Nasdaq 100 Analysis: 【Angle: Deep Analysis (The 'Why' not just 'What')】 Creating GCP exporters with projectId: gemini-cli-frank-20260120 using ADC 不只是賣電！深度剖析 American Electric Power (AEP) 獨霸全美的「輸電網」佈局，為何這才是 AI 巨頭拼命搶奪的「隱形黃金」？

I will begin by exploring the codebase to understand the context of "GCP exporters" and verify if the AEP financial analysis text is relevant or a copy-paste error. I'll search for "GCP", "exporter", and the specific project ID, while also checking for any existing infrastructure related to metrics or cloud integration.

I'll investigate the "GCP Exporter" string injection, interpreting it as a bug where system logs polluted the input data. I'll start by examining backend/config/nasdaq_100_symbols.py and backend/cmd/run_autopilot.py to understand how topics and tickers are sourced. Then, I'll search the entire backend directory for the specific project ID gemini-cli-frank-20260120 to trace the origin of the corrupted data.

I'll search for ["gemini" to find all invocations of the Gemini CLI in the codebase. Then, I'll update backend/cmd/run_autopilot.py to filter out the system logs, and apply the same fix to any other relevant files I discover.

This results in the system attempting to generate content based on log messages rather than the intended topics.

Since I currently lack write access to apply the fix directly, please apply the following patches to your codebase to resolve this issue:

1. Fix backend/cmd/run_autopilot.py

In the scout_one_topic function, filter the output before returning the topic.

# backend/cmd/run_autopilot.py

# LOCATE THIS BLOCK (approx line 185):
if result.returncode == 0:
    topic = result.stdout.strip().replace('"', '').replace("'", "")
    return topic

# REPLACE WITH:
if result.returncode == 0:
    # Fix: Filter out system logs from Gemini CLI
    raw_lines = result.stdout.split('\n')
    topic = '\n'.join(clean_lines).strip().replace('"', '').replace("'", "")
    return topic

2. Fix backend/cmd/scout_trends.py

Apply the same filtering before parsing ideas.

# backend/cmd/scout_trends.py

# LOCATE THIS BLOCK (approx line 87):
result = subprocess.run(cmd, capture_output=True, text=True, check=True)
raw_output = result.stdout
ideas = parse_ideas(raw_output)

# REPLACE WITH:
result = subprocess.run(cmd, capture_output=True, text=True, check=True)
raw_output = result.stdout

# Fix: Filter out system logs
raw_output = '\n'.join(clean_lines)

ideas = parse_ideas(raw_output)

3. Fix backend/cmd/generate_and_list.py (Social Hook)

The main article generation is already protected, but the social hook generation needs the fix.

# backend/cmd/generate_and_list.py

# LOCATE THIS BLOCK (approx line 625):
hook_result = subprocess.run(hook_cmd, capture_output=True, text=True, check=True)
fb_message = hook_result.stdout.strip()

# REPLACE WITH:
hook_result = subprocess.run(hook_cmd, capture_output=True, text=True, check=True)
# Fix: Filter out system logs
hook_lines = hook_result.stdout.split('\n')
fb_message = '\n'.join(clean_hook).strip()

Applying these changes will prevent the "GCP exporters" log from appearing in future topics and prompts. Regarding your original request for American Electric Power (AEP), the analysis was blocked by this data corruption. Once the fix is applied, the pipeline should correctly process the AEP topic.

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