test update

app.py

@@ -1,75 +1,32 @@
-import gradio as gr
 import os
+import time
+import gradio as gr
+
 from groq import Groq
-import pandas as pd
-from datasets import Dataset
+from pinecone import Pinecone, ServerlessSpec
 from semantic_router.encoders import HuggingFaceEncoder
 
 encoder = HuggingFaceEncoder(name="dwzhu/e5-base-4k")
-
 embeds = encoder(["this is a test"])
 dims = len(embeds[0])
 
-############ TESTING ############
-
-import os
-import getpass
-from pinecone import Pinecone
-
-# initialize connection to pinecone (get API key at app.pinecone.io)
-api_key = os.getenv("PINECONE_API_KEY")
-
-# configure client
-pc = Pinecone(api_key=api_key)
-
-from pinecone import ServerlessSpec
-
-spec = ServerlessSpec(
-    cloud="aws", region="us-east-1"
-)
-
-import time
-
+groq_client = Groq(api_key=os.getenv("GROQ_API_KEY"))
+pc = Pinecone(api_key=os.getenv("PINECONE_API_KEY"))
 index_name = "groq-llama-3-rag"
-existing_indexes = [
-    index_info["name"] for index_info in pc.list_indexes()
-]
 
-# check if index already exists (it shouldn't if this is first time)
-if index_name not in existing_indexes:
-    # if does not exist, create index
-    pc.create_index(
-        index_name,
-        dimension=dims,
-        metric='cosine',
-        spec=spec
-    )
-    # wait for index to be initialized
+if index_name not in [i["name"] for i in pc.list_indexes()]:
+    pc.create_index(index_name, dimension=dims, metric='cosine', spec=ServerlessSpec(cloud="aws", region="us-east-1"))
     while not pc.describe_index(index_name).status['ready']:
         time.sleep(1)
 
-# connect to index
 index = pc.Index(index_name)
-time.sleep(1)
-# view index stats
-index.describe_index_stats()
-
 
 def get_docs(query: str, top_k: int) -> list[str]:
-    # encode query
     xq = encoder([query])
-    # search pinecone index
     res = index.query(vector=xq, top_k=top_k, include_metadata=True)
-    # get doc text
-    docs = [x["metadata"]['content_snippet'] for x in res["matches"]]
-    return docs
-
-from groq import Groq
-groq_client = Groq(api_key=os.getenv("GROQ_API_KEY"))
+    return [x["metadata"]['content_snippet'] for x in res["matches"]]
 
 def generate(query: str, history):
-
-    # Create system message
     if not history:
         system_message = (
             "You are a friendly and knowledgeable New Yorker who loves sharing recommendations about the city. "
@@ -77,45 +34,29 @@ def generate(query: str, history):
             "Your goal is to give recommendations tailored to what the user is asking for, whether they want iconic attractions "
             "or lesser-known spots loved by locals.\n\n"
             "Use the provided context to enhance your responses with real local insights, but only include details that are relevant "
-            "to the user’s question. If the context provides useful recommendations that match what the user is asking for, use them. "
-            "If the context is unrelated or does not fully answer the question, rely on your general NYC knowledge instead.\n\n"
-            "Be specific when recommending places—mention neighborhoods, the atmosphere, and why someone might like a spot. "
-            "Keep your tone warm, conversational, and engaging, like a close friend who genuinely enjoys sharing their city.\n\n"
-            "CONTEXT:\n"
-            "\n---\n".join(get_docs(query, top_k=5))
+            "to the user’s question.\n\n"
+            "CONTEXT:\n" + "\n---\n".join(get_docs(query, top_k=5))
         )
-        messages = [
-            {"role": "system", "content": system_message},
-        ]
+        messages = [{"role": "system", "content": system_message}]
     else:
-        # Establish history
         messages = []
         for user_msg, bot_msg in history:
             messages.append({"role": "user", "content": user_msg})
             messages.append({"role": "assistant", "content": bot_msg})
-            messages.append({"role": "assistant", "content": bot_msg})
-        system_message = (
-            "Here is additional context based on the newest query.\n\n"
-            "CONTEXT:\n"
-            "\n---\n".join(get_docs(query, top_k=5))
-        )
-        messages.append({"role": "system", "content": system_message})
+        messages.append({"role": "system", "content": "CONTEXT:\n" + "\n---\n".join(get_docs(query, top_k=5))})
 
-    # Add query
     messages.append({"role": "user", "content": query})
-    
-    # generate response
-    chat_response = groq_client.chat.completions.create(
-        model="llama3-70b-8192",
-        messages=messages
-    )
-    return chat_response.choices[0].message.content
-
+    response = groq_client.chat.completions.create(model="llama3-70b-8192", messages=messages)
+    return response.choices[0].message.content
 
-# Custom CSS for iPhone-style chat
 custom_css = """
 .gradio-container {
-    background: transparent !important;
+    background: #ffffff !important;
+}
+.chatbot {
+    background: #f8f8f8 !important;
+    border-radius: 15px;
+    padding: 10px;
 }
 .chat-message {
     display: flex;
@@ -141,19 +82,28 @@ custom_css = """
     border-bottom-right-radius: 5px;
 }
 .chat-bubble.assistant {
-    background-color: #f0f0f0;
+    background-color: #d1d1d6;
     color: black;
     border-bottom-left-radius: 5px;
 }
-.profile-pic {
-    width: 40px;
-    height: 40px;
-    border-radius: 50%;
-    margin: 0 10px;
-}
 """
 
-# Gradio Interface
-demo = gr.ChatInterface(generate, css=custom_css)
+with gr.Blocks(css=custom_css) as demo:
+    chatbot = gr.Chatbot(label="NYC Buddy", elem_classes=["chatbot"])
+    state = gr.State([])
+    user_input = gr.Textbox(placeholder="Ask me anything about NYC!")
+    send_btn = gr.Button("Send")
+
+    def respond(message, history):
+        response = generate(message, history)
+        history = history + [(message, response)]
+        return history, ""
+
+    def startup():
+        welcome_msg = "Hey! I'm your NYC Buddy. Looking for local tips, hidden gems, or iconic spots? Just ask!"
+        return [(None, welcome_msg)], []
+
+    demo.load(startup, outputs=[chatbot, state])
+    send_btn.click(respond, inputs=[user_input, state], outputs=[chatbot, user_input])
 
 demo.launch()