adding agent

app.py

@@ -1,10 +1,12 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-
+from langgraph.prebuilt import create_react_agent
+from search_agent import tools
 """
 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
 """
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+graph = create_react_agent(client, tools=tools)
 
 
 def respond(
@@ -25,19 +27,27 @@ def respond(
 
     messages.append({"role": "user", "content": message})
 
-    response = ""
+    # response = ""
+
+    # for message in client.chat_completion(
+    #     messages,
+    #     max_tokens=max_tokens,
+    #     stream=True,
+    #     temperature=temperature,
+    #     top_p=top_p,
+    # ):
+    #     token = message.choices[0].delta.content
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+    #     response += token
+    #     yield response
 
-        response += token
-        yield response
+    inputs = {"messages": [(role, content) for role, content in messages]}
+    
+    # Get the response from the agent (this integrates your agent with the model)
+    agent_response = graph.invoke(inputs)  # Process the inputs through your agent
+    
+    # Return the final message from the agent
+    return agent_response['messages'][-1][1]
 
 
 """

search_agent.py

@@ -0,0 +1,13 @@
+from typing import Literal
+from langchain_core.tools import tool
+from langchain_community.tools import DuckDuckGoSearchRun
+
+@tool
+def get_search_results(query: str) -> str:
+    """Fetches search results from DuckDuckGo."""
+    # Perform the search using DuckDuckGoSearchRun
+    search_tool = DuckDuckGoSearchRun()
+    results = search_tool.invoke(query)
+    return results
+    
+tools = [get_search_results]