder, processor, sparse_encoder)
 semantic_cache = SemanticCache(qdrant_client, encoder, "semantic_cache", 0.75)
 
-def chat_pokemon(message: str, history):
+def chat_pokemon(message: str):
     answer = semantic_cache.search_cache(message)
     if answer != "":
         r = ""
@@ -23,8 +23,7 @@ def chat_pokemon(message: str, history):
         context_search = searcher.search_text(message)
         reranked_context = searcher.reranking(message, context_search)
         context = "\n\n-----------------\n\n".join(reranked_context)
-        final_prompt = f"USER QUERY:\n\n{message}\n\nCONTEXT:\n\n{context}"
-        response = chat_completion(final_prompt)
+        response = chat_completion(message, "Context:\n\n"+context)
         semantic_cache.upload_to_cache(message, response)
         r = ""
         for c in response:
@@ -41,14 +40,14 @@ def card_package(n_cards:int=5):
     description, cards = choose_random_cards(n_cards)
     package = [f"![Card {i+1}]({cards[i]})" for i in range(len(cards))]
     cards_message = "\n\n".join(package)
-    natural_lang_description = chat_completion(f"Can you enthusiastically describe the cards in this package?\n\n{description}")
+    natural_lang_description = card_completion(f"Can you enthusiastically describe the cards in this package?\n\n{description}")
     return "## Your package:\n\n" + cards_message + "\n\n## Description:\n\n" + summarize(natural_lang_description)
 
 
 iface1 = gr.ChatInterface(fn=chat_pokemon, title="Pokemon Chatbot", description="Ask any question about Pokemon and get an answer!")
 iface2 = gr.Interface(fn=what_pokemon, title="Pokemon Image Classifier", description="Upload an image of a Pokemon and get its name!", inputs="image", outputs="text")
-iface3 = gr.Interface(fn=card_package, title="Pokemon Card Package", description="Get a package of random Pokemon cards!", inputs=gr.Slider(5,10,step=1, label="Number of cards"), outputs=gr.Markdown(value="Your output will be displayed here", label="Card Package"))
+iface3 = gr.Interface(fn=card_package, title="Pokemon Card Package", description="Get a package of random Pokemon cards!", inputs=gr.Slider(5,10,step=1), outputs=gr.Markdown(value="Your output will be displayed here", label="Card Package"))
 
 iface = gr.TabbedInterface([iface1, iface2, iface3], ["PokemonChat", "Identify Pokemon", "Card Package"])
 
-iface.launch()
+iface.launch(server_name="0.0.0.0", server_port=7860)