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| from langchain.llms import OpenAI | |
| from langchain.prompts import PromptTemplate | |
| from langchain.chains import LLMChain | |
| from langchain.tools import DuckDuckGoSearchRun | |
| # Function to generate video script | |
| def generate_script(prompt,duration,origin,budget,api_key): | |
| # Template for generating 'Itinerary' using search engine | |
| itinerary_template = PromptTemplate( | |
| input_variables = ['location','duration','DuckDuckGo_Search','expense','origin'], | |
| template='Please come up with a detailed itinerary for a trip to {location} for a duration: {duration} days using this search data {DuckDuckGo_Search}. The maximum budget per person in INR is {expense}. The origin of the journey is {origin}. ' | |
| ) | |
| # Template for generating 'Conveyance Used' using search engine | |
| conveyance_template = PromptTemplate( | |
| input_variables = ['location', 'origin', 'DuckDuckGo_Search'], | |
| #template='Based on this itinerary: {itinerary}, please mention the conveyance to be taken during the trip while going from one place to another using this search data {DuckDuckGo_Search} ' | |
| template='Please mention the different ways to reach the {location} from {origin} and the different modes of travel using this search data {DuckDuckGo_Search} ' | |
| ) | |
| # Template for generating 'Cuisines' using search engine | |
| cuisines_template = PromptTemplate( | |
| input_variables = ['itinerary', 'DuckDuckGo_Search'], | |
| template='Based on this itinerary: {itinerary}, please mention the cuisines that I can try during the trip using this search data {DuckDuckGo_Search} ' | |
| ) | |
| # Template for generating 'Accomodation' using search engine | |
| accomodation_template = PromptTemplate( | |
| input_variables = ['itinerary', 'DuckDuckGo_Search'], | |
| template='Based on this itinerary: {itinerary}, please mention the accomodation/hotel that I can stay in during the trip using this search data {DuckDuckGo_Search} ' | |
| ) | |
| #Setting up OpenAI LLM | |
| llm = OpenAI(temperature=0.5, openai_api_key=api_key, model_name='gpt-3.5-turbo') | |
| #Creating chain for 'Itinerary', 'Conveyance', 'Cuisines', 'Accomodation' | |
| itinerary_chain = LLMChain(llm=llm, prompt=itinerary_template, verbose=True) | |
| conveyance_chain = LLMChain(llm=llm, prompt=conveyance_template, verbose=True) | |
| cuisines_chain = LLMChain(llm=llm, prompt=cuisines_template, verbose=True) | |
| accomodation_chain = LLMChain(llm=llm, prompt=accomodation_template, verbose=True) | |
| # https://python.langchain.com/docs/modules/agents/tools/integrations/ddg | |
| search = DuckDuckGoSearchRun() | |
| search_result = search.run(prompt) | |
| # Executing the chains we created for 'Itinerary' by taking help of search engine 'DuckDuckGo' | |
| itinerary = itinerary_chain.run(location=prompt,duration=duration,DuckDuckGo_Search=search_result,expense=budget,origin=origin) | |
| # Executing the chains we created for 'Conveyance', 'Cuisines', 'Accomodation' by taking help of search engine 'DuckDuckGo' | |
| conveyance = conveyance_chain.run(location=prompt,origin=origin,DuckDuckGo_Search=search_result) | |
| hotel = accomodation_chain.run(itinerary=itinerary,DuckDuckGo_Search=search_result) | |
| cuisine = cuisines_chain.run(itinerary=itinerary,DuckDuckGo_Search=search_result) | |
| # Returning the output | |
| return search_result,itinerary,conveyance,hotel,cuisine |