Edits and improvements to Gradio UI

assets/html.py

@@ -3,18 +3,58 @@
 TITLE = (
     '''
         <center> 
-            <h1>Agentic RSS reader</h1>
+            <h1>RASS (retrieval augmented simple syndication) Agent</h1>
+            <h2>Agentic RSS feed reader</h2>
         </center>
     '''
 )
 
 DESCRIPTION = (
     '''
-        <p>Uses sister Space 
+        <p><b>Problem</b>: I love RSS feeds, but need help keeping up with all of the content from my subscriptions.
+        
+        <b>Solution</b>: Build a tool to allow LLMs to find and interact with RSS feeds on behalf of the user.</p>
+        <h2>Introduction</h2>
+        <p>This demonstration uses sister space
         <a href='https://huggingface.co/spaces/Agents-MCP-Hackathon/rss-mcp-server'>
-        RSS feed reader</a> via MCP. Click 'Connect to MCP server' to get started. 
-        Check out the <a href='https://github.com/gperdrizet/MCP-hackathon/tree/main'>
+        RSS feed reader</a> via MCP to interact with RSS feeds. Click 'Connect to MCP 
+        server' to get started. If it takes a minute or two to reply, don't worry the inference
+        container was probably cold and spinning up. Check out the 
+        <a href='https://github.com/gperdrizet/MCP-hackathon/tree/main'>
         main project repo on GitHub</a>. Both Spaces by
         <a href=https://www.linkedin.com/in/gperdrizet/'>George Perdrizet</a>.</p>
+
+        I love RSS feeds - they remind me of a time when the internet was a weird and
+        wonderful place, filled with interesting content hiding behind every link. The tools
+        to produce and navigate that content have improved by leaps and bounds. However, 
+        the improvement has not come without some losses. Content often feels homogeneous and
+        it is too often painfully apparent that your favorite platform has a large degree of
+        control over what content you see and what content you don't.
+
+        This tool give the user back some of that control. It let's them decide what content
+        and sources they are interested in. I built it because I want access to diverse,
+        unfiltered publishing by many sources, paired modern AI to help me navigate it. 
+        I want the model to help me ingest my feed, not create it for me!
     '''
 )
+
+FEATURES_TOOLS ='''
+    ## Features
+
+    1. Inference with Anthropic's efficient claude-3-haiku model.
+    2. Custom MCP client with asynchronous server side events, retry and error handling based on the excellent repo by [Adel Zaalouk](https://github.com/zanetworker/mcp-playground/tree/main).
+    3. Multi-turn re-prompting to allow LLM workflows with multiple tool calls.
+    4. Queue and worker system to show user what's going on 'under the hood' while the model calls tools and generates replies. 
+    
+    ## Tools
+
+    1. `get_feed()`: Given a website name or URL, find its RSS feed and
+        return recent article titles, links and a generated summary of content if
+        avalible. Caches results for fast retrieval by other tools. Embeds content
+        to vector database for subsequent RAG.
+    2. `context_search()`: Vector search on article content for RAG context.
+    3. `find_article()`: Uses vector search on article content to find title of article
+        that user is referring to.
+    4. `get_summary()`: Gets article summary from Redis cache using article title.
+    5. `get_link()`: Gets article link from Redis cache using article title.
+'''

client/mcp_client.py

@@ -71,7 +71,7 @@ class MCPTimeoutError(Exception):
 class MCPClientWrapper:
     '''Main client wrapper class for interacting with Model Context Protocol (MCP) endpoints'''
 
-    def __init__(self, endpoint: str, timeout: float = 30.0, max_retries: int = 3):
+    def __init__(self, endpoint: str, timeout: float = 360.0, max_retries: int = 3):
         '''Initialize MCP client with endpoint URL
         
         Args:

client/tool_workflows.py

@@ -9,10 +9,10 @@ from client import prompts
 from client.anthropic_bridge import AnthropicBridge
 
 INTERMEDIATE_REPLY_HINTS = {
-    'context_search': 'Let me find some additional context before I generate a final answer.',
-    'find_article': 'I will find the title of that article.',
-    'get_summary': 'I will summarize that article',
-    'get_link': 'I will get the link to that article'
+    'rss_mcp_server_context_search': 'Let me find some additional context before I generate a final answer.',
+    'rss_mcp_server_find_article': 'I will find the title of that article.',
+    'rss_mcp_server_get_summary': 'I will summarize that article',
+    'rss_mcp_server_get_link': 'I will get the link to that article'
 }
 
 async def tool_loop(
@@ -37,7 +37,7 @@ async def tool_loop(
     tool_call = result['tool_call']
     tool_name = tool_call['name']
 
-    if tool_name == 'get_feed':
+    if tool_name == 'rss_mcp_server_get_feed':
         reply = await get_feed_call(
             user_query,
             result,

rss_client.py

@@ -40,8 +40,7 @@ logger = logging.getLogger(__name__)
 
 # Handle MCP server connection and interactions
 RSS_CLIENT = MCPClientWrapper(
-    #'https://agents-mcp-hackathon-rss-mcp-server.hf.space/gradio_api/mcp/sse',
-    'http://127.0.0.1:7860/gradio_api/mcp/sse'
+    'https://agents-mcp-hackathon-rss-mcp-server.hf.space/gradio_api/mcp/sse'
 )
 logger.info('Started MCP client')
 
@@ -57,6 +56,7 @@ logger.info('Started Anthropic API bridge')
 OUTPUT_QUEUE = queue.Queue()
 logger.info('Created response queue')
 
+
 def user_message(message: str, history: list) -> Tuple[str, list]:
     '''Adds user message to conversation and returns for immediate posting.
 
@@ -102,11 +102,12 @@ def send_message(chat_history: list):
                 yield chat_history
 
 
-with gr.Blocks(title='MCP RSS client') as demo:
+with gr.Blocks(title='RASS agent') as demo:
     with gr.Row():
         gr.HTML(html.TITLE)
 
     gr.Markdown(html.DESCRIPTION)
+    gr.Markdown(html.FEATURES_TOOLS)
 
     # MCP connection/tool dump
     connect_btn = gr.Button('Connect to MCP server')
@@ -128,7 +129,7 @@ with gr.Blocks(title='MCP RSS client') as demo:
     # Chat interface
     chatbot = gr.Chatbot(
         value=[],
-        height=250,
+        height=500,
         type='messages',
         show_copy_button=True
     )