Spaces:
Sleeping
Sleeping
| from langchain.prompts import PromptTemplate | |
| from langchain.chains import LLMChain | |
| from langchain.tools import DuckDuckGoSearchRun | |
| from langchain import HuggingFaceHub | |
| # 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 | |
| # llm = OpenAI(temperature=creativity,openai_api_key=api_key, | |
| # model_name='gpt-3.5-turbo') | |
| llm=HuggingFaceHub(repo_id="bhenrym14/platypus-yi-34b", model_kwargs={"temperature":creativity }) | |
| #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="langchain", DuckDuckGo_Search=search_result,duration=video_length) | |
| # Returning the output | |
| return search_result,title,script |