from langchain.llms import HuggingFaceHub from langchain.prompts import PromptTemplate from langchain.chains import LLMChain from langchain.tools import DuckDuckGoSearchRun # Function to generate video script def generate_script(prompt,video_length,creativity,api_key): # Template for generating 'Title' title_template = PromptTemplate( input_variables = ['subject'], template='Please come up with a title for a YouTube video on the {subject}.' ) # Template for generating 'Video Script' using search engine script_template = PromptTemplate( input_variables = ['title', 'DuckDuckGo_Search','duration'], template='Create a script for a YouTube video based on this title for me. TITLE: {title} of duration: {duration} minutes using this search data {DuckDuckGo_Search} ' ) #Setting up OpenAI LLM model_kwargs = { 'temperature': creativity } llm = HuggingFaceHub(repo_id ="HuggingFaceH4/zephyr-7b-gemma-v0.1", model_kwargs = model_kwargs) #Creating chain for 'Title' & 'Video Script' title_chain = LLMChain(llm=llm, prompt=title_template, verbose=True) script_chain = LLMChain(llm=llm, prompt=script_template, verbose=True) # https://python.langchain.com/docs/modules/agents/tools/integrations/ddg search = DuckDuckGoSearchRun() # Executing the chains we created for 'Title' title = title_chain.run(prompt) # Executing the chains we created for 'Video Script' by taking help of search engine 'DuckDuckGo' search_result = search.run(prompt) script = script_chain.run(title=title, DuckDuckGo_Search=search_result,duration=video_length) # Returning the output return search_result,title,script