- Uses Reddit API (via reddit) to fetch posts, comments & inbox messages.
- Stores posts, comments & direct messages in a PostgreSQL database.
- Embedding Pipeline: Converts text elements using the
nvidia/llama-nemotron-embed-1b-v2model. The output embeddings are dynamically sliced to 1024 dimensions (via Matryoshka Representation Learning) and L2-normalized to optimize pgvector search efficiency. - SHA-256 Wiki Cache: Pre-computes and caches wiki static files (
assets/redditPosts/) on startup. It performs SHA-256 change validation to detect modified files, and prunes cache keys for deleted files. - VLM Media Descriptions: Describes images (using
meta/llama-3.2-90b-vision-instruct/ Llama-3.2-11b) and videos (usingqwen/qwen3.5-397b-a17b/ Llama-3.2-11b fallback) in posts and crossposts at storage time or dynamically during RAG context synthesis. - Uses Tavily Search API to fetch live internet comparison data when user queries ask for comparisons or alternative college recommendations.
- Uses NVIDIA API (
mistralai/mistral-medium-3.5-128b/ Llama-3.1-70b fallback) to generate answers utilizing matching database results, wiki context, and live internet search data. - NVIDIA returns an action (
reply | query_user | reply_with_gif | dont_reply), where the bot can either reply, fetch a user's profile overview context, reply with a Giphy GIF, or skip.
The bot features a structured, color-coded logging system via the chalk library, separating operational concerns visually:
[BOT](Green) — App startup, wiki cache pre-computation, and scheduler.[DATABASE](Blue) — Table creation, schema migrations, and indexing operations.[STORE](Green) — Ingest pipeline actions (database inserts and VLM updates).[REDDIT](Red) — Reddit REST client requests, limits, and composition.[RAG]/[RAG Boost]/[RAG Cache](Cyan) — Dense retriever details, Matryoshka slicing, keyword matches, and wiki hits.[TAVILY SEARCH]/[VISION]/[MEDIA](Yellow) — Search engine interactions, frame extractions, and vision describer pipelines.[POST]/[COMMENT]/[DM](Magenta/Cyan) — Input events, model prompts, and JSON response actions.[ERROR](Red) — Exceptions, model fallbacks, and schema validation failures.
erDiagram
POSTS {
varchar id PK
text title
text selftext
varchar author
int8 created_utc
text url
varchar post_hint
text video_url
text image_description
vector embedding
}
COMMENTS {
varchar id PK
varchar post_id FK
varchar parent_id
varchar author
text body
int8 created_utc
vector embedding
}
DMS {
varchar id PK
varchar sender
varchar recipient
text body
int8 created_utc
vector embedding
}
POSTS ||--o{ COMMENTS : "has"
---
config:
layout: dagre
---
flowchart TD
subgraph s1["newPostProcessor()"]
n3(["Semantic & keyword search context"])
n12(["Check comparison intent: Fetch live internet context"])
n4(["Requests NVIDIA API with post details, relevant DB context & live internet context"])
n5(["NVIDIA may request user's recent posts/comments for context"])
n6(["Returns reply action, reply text, or gif search query"])
end
A(["Fetch newest 5 posts & 20 comments"]) --> n1(["Check for post ids not in seenPostIds (from database)"])
n1 -- "Pushes new posts to newPostProcessor([...post])" --> B(["Stores the post in database"])
B --> s1
n3 --> n12 --> n4
n4 --> n5 & n6
n5 --> n4
s1 -- "action: reply" --> n7(["Reply to the post using Reddit API"])
s1 -- "action: reply_with_gif" --> n11(["Query Giphy, evaluate still image embeddings & reply with GIF"])
s1 -- "action: dont_reply" --> n8(["Ignore post"])
style s1 fill:#4d4d4d,stroke:#ffffff,stroke-width:1px
---
config:
layout: dagre
---
flowchart TD
subgraph s1["newCommentProcessor()"]
n3(["Semantic & keyword search context"])
n12(["Check comparison intent: Fetch live internet context"])
n4(["Requests NVIDIA API with comment thread, relevant DB context & live internet context"])
n5(["NVIDIA may request user's recent posts/comments for context"])
n6(["Returns reply action, reply text, or gif search query"])
end
A(["Fetch newest 5 posts & 20 comments"]) --> n1(["Check for comment ids not in seenCommentIds (from database)"])
n1 -- "Pushes new comments to newCommentProcessor([...comment])" --> B(["Stores the comment in database"])
B --> n9(["Check: Mentioned u/AskNITJ OR replying to u/AskNITJ OR user is not the bot"])
n3 --> n12 --> n4
n4 --> n5 & n6
n5 --> n4
s1 -- "action: reply" --> n7(["Reply to the comment using Reddit API"])
s1 -- "action: reply_with_gif" --> n11(["Query Giphy, evaluate still image embeddings & reply with GIF"])
s1 -- "action: dont_reply" --> n8(["Ignore comment"])
n9 -- "Passes validation" --> s1
n9 --> n8
style s1 fill:#4d4d4d,stroke:#ffffff,stroke-width:1px
---
config:
layout: dagre
---
flowchart TD
subgraph s1["newDMProcessor()"]
n3(["Semantic & keyword search context"])
n12(["Check comparison intent: Fetch live internet context"])
n4(["Requests NVIDIA API with message, recent chat history, relevant DB context & live internet context"])
n5(["NVIDIA may request user's recent posts/comments for context"])
n6(["Returns reply action, reply text, or gif search query"])
end
A(["Fetch newest 5 DMs"]) --> n1(["Check for message ids not in seenMessageIds (from database)"])
n1 --> n10(["Stores the messages in database"])
n10 --> B(["Fetch recent DM history from database"])
n3 --> n12 --> n4
n4 --> n5 & n6
n5 --> n4
s1 -- "action: reply" --> n7(["Reply to the message using Reddit API & Save DB"])
s1 -- "action: reply_with_gif" --> n11(["Query Giphy, evaluate still image embeddings & reply with GIF & Save DB"])
s1 -- "action: dont_reply" --> n8(["Ignore DM"])
B -- "Pushes grouped DMs to newDMProcessor([...message])" --> s1
style s1 fill:#4d4d4d,stroke:#ffffff,stroke-width:1px
- Fork this repository.
- Pick an open issue.
- Create your branch and make improvements.
- Submit a Pull Request (PR).
Happy hacking, and thank you for supporting open source ❤️