Annieyun/clean (#3)

Co-authored-by: Alon Ragoler <alan.ragoler@gmail.com>

Author: annikayun-1

sp26_gke/workflows/gke_dummy_job.py

@@ -1,53 +1,5 @@
-"""
-Dummy GKE workflow job.
 
-Students can replace this module with real agent logic while keeping the same container
-+ Kubernetes deployment plumbing.
-"""
-
-from __future__ import annotations
-
-import json
-import os
-import sys
-import time
-import uuid
-from datetime import UTC, datetime
-
-
-def _now_iso() -> str:
-    return datetime.now(UTC).isoformat()
-
-
-def _log(event: str, **fields: object) -> None:
-    payload = {"ts": _now_iso(), "event": event, **fields}
-    print(json.dumps(payload), flush=True)
-
-
-def run() -> int:
-    run_id = str(uuid.uuid4())
-    loop_count = int(os.getenv("DUMMY_LOOP_COUNT", "5"))
-    sleep_seconds = float(os.getenv("DUMMY_SLEEP_SECONDS", "3"))
-    fail_on_purpose = os.getenv("DUMMY_FAIL", "false").lower() == "true"
-
-    _log(
-        "dummy_job_started",
-        run_id=run_id,
-        loop_count=loop_count,
-        sleep_seconds=sleep_seconds,
-    )
-
-    for step in range(1, loop_count + 1):
-        _log("dummy_job_step", run_id=run_id, step=step, total=loop_count)
-        time.sleep(sleep_seconds)
-
-    if fail_on_purpose:
-        _log("dummy_job_failed", run_id=run_id, reason="DUMMY_FAIL=true")
-        return 1
-
-    _log("dummy_job_completed", run_id=run_id)
-    return 0
 
 
 if __name__ == "__main__":
-    sys.exit(run())
+    sys.exit(run())

sp26_gke/workflows/prompts.py

@@ -8,7 +8,8 @@
 from __future__ import annotations
 
 # ---------------------------------------------------------------------------
-# Node 1 — Research: generate targeted search queries
+# Node 1 — research_topic
+# this node uses Tavily to search for data from X
 # ---------------------------------------------------------------------------
 SEARCH_QUERIES_PROMPT = """\
 You are a social media research assistant. Your job is to generate exactly 3 \
@@ -32,7 +33,8 @@
 """
 
 # ---------------------------------------------------------------------------
-# Node 2 — Analyze: extract sentiment from search results
+# Node 2 — analyze_sentiment
+# this node uses llm of choice (currently openAI, see sentiment_agent.py) to analyze raw results from node 1
 # ---------------------------------------------------------------------------
 SENTIMENT_ANALYSIS_PROMPT = """\
 You are an expert social media sentiment analyst. Below are raw search results \
@@ -78,7 +80,8 @@
 """
 
 # ---------------------------------------------------------------------------
-# Node 3 — Report: generate a polished, human-readable sentiment report
+# Node 3 — generate_report
+# this node uses llm of choice (currently openAI, see sentiment_agent.py) to produce structured sentiment report
 # ---------------------------------------------------------------------------
 REPORT_GENERATION_PROMPT = """\
 You are a senior social media intelligence analyst producing a sentiment \

sp26_gke/workflows/sentiment_agent.py

@@ -1,16 +1,20 @@
 """
-LangGraph sentiment analysis agent for X / social media.
+LangGraph sentiment analysis agent X.
 
-Runs a 3-node pipeline:
-  1. research_topic  — search X/social media via Tavily
-  2. analyze_sentiment — Gemini analyses raw results
-  3. generate_report — Gemini produces a structured sentiment report
+Runs a 3-node Graph API using LangGraph:
+  Node 1. research_topic  — uses Tavily to search X
+  Node 2. analyze_sentiment — LLM analyses raw results
+  Node 3. generate_report — LLM produces a structured sentiment report
 
-Usage (local):
-  GEMINI_API_KEY=... TAVILY_API_KEY=... pixi run sentiment-agent
+Current Notes:
+ - currently using OpenAI but planning to switch to Gemini once we have credits
+ - right now prompt is hard coded (see DEFAULT_TOPIC), will switch to a more usable UI that allows for custom prompts
+ - as of now, topic can be overridden with the SENTIMENT_TOPIC environment variable
+ - currently does not support cronjob
 
-The topic defaults to "latest hot topics in AI" but can be overridden
-with the SENTIMENT_TOPIC environment variable.
+Usage (local):
+  GEMINI_API_KEY=... TAVILY_API_KEY=...
+  pixi run sentiment-agent
 """
 
 from __future__ import annotations