Update app.py

app.py

@@ -174,14 +174,14 @@ def scrape_with_trafilatura(url, max_chars=None, timeout=5, use_beautifulsoup=Fa
         return ""
 
 def rephrase_query(chat_history, query, temperature=0.2):
-    system_prompt = """You are a highly intelligent conversational chatbot. Your task is to analyze the given context and new query, then decide whether to rephrase the query with or without incorporating the context. Follow these steps:
-1. Determine if the new query is a continuation of the previous conversation or an entirely new topic.
-2. If it's a continuation, rephrase the query by incorporating relevant information from the context to make it more specific and contextual.
-3. If it's a new topic, rephrase the query to make it more appropriate for a web search, focusing on clarity and accuracy without using the previous context.
-4. Provide ONLY the rephrased query without any additional explanation or reasoning."""
+    system_prompt = """You are a highly intelligent and context-aware conversational assistant. Your task is to accurately rephrase the given query based on the provided conversation context. Follow these steps:
+1. Assess whether the new query logically follows from the conversation context or introduces a new, unrelated topic.
+2. If it is a continuation, incorporate the most relevant details from the context to make the rephrased query more specific and aligned with the ongoing conversation.
+3. If it introduces a new topic, rewrite the query to ensure clarity, precision, and suitability for a standalone search, avoiding any irrelevant context from the conversation.
+4. Return ONLY the rephrased query, ensuring it is concise, clear, and contextually accurate, without any additional commentary or explanation."""
 
     user_prompt = f"""
-Context:
+Conversation context:
 {chat_history}
 
 New query: {query}
@@ -269,7 +269,7 @@ def is_content_unique(new_content, existing_contents, similarity_threshold=0.8):
     return True
 
 def assess_relevance_and_summarize(llm_client, query, document, temperature=0.2):
-    system_prompt = """You are a financial analyst AI assistant. Your task is to assess whether the given text is relevant to the user's query from a financial perspective and provide a brief summary if it is relevant."""
+    system_prompt = """You are a world class AI assistant. Your task is to assess whether the given text is relevant to the user's query and provide a brief summary if it is relevant."""
 
     user_prompt = f"""
 Query: {query}
@@ -278,7 +278,7 @@ Document Content:
 {document['content']}
 
 Instructions:
-1. Assess if the document is relevant to the query from a financial analyst's perspective.
+1. Assess if the document is relevant to the QUERY  made by the user.
 2. If relevant, summarize the main points in 1-2 sentences.
 3. If not relevant, simply state "Not relevant".
 
@@ -582,6 +582,7 @@ iface = gr.ChatInterface(
     chat_function,
     title="SearXNG Scraper for Financial News",
     description="Enter your query, and I'll search the web for the most recent and relevant financial news, scrape content, and provide summarized results.",
+    theme=gr.Theme.from_hub("allenai/gradio-theme"),
     additional_inputs=[
         gr.Slider(5, 20, value=10, step=1, label="Number of initial results"),
         gr.Dropdown(["bs4", "trafilatura", "scrapy", "newspaper"], value="bs4", label="Scraping Method"),
@@ -607,7 +608,7 @@ iface = gr.ChatInterface(
         show_copy_button=True,
         likeable=True,
         layout="bubble",
-        height=400,
+        height=600,
     )
 )