Update app.py

app.py

@@ -1,25 +1,41 @@
 # app.py
-import os, asyncio, aiohttp, nest_asyncio
+import os
+import logging
+import asyncio
+import nest_asyncio
+from datetime import datetime
+import uuid
+import aiohttp
+import gradio as gr
+
+from langfuse.llama_index import LlamaIndexInstrumentor
 from llama_index.tools.duckduckgo import DuckDuckGoSearchToolSpec
 from llama_index.tools.weather import OpenWeatherMapToolSpec
 from llama_index.tools.playwright import PlaywrightToolSpec
 from llama_index.core.tools import FunctionTool
-from llama_index.core.agent.workflow import ReActAgent, FunctionAgent, AgentWorkflow
+from llama_index.core.agent.workflow import AgentWorkflow
+from llama_index.core.workflow import Context
 from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
-from llama_index.llms.openai import OpenAI
 from llama_index.core.memory import ChatMemoryBuffer
 from llama_index.readers.web import RssReader
-from llama_index.core.workflow import Context
-import gradio as gr
+
 import subprocess
 subprocess.run(["playwright", "install"])
 
 # allow nested loops in Spaces
 nest_asyncio.apply()
 
+# --- Llangfuse ---
+instrumentor = LlamaIndexInstrumentor(
+    public_key=os.environ.get("LANGFUSE_PUBLIC_KEY"),
+    secret_key=os.environ.get("LANGFUSE_SECRET_KEY"),
+    host=os.environ.get("LANGFUSE_HOST"),
+)
+instrumentor.start()
+
 # --- Secrets via env vars ---
 HF_TOKEN            = os.getenv("HF_TOKEN")
-OPENAI_API_KEY      = os.getenv("OPENAI_API_KEY")
+# OPENAI_API_KEY      = os.getenv("OPENAI_API_KEY")
 OPENWEATHERMAP_KEY  = os.getenv("OPENWEATHERMAP_API_KEY")
 SERPER_API_KEY      = os.getenv("SERPER_API_KEY")
 
@@ -29,16 +45,18 @@ llm = HuggingFaceInferenceAPI(
     token=HF_TOKEN, 
     task="conversational"
 )
-# OpenAI for pure function-calling
-openai_llm = OpenAI(
-    model="gpt-4o",
-    api_key=OPENAI_API_KEY,
-    temperature=0.0,
-    streaming=False,
-)
 
-# --- Memory ---
-memory = ChatMemoryBuffer.from_defaults(token_limit=4096)
+memory = ChatMemoryBuffer.from_defaults(token_limit=8192)
+today_str = datetime.now().strftime("%B %d, %Y")
+ANON_USER_ID = os.environ.get("ANON_USER_ID", uuid.uuid4().hex)
+
+# # OpenAI for pure function-calling
+# openai_llm = OpenAI(
+#     model="gpt-4o",
+#     api_key=OPENAI_API_KEY,
+#     temperature=0.0,
+#     streaming=False,
+# )
 
 # --- Tools Setup ---
 # DuckDuckGo
@@ -65,6 +83,7 @@ async def _start_browser():
     return await PlaywrightToolSpec.create_async_playwright_browser(headless=True)
 browser = asyncio.get_event_loop().run_until_complete(_start_browser())
 playwright_tool_spec = PlaywrightToolSpec.from_async_browser(browser)
+
 navigate_tool = FunctionTool.from_defaults(
     playwright_tool_spec.navigate_to,
     name="web_navigate",
@@ -88,141 +107,81 @@ def fetch_google_news_rss():
 google_rss_tool = FunctionTool.from_defaults(
     fn=fetch_google_news_rss,
     name="fetch_google_news_rss",
-    description="Get headlines & URLs from Google News RSS."
+    description="Fetch latest headlines and URLs from Google News RSS."
 )
 
 # Serper
-async def fetch_serper(ctx, query):
-    if not SERPER_API_KEY:
-        raise ValueError("SERPER_API_KEY missing")
+async def fetch_serper_news(query: str):
+    if not serper_api_key:
+        raise ValueError("Missing SERPER_API_KEY environment variable")
     url = f"https://google.serper.dev/news?q={query}&tbs=qdr%3Ad"
-    hdr = {"X-API-KEY": SERPER_API_KEY, "Content-Type":"application/json"}
-    async with aiohttp.ClientSession() as s:
-        r = await s.get(url, headers=hdr)
-        r.raise_for_status()
-        return await r.json()
-serper_news_tool = FunctionTool.from_defaults(
-    fetch_serper, name="fetch_news_from_serper", 
-    description="Search today’s news via Serper."
-)
+    headers = {"X-API-KEY": serper_api_key, "Content-Type": "application/json"}
+    async with aiohttp.ClientSession() as session:
+        async with session.get(url, headers=headers) as resp:
+            resp.raise_for_status()
+            return await resp.json()
 
-# --- Agents ---
-# 1. Google News RSS Agent (replaces old google_news_agent)
-google_rss_agent = FunctionAgent(
-    name="google_rss_agent",
-    description="Fetches latest headlines and URLs from Google News RSS feed.",
-    system_prompt="You are an agent that fetches the latest headlines and URLs from the Google News RSS feed.",
-    tools=[google_rss_tool],
-    llm=openai_llm,
-    memory=memory,
-)
-
-# 2. Web Browsing Agent
-web_browsing_agent = ReActAgent(
-    name="web_browsing_agent",
-    description="Fetches Serper URLs, navigates to each link, extracts the text and builds a summary",
-    system_prompt=(
-        "You are a news-content agent. When asked for details on a headline:\n"
-        "1. Call `fetch_news_from_serper(query)` to get JSON with article URLs.\n"
-        "2. For each top URL, call `web_navigate(url)` then `web_extract_text()`.\n"
-        "3. Synthesize those texts into a concise summary."
-    ),
-    tools=[serper_news_tool, navigate_tool, extract_text_tool, extract_links_tool],
-    llm=llm,
-    memory=memory,
-)
-
-# 3. Weather Agent
-weather_agent = ReActAgent(
-    name="weather_agent",
-    description="Answers weather-related questions.",
-    system_prompt="You are a weather agent that provides current weather and forecasts.",
-    tools=[weather_tool, forecast_tool],
-    llm=openai_llm,
-)
-
-# 4. DuckDuckGo Search Agent
-search_agent = ReActAgent(
-    name="search_agent",
-    description="Searches general info using DuckDuckGo.",
-    system_prompt="You are a search agent that uses DuckDuckGo to answer questions.",
-    tools=[search_tool],
-    llm=openai_llm,
+serper_news_tool = FunctionTool.from_defaults(
+    fetch_serper_news,
+    name="fetch_news_from_serper",
+    description="Fetch news articles on a given topic via the Serper API."
 )
 
-router_agent = ReActAgent(
-    name="router_agent",
-    description="Routes queries to the correct specialist agent.",
-    system_prompt=(
-        "You are RouterAgent. "
-        "Given the user query, reply with exactly one name from: "
-        "['google_rss_agent','weather_agent','search_agent','web_browsing_agent']."
-    ),
-    llm=llm,
-    tools=[
-        FunctionTool.from_defaults(
-            fn=lambda ctx, choice: choice,
-            name="choose_agent",
-            description="Return the chosen agent name."
-        )
-    ],
-    can_handoff_to=[
-        "google_rss_agent",
-        "weather_agent",
-        "search_agent",
-        "web_browsing_agent",
-    ],
-)
+# Create the agent workflow
+tools = [
+    duckduckgo_tool,
+    navigate_tool,
+    extract_text_tool,
+    extract_links_tool,
+    weather_tool,
+    forecast_tool,
+    google_rss_tool,
+    serper_news_tool,
+]
+web_agent = AgentWorkflow.from_tools_or_functions(tools, llm=llm)
+ctx = Context(web_agent)
+
+# Async helper to run agent queries
+def run_query_sync(query: str):
+    """Helper to run async agent.run in sync context."""
+    return asyncio.get_event_loop().run_until_complete(
+        web_agent.run(query, ctx=ctx)
+    )
 
-workflow = AgentWorkflow(
-    agents=[router_agent, google_rss_agent, web_browsing_agent, weather_agent, search_agent],
-    root_agent="router_agent"
-)
-ctx = Context(workflow)
-
-# # Sync wrapper
-# async def respond(query: str) -> str:
-#     out = await workflow.run(user_msg=query, ctx=ctx, memory=memory)
-#     return out.response.blocks[0].text
-    
-# # Async response handler for Gradio
-# async def respond_gradio(query, chat_history):
-#     answer = await respond(query)
-#     return chat_history + [[query, answer]]
-
-# New unified respond() function
-async def respond(message, history):
-    out = await workflow.run(user_msg=message, ctx=ctx, memory=memory)
-    answer = out.response.blocks[0].text
-    # Return the full updated history
-    return history + [[message, answer]]
-
-# --- Gradio UI ---
-# with gr.Blocks() as demo:
-#     gr.Markdown("## 🤖 Perspicacity")
-#     gr.Markdown(
-#     "This bot can check the news, tell you the weather, and even browse websites to answer follow-up questions — all powered by a team of tiny AI agents working behind the scenes.  \n\n"
-#     "🧪 Built for fun during the [AI Agents course](https://huggingface.co/learn/agents-course/unit0/introduction) at Hugging Face — it's just a demo to show what agents can do.  \n"
-#     "🙌 Got ideas or improvements? PRs welcome!"
-#     )
-#     chatbot = gr.Chatbot()
-#     txt = gr.Textbox(placeholder="Ask me about news, weather, etc…")
-
-#     txt.submit(respond_gradio, inputs=[txt, chatbot], outputs=chatbot)
-
-# demo.launch()
-with gr.Blocks() as demo:
-    gr.Markdown("## 🗞️ Multi‐Agent News & Weather Chatbot")
+async def run_query(query: str):
+    trace_id = f"agent-run-{uuid.uuid4().hex}"
+    try:
+        with instrumentor.observe(
+            trace_id=trace_id,
+            session_id="web-agent-session",
+            user_id=ANON_USER_ID,
+        ):
+            return await web_agent.run(query, ctx=ctx)
+    finally:
+        instrumentor.flush()
+
+# Gradio interface function
+async def gradio_query(user_input, chat_history=None):
+    chat_history = chat_history or []
+    result = await run_query(user_input)
+    response = result.response
+    chat_history.append((user_input, response))
+    return chat_history, chat_history
+
+# Build and launch Gradio app
+grb = gr.Blocks()
+with grb:
+    gr.Markdown("## Perspicacity")
     gr.Markdown(
         "This bot can check the news, tell you the weather, and even browse websites to answer follow-up questions — all powered by a team of tiny AI agents working behind the scenes.\n\n"
         "🧪 Built for fun during the [AI Agents course](https://huggingface.co/learn/agents-course/unit0/introduction) — it's just a demo to show what agents can do.  \n"
         "🙌 Got ideas or improvements? PRs welcome!  \n\n"
         "👉 _Try asking “What’s the weather in Montreal?” or “What’s in the news today?”_"
     )
+    chatbot = gr.Chatbot()  # conversation UI
+    txt = gr.Textbox(placeholder="Ask me anything...", show_label=False)
+    txt.submit(gradio_query, [txt, chatbot], [chatbot, chatbot])
+    gr.Button("Send").click(gradio_query, [txt, chatbot], [chatbot, chatbot])
 
-    chatbot = gr.Chatbot()
-    txt = gr.Textbox(placeholder="Ask me about news, weather or anything…")
-
-    txt.submit(respond, inputs=[txt, chatbot], outputs=chatbot)
-
-demo.launch()
+if __name__ == "__main__":
+    grb.launch()