Update app.py

app.py

@@ -1,21 +1,6 @@
 """
 app.py – Enterprise SQL Agent (Gradio + smolagents + MCP)
-
-Provider priority
-──────────────────
-1. OpenAI   → set OPENAI_API_KEY   (override model with OPENAI_MODEL, default = gpt-4o)
-2. Gemini   → set GOOGLE_API_KEY  (override model with GOOGLE_MODEL, default = gemini-pro)
-3. Hugging Face Inference fallback
-     • HF_MODEL_ID   (default = microsoft/Phi-3-mini-4k-instruct)
-     • HF_API_TOKEN  (only if the repo is gated)
-
-File layout
-────────────
-app.py
-mcp_server.py
-connectors/
-    └─ salesforce_connector.py
-requirements.txt
+HubSpot Integration Only
 """
 
 import os, pathlib, json, pprint, gradio as gr
@@ -25,13 +10,13 @@ from smolagents.models import LiteLLMModel, InferenceClientModel
 
 # ───────────────────────── 1.  Choose base LLM ──────────────────────────
 OPENAI_KEY   = os.getenv("OPENAI_API_KEY")
-OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o")          # stable id
+OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o")
 
 GEMINI_KEY   = os.getenv("GOOGLE_API_KEY")
 GEM_MODEL    = os.getenv("GOOGLE_MODEL", "gemini-pro")
 
 HF_MODEL_ID  = os.getenv("HF_MODEL_ID", "microsoft/Phi-3-mini-4k-instruct")
-HF_TOKEN     = os.getenv("HF_API_TOKEN")  # optional
+HF_TOKEN     = os.getenv("HF_API_TOKEN")
 
 if OPENAI_KEY:
     BASE_MODEL = LiteLLMModel(model_id=f"openai/{OPENAI_MODEL}", api_key=OPENAI_KEY)
@@ -50,8 +35,11 @@ SERVER_PATH = pathlib.Path(__file__).with_name("mcp_server.py")
 def respond(message: str, history: list):
     """Prompt → CodeAgent → MCP tools → string reply."""
     params = StdioServerParameters(command="python", args=[str(SERVER_PATH)])
-    with MCPClient(params) as tools:
-        answer = CodeAgent(tools=tools, model=BASE_MODEL).run(message)
+    try:
+        with MCPClient(params) as tools:
+            answer = CodeAgent(tools=tools, model=BASE_MODEL).run(message)
+    except Exception as e:
+        answer = f"Error while querying tools: {e}"
 
     # ensure plain-text output
     if not isinstance(answer, str):