Add Slack messaging

indexing.py

@@ -12,13 +12,15 @@ import langchain_openai
 import langchain_weaviate
 import langgraph.graph
 
+import slack
 import weaviate
 from hn import HackerNewsClient, Story
 from scrape import JinaScraper
 
 NUM_STORIES = 20
-USER_PREFERENCES = []
-ENABLE_MLFLOW_TRACING = False  # Set to True if you want to use MLflow for tracing
+USER_PREFERENCES = ["Machine Learning", "Linux", "Open-Source"]
+ENABLE_SLACK = False  # Send updates to Slack, need to set SLACK_BOT_TOKEN env var
+ENABLE_MLFLOW_TRACING = False  # Use MLflow (at http://localhost:5000) for tracing
 
 
 llm = langchain.chat_models.init_chat_model(
@@ -100,13 +102,13 @@ def generate(state: State):
     return {"answer": response.content}
 
 
-def run_query(preferences: Iterable[str]):
+def run_query(preferences: Iterable[str]) -> str:
     graph_builder = langgraph.graph.StateGraph(State).add_sequence([retrieve, generate])
     graph_builder.add_edge(langgraph.graph.START, "retrieve")
     graph = graph_builder.compile()
 
     response = graph.invoke(State(preferences=preferences, context=[], answer=""))
-    print(response["answer"])
+    return response["answer"]
 
 
 def get_existing_story_ids() -> set[str]:
@@ -233,7 +235,10 @@ async def main():
         print("No new stories to process")
 
     # 4. Query
-    run_query(USER_PREFERENCES)
+    answer = run_query(USER_PREFERENCES)
+    print(answer)
+    if ENABLE_SLACK:
+        slack.send_message(channel="#ragpull-demo", text=answer)
 
 
 if __name__ == "__main__":