fsndzomga

from langchain.prompts import ChatPromptTemplate
from langchain.chat_models import ChatOpenAI
from apikey import OPENAI_API_KEY
import os

os.environ['OPENAI_API_KEY'] = OPENAI_API_KEY

model = ChatOpenAI()

prompt = ChatPromptTemplate.from_template("In 2016, who was the president of {country}")

fsndzomga

from langchain.vectorstores import Chroma
from langchain.embeddings import OpenAIEmbeddings
from langchain.schema.runnable import RunnablePassthrough
from langchain.schema.output_parser import StrOutputParser
from langchain.prompts import ChatPromptTemplate
from langchain.chat_models import ChatOpenAI
from operator import itemgetter
from apikey import OPENAI_API_KEY
import os

fsndzomga

from flask import render_template, redirect, url_for, request, flash, session
from app import app
from app.forms import EmptyForm
from pdf_bot_class import PdfBot
from io import BytesIO
from uuid import uuid4


@app.route('/')
@app.route('/index')

fsndzomga

import os
import PyPDF2
from embedchain import App
from config import Config
from embedchain.config import ChunkerConfig, AddConfig


OPENAI_KEY = Config.OPENAI_KEY
chunker_config = ChunkerConfig(chunk_size=500, chunk_overlap=100)

fsndzomga

[nlp]
lang = "en"
pipeline = ["llm"]

[components]

[components.llm]
factory = "llm"

[components.llm.task]

fsndzomga

from keys import OPENAI_API_KEY
import os
from spacy_llm.util import assemble

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY


nlp = assemble("config.cfg")
doc = nlp("You are an idiot !")
print(doc.cats)

fsndzomga

import pandas as pd
from keys import OPENAI_API_KEY
import os
from spacy_llm.util import assemble
import pandas as pd

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

nlp = assemble("email_config.cfg")

fsndzomga

[nlp]
lang = "en"
pipeline = ["llm"]

[components]

[components.llm]
factory = "llm"

[components.llm.task]

fsndzomga

# Example of a simple corpus
corpus = [
    "Natural Language Processing is fascinating.",
    "ChatGPT is based on GPT-3.",
    "Machine learning is an application of artificial intelligence."
]

fsndzomga

from nltk.tokenize import word_tokenize

sentence = "Natural Language Processing is fascinating."
tokens = word_tokenize(sentence)
print(tokens)
# Output: ['Natural', 'Language', 'Processing', 'is', 'fascinating', '.']