replace local config to use HF UI secret variable for search tool

qa_graph.py

@@ -1,5 +1,3 @@
-# qa_graph.py
-
 from typing import TypedDict
 import re
 from langgraph.graph import StateGraph, START, END
@@ -7,12 +5,12 @@ from tools.calculator_tool import calculator_tool
 from tools.search_tool import search_tool
 from transformers import pipeline
 
-# 1) Define the shape of our state
+# Shape of the state
 class QAState(TypedDict):
     question: str   # incoming question
     answer: str     # to store tool output or synthesized answer
 
-# 2) Use text2text-generation for T5 models like flan-t5
+# Use text2text-generation for llm model
 synthesizer = pipeline(
     "text2text-generation",
     model="google/flan-t5-small",
@@ -23,16 +21,16 @@ synthesizer = pipeline(
     temperature=0.7
 )
 
-# 3) Tool agent: calculator for math, search for other
+# Tool agent: calculator for math, search for other
 def QAAgent(state: QAState) -> QAState:
     q = state["question"].strip()
     if re.fullmatch(r"[0-9\s\+\-\*\/\.\(\)]+", q):
         state["answer"] = calculator_tool.invoke(q)
     else:
-        state["answer"] = search_tool.invoke(q)  # update to `.invoke(q)` only if search_tool is a LangChain tool
+        state["answer"] = search_tool.invoke(q)
     return state
 
-# 4) Synthesis agent to generate final response
+# Synthesis agent to generate final response
 def SynthesisAgent(state: QAState) -> QAState:
     question = state["question"]
     tool_out = state["answer"]
@@ -46,7 +44,7 @@ def SynthesisAgent(state: QAState) -> QAState:
     state["answer"] = completion
     return state
 
-# 5) Build the graph: START -> QAAgent -> SynthesisAgent -> END
+# Build the graph
 builder = StateGraph(QAState)
 builder.set_entry_point("QAAgent")
 builder.add_node("QAAgent", QAAgent)
@@ -58,7 +56,7 @@ builder.add_edge("SynthesisAgent", END)
 
 graph = builder.compile()
 
-# 6) Local testing
+# Local testing
 if __name__ == "__main__":
     # Math example
     s1: QAState = {"question": "2 + 2", "answer": ""}

tools/search_tool.py

@@ -1,6 +1,8 @@
 from tavily import TavilyClient
 from langchain.tools import tool
-from config import TAVILY_API_KEY
+# from config import TAVILY_API_KEY
+import os
+TAVILY_API_KEY = os.getenv("TAVILY_API_KEY")
 
 class SearchTool:
     def __init__(self, api_key: str):
@@ -8,16 +10,16 @@ class SearchTool:
 
     def search(self, query: str):
         response = self.client.search(query)
-        # Extract a string summary of results (you can adapt this as needed)
+        # Extract a string summary of results
         results = response.get("results", [])
         if not results:
             return "No results found."
-        # For simplicity, join first 3 results' titles or snippets
+        # For simplicity, joining first 3 results' titles or snippets
         summaries = [res.get("title", "") or res.get("snippet", "") for res in results[:3]]
         return " | ".join(summaries)
 
 search_tool_instance = SearchTool(api_key=TAVILY_API_KEY)
 
-@tool(description="Use this tool to search for information on the web using Tavily API and return a summary of results.")
+@tool(description="Tool to search for information on the web using Tavily API and return a summary of results.")
 def search_tool(query: str) -> str:
     return search_tool_instance.search(query)