Mansa Musa was the emperor of the Mali Empire in West Africa during the 14th century. He accumulated immense wealth through several means:        - Gold mining - Mali contained very rich gold deposits, especially in the region of Bambuk. Gold mining and gold trade was a major source of wealth for the empire.        - Control of trade routes - Mali dominated the trans-Saharan trade routes connecting West Africa to North Africa and beyond. By taxing the goods that passed through its territory, Mali profited greatly.        - Tributary states - Many lands surrounding Mali paid tribute to the empire. This came in the form of gold, slaves, and other valuable resources.        - Agriculture - Mali also had extensive agricultural lands irrigated by the Niger River. Surplus food produced could be sold or traded.         - Royal monopolies - The emperor claimed monopoly rights over the production and sale of certain goods like salt from the Taghaza mines. This added to his personal wealth.        - Inheritance - As an emperor, Mansa Musa inherited a wealthy state. His predecessors had already consolidated lands and accumulated riches which fell to Musa.        So in summary, mining, trade, taxes,For more head to the LCEL section.[Legacy] Chain interface‚ÄãChain's are the legacy interface for "chained" applications. We define a Chain very generically as a sequence of calls to components, which can include other chains. The base interface is simple:class Chain(BaseModel, ABC):    """Base interface that all chains should implement."""    memory: BaseMemory    callbacks: Callbacks    def __call__(        self,        inputs: Any,        return_only_outputs: bool = False,        callbacks: Callbacks = None,    ) -> Dict[str, Any]:        ...We can recreate the LCEL runnable we made above using the built-in LLMChain:from langchain.chains import LLMChainchain = LLMChain(llm=model, prompt=prompt, output_parser=StrOutputParser())chain.run(question="How did Mansa Musa accumulate
Using an LLM in isolation is fine for simple applications, but more complex applications require chaining LLMs - either with each other or with other components.
Using an LLM in isolation is fine for simple applications, but more complex applications require chaining LLMs - either with each other or with other components. ->: Mansa Musa was the emperor of the Mali Empire in West Africa during the 14th century. He accumulated immense wealth through several means:        - Gold mining - Mali contained very rich gold deposits, especially in the region of Bambuk. Gold mining and gold trade was a major source of wealth for the empire.        - Control of trade routes - Mali dominated the trans-Saharan trade routes connecting West Africa to North Africa and beyond. By taxing the goods that passed through its territory, Mali profited greatly.        - Tributary states - Many lands surrounding Mali paid tribute to the empire. This came in the form of gold, slaves, and other valuable resources.        - Agriculture - Mali also had extensive agricultural lands irrigated by the Niger River. Surplus food produced could be sold or traded.         - Royal monopolies - The emperor claimed monopoly rights over the production and sale of certain goods like salt from the Taghaza mines. This added to his personal wealth.        - Inheritance - As an emperor, Mansa Musa inherited a wealthy state. His predecessors had already consolidated lands and accumulated riches which fell to Musa.        So in summary, mining, trade, taxes,For more head to the LCEL section.[Legacy] Chain interface‚ÄãChain's are the legacy interface for "chained" applications. We define a Chain very generically as a sequence of calls to components, which can include other chains. The base interface is simple:class Chain(BaseModel, ABC):    """Base interface that all chains should implement."""    memory: BaseMemory    callbacks: Callbacks    def __call__(        self,        inputs: Any,        return_only_outputs: bool = False,        callbacks: Callbacks = None,    ) -> Dict[str, Any]:        ...We can recreate the LCEL runnable we made above using the built-in LLMChain:from langchain.chains import LLMChainchain = LLMChain(llm=model, prompt=prompt, output_parser=StrOutputParser())chain.run(question="How did Mansa Musa accumulate