remove endpoints in fastify && update model

app/cron_ai_score.py

@@ -243,7 +243,7 @@ async def download_data(ticker, con, start_date, end_date, skip_downloading):
             if not df_copy.empty:
                 with open(file_path, 'wb') as file:
                     file.write(orjson.dumps(df_copy.to_dict(orient='records')))
-            print(df_copy)
+
             return df_copy
 
         except Exception as e:
@@ -266,6 +266,7 @@ async def chunked_gather(tickers, con, skip_downloading, chunk_size):
 
     for chunk in tqdm(chunks(tickers, chunk_size)):
         # Create tasks for each chunk
+        print(f"chunk size: {len(chunk)}")
         tasks = [download_data(ticker, con, start_date, end_date, skip_downloading) for ticker in chunk]
         # Await the results for the current chunk
         chunk_results = await asyncio.gather(*tasks)
@@ -357,7 +358,7 @@ async def run():
               AND symbol NOT LIKE '%.%' 
               AND symbol NOT LIKE '%-%' 
         """)
-        warm_start_symbols = ['AAPL'] #[row[0] for row in cursor.fetchall()]
+        warm_start_symbols = ['PEP'] #[row[0] for row in cursor.fetchall()]
 
         print(f'Warm Start Training: Total Tickers {len(warm_start_symbols)}')
         await warm_start_training(warm_start_symbols, con, skip_downloading)

app/ml_models/score_model.py

@@ -23,16 +23,11 @@ class ScorePredictor:
         self.pca = PCA(n_components=0.95)  # Retain components explaining 95% variance
         self.warm_start_model_path = 'ml_models/weights/ai-score/warm_start_weights.pkl'
         self.model = lgb.LGBMClassifier(
-            n_estimators=200,           # Number of boosting iterations - good balance between performance and training time
+            n_estimators=20_000,           # Number of boosting iterations - good balance between performance and training time
-            learning_rate=0.005,         # Smaller learning rate for better generalization
+            learning_rate=0.001,         # Smaller learning rate for better generalization
-            max_depth=5,                 # Controlled depth to prevent overfitting
+            max_depth=6,                 # Controlled depth to prevent overfitting
-            num_leaves=2**5-1,            # 2^max_depth, prevents overfitting while maintaining model complexity
+            num_leaves=2**6-1,            # 2^max_depth, prevents overfitting while maintaining model complexity
-            colsample_bytree=0.8,       # Use 80% of features per tree to reduce overfitting
+            colsample_bytree=0.1,
-            subsample=0.8,              # Use 80% of data per tree to reduce overfitting
-            min_child_samples=5,       # Minimum samples per leaf to ensure reliable splits
-            random_state=42,            # For reproducibility
-            reg_alpha=0.1,             # L1 regularization
-            reg_lambda=0.1,            # L2 regularization
             n_jobs=10,                 # Use N CPU cores
             verbose=0,               # Reduce output noise
         )

fastify/app.js

@@ -61,10 +61,6 @@ const corsMiddleware = (request, reply, done) => {
 fastify.addHook("onRequest", corsMiddleware);
 
 //fastify.register(require('./mixpanel/server'), { mixpanel, UAParser });
-fastify.register(require("./get-user-stats/server"), { pb });
-fastify.register(require("./get-community-stats/server"), { pb });
-fastify.register(require("./get-moderators/server"), { pb });
-fastify.register(require("./get-user-data/server"), { pb });
 fastify.register(require("./get-all-comments/server"), { pb });
 fastify.register(require("./get-post/server"), { pb });
 fastify.register(require("./get-one-post/server"), { pb });

fastify/get-community-stats/server.js

@@ -1,27 +0,0 @@
-module.exports = function (fastify, opts, done) {
-    const pb = opts.pb;
-
-    fastify.get('/get-community-stats', async (request, reply) => {
-        let output;
-        let totalUsers = 0;
-        let totalPosts = 0;
-        let totalComments = 0;
-
-        try {
-            totalUsers = (await pb.collection("users").getList(1, 1))?.totalItems;
-            totalPosts = (await pb.collection("posts").getList(1, 1))?.totalItems;
-            totalComments = (await pb.collection("comments").getList(1, 1))?.totalItems;
-
-          
-            output = { totalUsers, totalPosts, totalComments };
-
-        } catch (e) {
-            console.error(e);
-            output = { totalUsers, totalPosts, totalComments };
-        }
-
-        reply.send({ items: output });
-    });
-
-    done();
-};

fastify/get-moderators/server.js

@@ -1,22 +0,0 @@
-// Declare a route
-module.exports = function (fastify, opts, done) {
-    
-    const pb = opts.pb;
-
-    fastify.get('/get-moderators', async (request, reply) => {
-    let output;
-
-    try {
-        output = await pb.collection("moderators").getFullList({
-            expand: 'user'
-        })
-    }
-    catch(e) {
-        output = [];
-    }
-    
-    reply.send({ items: output })
-    });
-
-    done();
-};

fastify/get-user-data/server.js

@@ -1,22 +0,0 @@
-// Declare a route
-module.exports = function (fastify, opts, done) {
-    
-    const pb = opts.pb;
-
-    fastify.post('/get-user-data', async (request, reply) => {
-    const data = request.body;
-    const userId = data?.userId
-    let output;
-
-    try {
-        output = await pb.collection("users").getOne(userId)
-    }
-    catch(e) {
-        output = {};
-    }
-    
-    reply.send({ items: output })
-    });
-
-    done();
-};

fastify/get-user-stats/server.js

@@ -1,36 +0,0 @@
-// Declare a route
-module.exports = function (fastify, opts, done) {
-    
-    const pb = opts.pb;
-
-    fastify.post('/get-user-stats', async (request, reply) => {
-    const data = request.body;
-    const userId = data?.userId;
-
-    let output;
-
-    try {
-        const getNumberOfPosts = await pb.collection("posts").getList(1,1, {
-            filter: `user="${userId}"`,
-        });
-        const numberOfPosts = getNumberOfPosts?.totalItems
-
-
-        const getNumberOfComments = await pb.collection("comments").getList(1,1, {
-            filter: `user="${userId}"`,
-        });
-        const numberOfComments = getNumberOfComments?.totalItems
-
-        output = {numberOfPosts, numberOfComments}
-        console.log(output)
-
-    }
-    catch(e) {
-        output = {};
-    }
-
-    reply.send({ items: output })
-    });
-
-    done();
-};