from langchain.llms import OpenAI

import os
os.environ["OPEN_API_KEY"]=OPEN_API_KEY

llm=OpenAI(openai_api_key=os.environ["OPEN_API_KEY"],temperature=0.6)

text="What is the capital of India"

print(llm.predict(text))



os.environ["HUGGINGFACEHUB_API_TOKEN"]=HuggingFaceHub_API_TOKEN


from langchain import HuggingFaceHub
llm_huggingface=HuggingFaceHub(repo_id="google/flan-t5-large",model_kwargs={"temperature":0,"max_length":64})


output=llm_huggingface.predict("Can you tell me the capital of Russia")
print(output)


output=llm_huggingface.predict("Can you write a poem about AI")
print(output)


llm.predict("Can you write a poem about AI")




from langchain.prompts import PromptTemplate

prompt_template=PromptTemplate(input_variables=['country'],
template="Tell me the capital of this {country}")

prompt_template.format(country="India")


from langchain.chains import LLMChain
chain=LLMChain(llm=llm,prompt=prompt_template)
print(chain.run("India"))




capital_template=PromptTemplate(input_variables=['country'],
template="Please tell me the capital of the {country}")

capital_chain=LLMChain(llm=llm,prompt=capital_template)

famous_template=PromptTemplate(input_variables=['capital'],
template="Suggest me some amazing places to visit in {capital}")

famous_chain=LLMChain(llm=llm,prompt=famous_template)

from langchain.chains import SimpleSequentialChain
chain=SimpleSequentialChain(chains=[capital_chain,famous_chain])
chain.run("India")



capital_template=PromptTemplate(input_variables=['country'],
template="Please tell me the capital of the {country}")

capital_chain=LLMChain(llm=llm,prompt=capital_template,output_key="capital")

famous_template=PromptTemplate(input_variables=['capital'],
template="Suggest me some amazing places to visit in {capital}")

famous_chain=LLMChain(llm=llm,prompt=famous_template,output_key="places")

from langchain.chains import SequentialChain
chain=SequentialChain(chains=[capital_chain,famous_chain],
input_variables=['country'],
output_variables=['capital',"places"])

chain({'country':"India"})




from langchain.chat_models import ChatOpenAI

from langchain.schema import HumanMessage,SystemMessage,AIMessage

chatllm=ChatOpenAI(openai_api_key=os.environ["OPEN_API_KEY"],temperature=0.6,model='gpt-3.5-turbo')

chatllm([
SystemMessage(content="Yor are a comedian AI assitant"),
HumanMessage(content="Please provide some comedy punchlines on AI")
])




from langchain.chat_models import ChatOpenAI
from langchain.prompts.chat import ChatPromptTemplate
from langchain.schema import BaseOutputParser

class Commaseperatedoutput(BaseOutputParser):
    def parse(self,text:str):
        return text.strip().split(",")

template="Your are a helpful assistant. When the use given any input , you should generate 5 words synonyms in a comma seperated list"
human_template="{text}"
chatprompt=ChatPromptTemplate.from_messages([
    ("system",template),
    ("human",human_template)


])

chain=chatprompt|chatllm|Commaseperatedoutput()

chain.invoke({"text":"intelligent"})