from constants import OPENAI_API_KEY

!pip show langchain-openai | grep "Version:"

Version: 0.2.9

import os

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="gpt-4o-mini")

from langchain_core.output_parsers import (
    JsonOutputParser,
)


# A function that operates on finalized inputs
# rather than on an input_stream
def _extract_country_names(inputs):
    """A function …

from constants import OPENAI_API_KEY

!pip show langchain-openai | grep "Version:"

Version: 0.2.9

import os

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="gpt-4o-mini")

chunks = []
for chunk in model.stream("what color is the sky?"):
    chunks.append(chunk)
    print(chunk.content, end="|", flush=True)

|The| color …

!python --version

Python 3.12.4

from constants import OPENAI_API_KEY

!pip show langchain-openai | grep "Version:"

Version: 0.2.9

import os

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="gpt-4o-mini")

!pip install faiss-cpu

Collecting faiss-cpu
  Downloading faiss_cpu-1.9.0.post1-cp312-cp312-manylinux_2_17_x86_64 …

content = """
one
two
"""

# Split content into lines and skip empty lines
lines = [line for line in content.splitlines() if line.strip()]
print(lines)

['one', 'two']

import numpy as np
import pandas as pd
from io import StringIO

content = """
    1, 2
    3, 4
    5, 6
"""

content

'\n    1, 2\n    3, 4\n    5, 6\n'

df = pd.read_csv(StringIO(content), header=None …

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier, export_graphviz
import pydotplus
from IPython.display import Image

# Create a custom student dataset
data = {
    "GPA": [3.5, 3.0, 3.8, 3.2, 3.6, 2.8, 3.9, 2.5, 3.1, 3.7],
    "Internship …

import matplotlib.pyplot as plt

python_course_green = "#476042"
plt.figure(figsize=(6, 4))
plt.subplot(221) # equivalent to: plt.subplot(2, 2, 1)

<matplotlib.axes._subplots.AxesSubplot at 0x11365e1d0>

plt.text(0.5, # x coordinate, 0 …

import numpy as np
import pandas as pd

df = pd.read_csv('abc.csv')

df

import numpy as np
import pandas as pd

df = pd.DataFrame(np.random.rand(10, 5))

df

import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: ml311; pyv: 3.11.10 (main, Oct  3 2024, 07:29:13) [GCC 11.2.0]'

print(pyu.ps2("haystack-ai ollama-haystack python-dotenv"))

haystack-ai==2.8.0
ollama-haystack is not installed in the current environment.
python-dotenv==0.21.0

import traceback

def divide_numbers …