Update app.py

app.py

@@ -1,11 +1,13 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+from fastmcp import FastMCPClient
+import os
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
+# Set up inference client (LLM)
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+# Set up FastMCP client (replace with your actual MCP server URL)
+mcp = FastMCPClient("Jobicy Remote Jobs Agent", url="https://oppaai-job-search-mcp-server.hf.space/gradio_api/mcp/sse")
 
 def respond(
     message,
@@ -25,8 +27,27 @@ def respond(
 
     messages.append({"role": "user", "content": message})
 
-    response = ""
+    # Tool invocation keyword check (e.g., "search jobs for Python in Canada")
+    if "search jobs" in message.lower():
+        # Simple NLP parse: extract keyword, country, industry
+        # (You can improve this with spaCy or regex later)
+        keyword = message.split("for")[-1].strip().split(" in ")[0].strip()
+        country = message.split(" in ")[-1].strip() if " in " in message else ""
+        res = mcp.call_tool("search_jobs", inputs={"keyword": keyword, "country": country, "limit": 5})
+
+        if "error" in res:
+            return f"❌ {res['error']}"
+        if not res.get("jobs"):
+            return "No jobs found with those filters."
 
+        job_lines = [
+            f"**{j['title']}** at {j['company']} ({j['location']})\n{j['salary']}\nPosted: {j['pubDate']}\n[Apply Here]({j['url']})"
+            for j in res["jobs"]
+        ]
+        return "\n\n---\n\n".join(job_lines)
+
+    # Fallback to LLM
+    response = ""
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -34,31 +55,20 @@ def respond(
         temperature=temperature,
         top_p=top_p,
     ):
-        token = message.choices[0].delta.content
-
+        token = message.choices[0].delta.content or ""
         response += token
         yield response
 
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Textbox(value="You are a friendly assistant who can also help find remote jobs.", label="System message"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
     ],
+    title="Job Search Assistant Chatbot"
 )
 
-
 if __name__ == "__main__":
     demo.launch()