Update app.py

app.py

@@ -3,45 +3,25 @@ from huggingface_hub import InferenceClient
 from sentence_transformers import SentenceTransformer
 import torch
 
-# ✅✅✅ change data to match their project 
+# Load knowledge
 with open("knowledge.txt", "r", encoding="utf-8") as file:
-  knowledge = file.read()
+    knowledge = file.read()
 
-print(knowledge)
-
-# ✅✅✅ Change \n to wherever you want the text file to be broken into chunks 
 cleaned_chunks = [chunk.strip() for chunk in knowledge.strip().split("\n") if chunk.strip()]
-print(cleaned_chunks)
-
 model = SentenceTransformer('all-MiniLM-L6-v2')
-
 chunk_embeddings = model.encode(cleaned_chunks, convert_to_tensor=True)
-print(chunk_embeddings)
-
-cleaned_text = ""
 
 def get_top_chunks(query):
     query_embedding = model.encode(query, convert_to_tensor=True)
     query_embedding_normalized = query_embedding / query_embedding.norm()
-
     similarities = torch.matmul(chunk_embeddings, query_embedding_normalized)
-    print(similarities)
     top_indices = torch.topk(similarities, k=5).indices.tolist()
-    print(top_indices)
-
     return [cleaned_chunks[i] for i in top_indices]
 
-top_results = get_top_chunks("What are some good wizard characters?")
-print(top_results)
-
-
 client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2")
 
-
-def respond(message, history):
+def respond(message, history, name):
     response = ""
-    # char_limit= 500
-
     top_chunks = get_top_chunks(message)
     context = "\n".join(top_chunks)
 
@@ -49,9 +29,10 @@ def respond(message, history):
         {
             "role": "system",
             "content": (
-                "You are a chatbot that helps users create characters for role-playing games."
-                "The user wants their character to be called" + character_name.value + "."
-                "Use the following knowledge to inform your answers:\n\n" + context + "and keep your answers under 300 words."
+                f"You are a chatbot that helps users create characters for role-playing games. "
+                f"The user wants their character to be called {name}. "
+                f"Use the following knowledge to inform your answers:\n\n{context}\n\n"
+                "Keep your answers under 300 words."
             )
         }
     ]
@@ -65,7 +46,7 @@ def respond(message, history):
         messages,
         max_tokens=300,
         temperature=1.2,
-        stream=True, 
+        stream=True,
     )
 
     for message in stream:
@@ -74,43 +55,27 @@ def respond(message, history):
             response += token
             yield response
 
-    # if len(response) > char_limit:
-    #     response = response[:char_limit]
-
-    # for punc in [".", "!", "?"]:
-    #     i = response.rfind(punc)
-    #     if i != -1:
-    #         response = response[:i+1]
-    #         break 
-
-    # yield response
-    
-# chatbot = gr.ChatInterface(respond, type="messages")
-
+# === GUI ===
 
 with gr.Blocks() as chatbot:
     with gr.Row(scale=1):
         with gr.Column(scale=1):  
             gr.Image(
-	    value="frog.png", 
-	    show_label=False, 
-	    show_share_button = False, 
-	    show_download_button = False)
+                value="frog.png", 
+                show_label=False, 
+                show_share_button=False, 
+                show_download_button=False
+            )
         with gr.Column(scale=1):
             character_name = gr.Textbox(placeholder="Type your name here…")
-            gr.ChatInterface( respond,
-    type="messages",
-    examples=None,
-    title="Character Creator",
-    description="Welcome! Tell me what you want to create and we can make your character come to life!")
-
-            
-
-    
-    
-
-chatbot.launch()
-
-
 
+            chat = gr.ChatInterface(
+                fn=respond,
+                additional_inputs=[character_name],  # Pass name into function!
+                type="messages",
+                examples=None,
+                title="Character Creator",
+                description="Welcome! Tell me what you want to create and we can make your character come to life!"
+            )
 
+chatbot.launch()