Agar tum us repo ko bas ek normal folder ki tarah rakhna chahte ho aur uske saare files parent repo ke saath GitHub par push karna chahte ho, toh Option 2 sahi hai.
Time.
Saturday, 30 May 2026
sql
WITH filtered AS (
SELECT *
FROM Kurtis
WHERE stock_quantity > 20
AND color IN ('Red', 'Green')
AND date_added BETWEEN DATE '2024-08-01' AND DATE '2024-11-01'
),
ranked AS (
SELECT *,
DENSE_RANK() OVER (
PARTITION BY brand, size
ORDER BY price DESC
) AS rnk
FROM filtered
),
selected AS (
SELECT *
FROM ranked
WHERE rnk = 1
),
stock_totals AS (
SELECT brand,
size,
SUM(stock_quantity) AS total_stock
FROM selected
GROUP BY brand, size
)
SELECT
s.brand,
s.size,
s.color,
s.price,
t.total_stock
FROM selected s
JOIN stock_totals t
ON s.brand = t.brand
AND s.size = t.size
ORDER BY
s.brand,
t.total_stock DESC,
s.price DESC;
SELECT
k.brand,
k.size,
k.color,
k.price,
s.total_stock
FROM Kurtis k
JOIN (
SELECT
brand,
size,
SUM(stock_quantity) AS total_stock
FROM Kurtis
WHERE stock_quantity > 20
AND color IN ('Red', 'Green')
AND date_added BETWEEN '2024-08-01' AND '2024-11-01'
GROUP BY brand, size
) s
ON k.brand = s.brand
AND k.size = s.size
WHERE k.stock_quantity > 20
AND k.color IN ('Red', 'Green')
AND k.date_added BETWEEN '2024-08-01' AND '2024-11-01'
AND k.price = (
SELECT MAX(price)
FROM Kurtis k2
WHERE k2.brand = k.brand
AND k2.size = k.size
AND k2.stock_quantity > 20
AND k2.color IN ('Red', 'Green')
AND k2.date_added BETWEEN '2024-08-01' AND '2024-11-01'
)
ORDER BY k.brand, s.total_stock DESC, k.price DESC;
Thursday, 28 May 2026
Sunday, 24 May 2026
langchain mein if chabot bana ho but like uska code invoke na support
from transformers import AutoTokenizer, AutoModelForCausalLM
from langchain_core.runnables import RunnableLambda
model_name = "Qwen/Qwen3-0.6B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
device_map="auto"
)
def generate_response(user_input):
messages = [
{"role": "user", "content": user_input}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True,
enable_thinking=True
)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(
**inputs,
max_new_tokens=200
)
response = tokenizer.decode(
outputs[0][inputs.input_ids.shape[1]:],
skip_special_tokens=True
)
return response
llm = RunnableLambda(generate_response)
print(llm.invoke("Who are Eldians in AOT?"))
Friday, 15 May 2026
Wednesday, 13 May 2026
3rd year chutti
1. project -:
2. leetcode- legularly
3. gen ai -regularly
4. cs funcdamental
5. english speaking : regularly
6. deep learning and ml ki practice -:
Friday, 8 May 2026
docker ka use
watch campusx video
then fastapi wale course m se repo m dockerfile wali file dekh
https://chatgpt.com/share/69fe4e12-148c-83e8-9d78-05c8686a46e8
Hello
added second repo in current repo as folder
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