Update app.py

app.py

@@ -16,11 +16,14 @@ logging.basicConfig(level=logging.INFO)
 logging.info('App loading\n\n')
 
 # Import tool from Hub
-image_generation_tool = load_tool("m-ric/text-to-image")
-llm_engine = HfApiEngine("Qwen/Qwen2.5-72B-Instruct")
+hf_token = os.environ.get("HF_TOKEN")
+
+llm_engine = HfApiEngine(model="Qwen/Qwen2.5-72B-Instruct", token=hf_token)
 
 # Initialize the agent with the image generation tool
-agent = ReactCodeAgent(tools=[], llm_engine=llm_engine, additional_authorized_imports=['requests', 'bs4'])
+agent = ReactCodeAgent(
+    tools=[], llm_engine=llm_engine, additional_authorized_imports=['requests', 'bs4', "html5lib"], add_base_tools=True
+)
 
 logging.info('App initialized \n')
 
@@ -29,10 +32,6 @@ app = App(token=os.environ.get("SLACK_BOT_TOKEN"))
 
 assistant = Assistant()
 
-# call LLLM
-def call_llm(query):
-    return agent.run(query)
-
 # This listener is invoked when a human user opened an assistant thread
 @assistant.thread_started
 def start_assistant_thread(say: Say, set_suggested_prompts: SetSuggestedPrompts):
@@ -43,8 +42,8 @@ def start_assistant_thread(say: Say, set_suggested_prompts: SetSuggestedPrompts)
     set_suggested_prompts(
         prompts=[
             # If the suggested prompt is long, you can use {"title": "short one to display", "message": "full prompt"} instead
-           {"title" : "Read the latest Slack engineering block in French", 
-            "message": "Read the latest blog post from Slack blog and translate the post title to French. URL of the blog is https://slack.engineering/"}
+           {"title" : "Summarize latest post from Slack engineering blog", 
+            "message": "Read blog post https://slack.engineering/slack-audit-logs-and-anomalies/ and summarize it in 200 words"}
         ],
     )
 
@@ -60,26 +59,12 @@ def respond_in_assistant_thread(
 ):
     try:
         # Tell the human user the assistant bot acknowledges the request and is working on it
-        set_status("Agent is hard at work...")
+        set_status("is hard at work...")
 
         query = payload['blocks'][0]['elements'][0]['elements'][0]['text']
-
-        logging.info('Query ' + query + '\n')
         
-        # # Collect the conversation history with this user
-        # replies_in_thread = client.conversations_replies(
-        #     channel=context.channel_id,
-        #     ts=context.thread_ts,
-        #     oldest=context.thread_ts,
-        #     limit=10,
-        # )
-        # messages_in_thread: List[Dict[str, str]] = []
-        # for message in replies_in_thread["messages"]:
-        #     role = "user" if message.get("bot_id") is None else "assistant"
-        #     messages_in_thread.append({"role": role, "content": message["text"]})
-
         # Pass the latest prompt and chat history to the LLM (call_llm is your own code)
-        agent_gen = agent.run(task=query, stream=True, url="https://slack.engineering/")
+        agent_gen = agent.run(task=query, stream=True, url="https://slack.engineering/slack-audit-logs-and-anomalies/")
 
         for val in agent_gen:
             if 'final_answer' in val: