ML-based recommendation feed for Bluesky posts

Get webserver up and running

+922 -39
+4
pyproject.toml
··· 6 6 requires-python = ">=3.9" 7 7 dependencies = [ 8 8 "atproto>=0.0.61", 9 + "faiss-cpu>=1.12.0", 10 + "fastapi[standard]>=0.119.0", 11 + "httpx>=0.28.1", 12 + "jinja2>=3.1.6", 9 13 "lightning>=2.5.5", 10 14 "pandas>=2.3.1", 11 15 "polars>=1.33.1",
+148
scripts/serving/main.py
··· 1 + from argparse import ArgumentParser 2 + import json 3 + import os 4 + from typing import List, Union 5 + 6 + from atproto import AsyncIdResolver 7 + import faiss 8 + from fastapi import FastAPI, HTTPException 9 + from fastapi.responses import HTMLResponse 10 + from jinja2 import Template 11 + import numpy as np 12 + import httpx 13 + import torch 14 + 15 + from scripts.utils import get_logger 16 + from scripts.training.models import FollowEmbedModule 17 + 18 + logger = get_logger(__name__) 19 + 20 + BSKY_URL = "https://public.api.bsky.app" 21 + 22 + for var in ["CHECKPOINT_PATH", "DID_ID_MAP_PATH"]: 23 + if var not in os.environ: 24 + raise ValueError(f"Missing required env var: {var}") 25 + checkpoint_path = os.environ["CHECKPOINT_PATH"] 26 + did_id_map_path = os.environ["DID_ID_MAP_PATH"] 27 + 28 + logger.info("Loading model from checkpoint...") 29 + model = FollowEmbedModule.load_from_checkpoint(checkpoint_path, device="cpu") 30 + source_embed = model.source_embed.embed.weight.cpu().detach().to(torch.float16).numpy() 31 + target_embed = model.target_embed.embed.weight.cpu().detach().to(torch.float16).numpy() 32 + del model # Manual memory mgmt is cool 33 + with open(did_id_map_path, "r") as in_file: 34 + did_id_map: dict[str, int] = json.load(in_file) 35 + 36 + id_did_map = {value: key for key, value in did_id_map.items()} 37 + 38 + logger.info("Building index...") 39 + source_index = faiss.IndexHNSWFlat(target_embed.shape[1], 32) 40 + source_index.add(target_embed) # type: ignore 41 + logger.info("Index constructed") 42 + 43 + 44 + async def get_follows(did: str) -> List[str]: 45 + follows = [] 46 + try: 47 + async with httpx.AsyncClient() as client: 48 + data = await client.get( 49 + BSKY_URL + "/xrpc/app.bsky.graph.getFollows", 50 + params={"actor": did, "limit": 100}, 51 + headers={"Content-Type": "application/json"}, 52 + ) 53 + data = data.json() 54 + for follow in data["follows"]: 55 + follows.append(follow["did"]) 56 + except Exception as e: 57 + raise e 58 + 59 + if "cursor" not in data: 60 + return follows 61 + 62 + # Limit to 2000 follows per account 63 + while data["cursor"] and len(follows) < 2000: 64 + try: 65 + async with httpx.AsyncClient() as client: 66 + data = await client.get( 67 + BSKY_URL + "/xrpc/app.bsky.graph.getFollows", 68 + params={"actor": did, "limit": 100, "cursor": data["cursor"]}, 69 + headers={"Content-Type": "application/json"}, 70 + ) 71 + data = data.json() 72 + for follow in data["follows"]: 73 + follows.append(follow["did"]) 74 + 75 + if "cursor" not in data: 76 + break 77 + except Exception as e: 78 + raise e 79 + 80 + return follows 81 + 82 + 83 + async def get_profiles(dids: list[str]): 84 + profiles = [] 85 + try: 86 + async with httpx.AsyncClient() as client: 87 + data = await client.get( 88 + BSKY_URL + "/xrpc/app.bsky.actor.getProfiles", 89 + params={"actors": dids}, 90 + headers={"Content-Type": "application/json"}, 91 + ) 92 + data = data.json() 93 + for profile in data["profiles"]: 94 + profiles.append(profile) 95 + return profiles 96 + except Exception as e: 97 + raise e 98 + 99 + 100 + async def get_recs(did: str): 101 + follows = await get_follows(did) 102 + logger.info(f"Number of follows: {len(follows)}") 103 + 104 + user_id = did_id_map[did] 105 + user_vec = np.expand_dims(source_embed[user_id, :], axis=0) # (1,256) 106 + 107 + _, neighbors = source_index.search(user_vec, 25) # type: ignore 108 + neigh_dids: list[str] = [] 109 + for neigh in neighbors[0]: 110 + neigh_did: str = id_did_map[neigh.item()] 111 + if neigh_did not in follows: 112 + neigh_dids.append(neigh_did) 113 + 114 + profiles = await get_profiles(neigh_dids) 115 + return profiles 116 + 117 + 118 + app = FastAPI() 119 + 120 + with open( 121 + os.path.join(os.path.dirname(os.path.abspath(__file__)), "page.html"), "r" 122 + ) as template_file: 123 + template_str = template_file.read() 124 + template = Template(template_str) 125 + 126 + 127 + @app.get("/") 128 + async def render_page(query: Union[str, None] = None): 129 + logger.info(f"Received query: {query}") 130 + if not query: 131 + result = template.render(profiles=[], query="") 132 + return HTMLResponse(content=result) 133 + 134 + # If it doesn't start with 'did' resolve as handle 135 + if query[:4] == "did": 136 + did = query 137 + else: 138 + resolver = AsyncIdResolver() 139 + did = await resolver.handle.resolve(query) 140 + if did is None: 141 + return HTTPException(status_code=500, detail="Couldn't resolve handle") 142 + 143 + recs = await get_recs(did) 144 + for rec in recs: 145 + if "avatar" in rec: 146 + rec["avatar"] = rec["avatar"].replace("avatar", "avatar_thumbnail") 147 + result = template.render(profiles=recs, query=query) 148 + return HTMLResponse(content=result)
+179
scripts/serving/page.html
··· 1 + <!DOCTYPE html> 2 + <head> 3 + <meta charset="UTF-8"> 4 + <meta name="viewport" content="width=device-width, initial-scale=1.0"> 5 + <title>Bluesky Recommendations</title> 6 + <style> 7 + * { 8 + margin: 0; 9 + padding: 0; 10 + box-sizing: border-box; 11 + } 12 + 13 + body { 14 + font-family: 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, sans-serif; 15 + background: #f8f5d7; 16 + min-height: 100vh; 17 + padding: 40px 20px; 18 + } 19 + 20 + .container { 21 + max-width: 750px; 22 + margin: 0 auto; 23 + padding-top: 80px; 24 + } 25 + 26 + .list-contianer { 27 + max-width: 500px; 28 + } 29 + 30 + h1 { 31 + color: rgb(0, 0, 0); 32 + text-align: center; 33 + margin-bottom: 40px; 34 + font-size: 2.5em; 35 + } 36 + 37 + .profiles-grid { 38 + display: flex; 39 + gap: 24px; 40 + padding: 12px; 41 + } 42 + 43 + .profile-card { 44 + background: rgb(255, 254, 241); 45 + border-radius: 10px; 46 + padding: 24px; 47 + margin: 15px 10px; 48 + box-shadow: 0 5px 5px rgba(0,0,0,0.2); 49 + transition: transform 0.3s ease, box-shadow 0.3s ease; 50 + cursor: pointer; 51 + display: flex; 52 + align-items: center; 53 + } 54 + 55 + .profile-card:hover { 56 + transform: scale(1.02); 57 + box-shadow: 0 5px 5px rgba(0,0,0,0.3); 58 + } 59 + 60 + .profile-image { 61 + max-width: 80px; 62 + max-height: 80px; 63 + aspect-ratio: 1; 64 + border-radius: 55px; 65 + object-fit: cover; 66 + } 67 + 68 + .profile-info { 69 + text-align: left; 70 + margin-left: 25px; 71 + } 72 + 73 + .display-name { 74 + font-size: 1.4em; 75 + font-weight: 600; 76 + color: #2d3748; 77 + margin-bottom: 2px; 78 + } 79 + 80 + .did { 81 + font-size: 0.9em; 82 + color: #718096; 83 + font-family: 'Courier New', monospace; 84 + background: #f7fafc; 85 + padding: 6px 12px; 86 + margin-bottom: 4px; 87 + border-radius: 8px; 88 + word-break: break-all; 89 + width: fit-content; 90 + } 91 + .description { 92 + font-size: 0.95em; 93 + color: #4a5568; 94 + line-height: 1.5; 95 + margin-bottom: 12px; 96 + padding-left: 6px; 97 + } 98 + 99 + .search-container { 100 + margin: 0 auto 30px; 101 + padding: 0 10px; 102 + } 103 + .search-container form { 104 + display: flex; 105 + gap: 10px; 106 + width: 100%; 107 + } 108 + .search-input { 109 + flex: 1; 110 + padding: 12px 16px; 111 + font-size: 1em; 112 + border: 2px solid #e2e8f0; 113 + border-radius: 8px; 114 + background: rgb(255, 254, 241); 115 + font-family: 'Courier New', monospace; 116 + } 117 + .search-input:focus { 118 + outline: none; 119 + border-color: #667eea; 120 + } 121 + .search-button { 122 + padding: 12px 24px; 123 + font-size: 1em; 124 + font-weight: 600; 125 + background: #667eea; 126 + color: white; 127 + border: none; 128 + border-radius: 8px; 129 + cursor: pointer; 130 + transition: background 0.3s ease; 131 + } 132 + .search-button:hover { 133 + background: #5568d3; 134 + } 135 + 136 + .blurb { 137 + text-align: center; 138 + margin-bottom: 10px; 139 + } 140 + </style> 141 + </head> 142 + <body> 143 + <div class="container"> 144 + <h1>Bluesky Account Recommendations</h1> 145 + 146 + <p class="blurb">Enter your bluesky handle or DID and get a list of recommended accounts!</p> 147 + 148 + <div class="search-container"> 149 + <form onsubmit="event.preventDefault(); searchProfile();"> 150 + <input type="text" id="searchInput" placeholder="Enter handle or DID (e.g. johndoe.bsky.social)..." class="search-input" value="{{ query }}"> 151 + <button type="submit" class="search-button">Go</button> 152 + </form> 153 + </div> 154 + 155 + <ul class="list-container"> 156 + {% for profile in profiles %} 157 + <div class="profile-card" onclick="window.open('https://bsky.app/profile/{{ profile.handle }}', '_blank')"> 158 + <img src={{ profile.avatar }} alt="Profile" class="profile-image"> 159 + <div class="profile-info"> 160 + <div class="display-name">@{{ profile.handle }}</div> 161 + <div class="did">{{ profile.did }}</div> 162 + <div class="description">{{ profile.description }}</div> 163 + </div> 164 + </div> 165 + {% endfor %} 166 + </ul> 167 + 168 + <script> 169 + function searchProfile() { 170 + const searchValue = document.getElementById('searchInput').value.trim(); 171 + if (searchValue) { 172 + const url = new URL(window.location.href); 173 + url.searchParams.set('query', searchValue); 174 + window.location.href = url.toString(); 175 + } 176 + } 177 + </script> 178 + </div> 179 + </body>
-38
scripts/training/serve.py
··· 1 - from argparse import ArgumentParser 2 - import json 3 - 4 - from scripts.training.models import UserEmbedding, FollowEmbedModule 5 - 6 - 7 - def main(checkpoint_path: str, id_map_path: str): 8 - model = FollowEmbedModule.load_from_checkpoint(checkpoint_path) 9 - 10 - print(f"Shape of source embed weights: {model.source_embed.embed.weight.shape}") 11 - with open(id_map_path, "r") as in_file: 12 - did_id_map = json.load(in_file) 13 - 14 - did = "did:plc:uxmy3zztxyhfk6mxrkun5tpr" 15 - user_id = did_id_map[did] 16 - print(f"did: {did}") 17 - print(f"id: {did_id_map[did]}") 18 - 19 - source_tensor = model.source_embed.embed.weight[user_id, :] 20 - print(f"Embedding: {source_tensor}") 21 - 22 - 23 - if __name__ == "__main__": 24 - parser = ArgumentParser() 25 - parser.add_argument( 26 - "--checkpoint", 27 - required=True, 28 - help="Path to model checkpoint file", 29 - ) 30 - parser.add_argument( 31 - "--did-id-map", 32 - dest="did_id_map", 33 - required=True, 34 - help="Path to did_id_map file", 35 - ) 36 - args = parser.parse_args() 37 - 38 - main(checkpoint_path=args.checkpoint, id_map_path=args.did_id_map)
+2 -1
scripts/utils.py
··· 102 102 103 103 # Create formatter 104 104 formatter = logging.Formatter( 105 - "%(asctime)s | %(levelname)s | %(message)s", datefmt="%Y-%m-%d %H:%M:%S" 105 + "%(asctime)s.%(msecs)03d | %(levelname)s | %(message)s", 106 + datefmt="%Y-%m-%d %H:%M:%S", 106 107 ) 107 108 108 109 # Console handler
+589
uv.lock
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