Update app.py

app.py

@@ -9,61 +9,27 @@ from langchain_core.prompts import PromptTemplate
 from langchain_community.tools import DuckDuckGoSearchRun
 from langchain_community.llms import HuggingFaceHub
 from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
+from agent import alfred
 
-HUGGINGFACEHUB_API_TOKEN = os.getenv("HF_TOKEN")
+#HUGGINGFACEHUB_API_TOKEN = os.getenv("HF_TOKEN")
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
-# Prompt
-template = '''Answer the following questions as best you can. You have access to the following tools:
-
-{tools}
-
-Use the following format:
-
-Question: the input question you must answer
-Thought: you should always think about what to do
-Action: the action to take, should be one of [{tool_names}]
-Action Input: the input to the action
-Observation: the result of the action
-... (this Thought/Action/Action Input/Observation can repeat N times)
-Thought: I now know the final answer
-Final Answer: the final answer to the original input question
-
-Begin!
-Question: {input}
-Thought:{agent_scratchpad}'''
-prompt = PromptTemplate.from_template(template)
-
-# Tools
-search_tool = DuckDuckGoSearchRun()
-tools = [search_tool]
-
-# LLM
-llm = HuggingFaceEndpoint(
-    repo_id="deepseek-ai/DeepSeek-R1-0528",
-    task="text-generation",
-    provider="hyperbolic",  # set your provider here
-    # provider="nebius",
-    # provider="together",
-)
-model = ChatHuggingFace(llm=llm)
 
 class BasicAgent:
     def __init__(self):
-        self.agent = create_react_agent(model, tools, prompt)
-        self.agent_executor = AgentExecutor(agent = self.agent, tools = tools)
-    def __call__(self, question: str) -> str:
-        response = self.agent_executor.invoke(
-            {
-            "input": question
-            }
-        )
-        return response
+        self.agent = alfred
+    async def __call__(self, question: str) -> str:
+        state_dict = await alfred.ainvoke({"messages": [HumanMessage(content = question)]})
+        response = state_dict["messages"][-1]
+        try:
+            return response.content
+        except:
+            return "Sorry, I can't answer to this question."
 
-def run_and_submit_all( profile: gr.OAuthProfile | None):
+async def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     and displays the results.
@@ -84,7 +50,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
-        agent = BasicAgent()
+        agent = await BasicAgent()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None