Update app.py

app.py

@@ -1,12 +1,21 @@
 """
 app.py – Enterprise SQL Agent (Gradio + smolagents + MCP)
 
-Secrets / ENV
-─────────────
-OPENAI_API_KEY   → calls OpenAI  (default model gpt-4o, override via OPENAI_MODEL)
-GOOGLE_API_KEY   → calls Gemini (default model gemini-pro, override via GOOGLE_MODEL)
-HF_MODEL_ID      → Hugging Face chat-completion model (fallback if no keys)
-HF_API_TOKEN     → token for gated HF repo (optional)
+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
 """
 
 import os, pathlib, json, pprint, gradio as gr
@@ -14,42 +23,37 @@ from mcp import StdioServerParameters
 from smolagents import MCPClient, CodeAgent
 from smolagents.models import LiteLLMModel, InferenceClientModel
 
-# ─── 1. Pick the base LLM ───────────────────────────────────────────────
+# ───────────────────────── 1.  Choose base LLM ──────────────────────────
 OPENAI_KEY   = os.getenv("OPENAI_API_KEY")
-OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o")
+OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o")          # stable id
 
 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")  # only if the repo is gated
+HF_TOKEN     = os.getenv("HF_API_TOKEN")  # optional
 
 if OPENAI_KEY:
-    BASE_MODEL = LiteLLMModel(model_id=f"openai/{OPENAI_MODEL}",
-                              api_key=OPENAI_KEY)
-    ACTIVE = f"OpenAI · {OPENAI_MODEL}"
+    BASE_MODEL = LiteLLMModel(model_id=f"openai/{OPENAI_MODEL}", api_key=OPENAI_KEY)
+    ACTIVE     = f"OpenAI · {OPENAI_MODEL}"
 elif GEMINI_KEY:
-    BASE_MODEL = LiteLLMModel(model_id=f"google/{GEM_MODEL}",
-                              api_key=GEMINI_KEY)
-    ACTIVE = f"Gemini · {GEM_MODEL}"
+    BASE_MODEL = LiteLLMModel(model_id=f"google/{GEM_MODEL}", api_key=GEMINI_KEY)
+    ACTIVE     = f"Gemini · {GEM_MODEL}"
 else:
-    BASE_MODEL = InferenceClientModel(model_id=HF_MODEL_ID,
-                                      hf_api_token=HF_TOKEN,
-                                      timeout=90)
-    ACTIVE = f"Hugging Face · {HF_MODEL_ID}"
+    BASE_MODEL = InferenceClientModel(model_id=HF_MODEL_ID, hf_api_token=HF_TOKEN, timeout=90)
+    ACTIVE     = f"Hugging Face · {HF_MODEL_ID}"
 
-# ─── 2. Path to MCP server ──────────────────────────────────────────────
+# ───────────────────────── 2.  MCP server path ──────────────────────────
 SERVER_PATH = pathlib.Path(__file__).with_name("mcp_server.py")
 
-# ─── 3. Chat callback ───────────────────────────────────────────────────
+# ───────────────────────── 3.  Chat callback ────────────────────────────
 def respond(message: str, history: list):
-    """Prompt → CodeAgent → MCP tools → safe string reply."""
+    """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)
 
-    # Always stringify for Gradio
+    # ensure plain-text output
     if not isinstance(answer, str):
         try:
             answer = json.dumps(answer, indent=2, ensure_ascii=False)
@@ -62,14 +66,16 @@ def respond(message: str, history: list):
     ]
     return history, history
 
-# ─── 4. Build UI ────────────────────────────────────────────────────────
+# ───────────────────────── 4.  Gradio UI ────────────────────────────────
 with gr.Blocks(title="Enterprise SQL Agent") as demo:
     state = gr.State([])
-    gr.Markdown("## 🏢 Enterprise SQL Agent — ask questions about your data")
+    gr.Markdown("## 🏢 Enterprise SQL Agent — query your data with natural language")
 
     chat = gr.Chatbot(type="messages", label="Conversation")
-    box  = gr.Textbox(placeholder="e.g. Who are my inactive Northeast customers?",
-                      show_label=False)
+    box  = gr.Textbox(
+        placeholder="e.g. Who are my inactive Northeast customers?",
+        show_label=False,
+    )
     box.submit(respond, [box, state], [chat, state])
 
     with gr.Accordion("Example prompts", open=False):
@@ -79,7 +85,7 @@ with gr.Blocks(title="Enterprise SQL Agent") as demo:
             "* Draft re-engagement emails for inactive accounts."
         )
 
-    gr.Markdown(f"_Powered by MCP + smolagents + Gradio • Active model → **{ACTIVE}**_")
+    gr.Markdown(f"_Powered by MCP · smolagents · Gradio  •  Active model → **{ACTIVE}**_")
 
 if __name__ == "__main__":
     demo.launch()