Building a KB-Driven Reddit Outreach Dashboard

We built a custom local outreach dashboard to scan Reddit, draft context-rich responses via LLMs based on product knowledge bases, and quickly reply manually. Here is the architecture.

1. The Pain: Reddit's HTTP 403 Blocks

Reddit blocks standard API requests from scripts.

403 Error Blocks

The Fix: We scrape posts via Reddit's public Atom RSS search feeds with a browser User-Agent, bypassing the blocks completely.

2. Interactive CLI & Deduplication

To prevent duplicate replies and spamming:

Deduplication Filter: Automatically hides posts you already skipped or replied to.
Dynamic Feedback: Appends approved/edited responses to a few-shots history file to align future drafts with your tone.

CLI Review Interface

3. Gemini Token Limits & The Local Gemma Transition

Initially, we ran everything through the Gemini API, but we hit the token/rate limits when loading large chunks of subreddit context.

Gemini Token Limit Error

To solve this, we tried running Gemma 2 locally using Ollama (`gemma4:e2b`), which was surprisingly easy to set up.

Timeout Fix: Increased the API connection timeout to 120s to allow the 7.2 GB local model to load into memory.
One-Click Fallback: Added a fallback option to switch to the Gemini Cloud (`gemini-2.5-flash`) if the local model times out.

4. Human-in-the-Loop Tkinter Popup

Selecting `d` (draft) opens a dual-panel popup editor built with `tkinter`:

Top (Read-Only): Displays the original Reddit post for context.
Bottom (Editable): Displays the AI-generated reply.
Save & Done: Copies text to clipboard, logs the few-shot example, and opens the browser thread.

Tkinter Side-by-Side Editor Window