Update app.py

app.py

@@ -1,37 +1,49 @@
-import os
+import re
 import gradio as gr
-from smolagents import MCPClient, InferenceClientModel, CodeAgent
-
-# Your MCP server URL (replace with your actual HF space MCP endpoint)
-MCP_URL = "https://oppaai-job-search-mcp-server.hf.space/gradio_api/mcp/sse"
-
-# Initialize MCP client to connect to your MCP server
-mcp_client = MCPClient({"url": MCP_URL, "transport": "streamable-http"})
-
-# Fetch available tools from MCP server
-tools = mcp_client.get_tools()
+from smolagents import Agent
+from smolagents.mcp import MCPServerHTTP
+from smolagents.models import HuggingFaceModel
+from smolagents.providers import HuggingFaceProvider
+
+# MCP Server SSE URL
+SSE_URL = "https://oppaai-job-search-mcp-server.hf.space/gradio_api/mcp/sse"
+server = MCPServerHTTP(url=SSE_URL)
+
+# Use HF Qwen3-8B model from Hugging Face Hub
+hf_model = HuggingFaceModel(
+    model_name="Qwen/Qwen-3-8B",  # change this if you have exact repo name or path
+    provider=HuggingFaceProvider(
+        api_token="HF_TOKEN"  # put your HF token here if required
+    )
+)
 
-# Initialize your LLM model from Hugging Face (requires HF token for private/protected models)
-llm_model = InferenceClientModel(
-    model_id="HuggingFaceH4/zephyr-7b-beta",
-    token=os.getenv("HUGGINGFACE_TOKEN"),  # Set this environment variable if needed
+# Create Agent with MCP Server
+agent = Agent(
+    model=hf_model,
+    mcp_servers=[server],
+    instructions="""
+    Your name is Jobcy. You are an AI assistant designed to help users to find remote jobs by searching through job listings from various sources, including the Jobicy API and other platforms.
+    You will list the job listings in a structured format, including the job title, company, location, and the google search link.
+    """,
+    stream=False
 )
 
-# Create an agent that uses the tools and the LLM
-agent = CodeAgent(tools=tools, model=llm_model, stream_outputs=True)
+def chat_with_agent(user_input, history):
+    history = history or []
+    history.append(("user", user_input))
 
+    result = agent.run(user_input)
+    cleaned_output = re.sub(r"<think>.*?</think>", "", result.output, flags=re.DOTALL).strip()
 
-def respond(message, history):
-    # Agent processes the input message, uses tools if needed, else LLM
-    reply = agent.run(message)
-    return reply
+    history.append(("agent", cleaned_output))
+    return history, history
 
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    user_input = gr.Textbox(placeholder="Ask Jobcy about remote jobs or anything else...", label="Your Message")
+    state = gr.State([])
 
-demo = gr.ChatInterface(
-    fn=respond,
-    title="Job Search Assistant (Agent)",
-    description="Ask me about job listings or general questions — I’ll use the job search tool when needed!",
-)
+    user_input.submit(chat_with_agent, inputs=[user_input, state], outputs=[chatbot, state])
 
-if __name__ == "__main__":
-    demo.launch()
+demo.title = "Jobcy Remote Job Search Assistant"
+demo.launch()