# Banana This page covers how to use the Banana ecosystem within LangChain. It is broken into two parts: installation and setup, and then references to specific Banana wrappers. ## Installation and Setup - Install with `pip3 install banana-dev` - Get an CerebriumAI api key and set it as an environment variable (`BANANA_API_KEY`) ## Define your Banana Template If you want to use an available language model template you can find one [here](https://app.banana.dev/templates/conceptofmind/serverless-template-palmyra-base). This template uses the Palmyra-Base model by [Writer](https://writer.com/product/api/). You can check out an example Banana repository [here](https://github.com/conceptofmind/serverless-template-palmyra-base). ## Build the Banana app You must include a output in the result. There is a rigid response structure. ```python # Return the results as a dictionary result = {'output': result} ``` An example inference function would be: ```python def inference(model_inputs:dict) -> dict: global model global tokenizer # Parse out your arguments prompt = model_inputs.get('prompt', None) if prompt == None: return {'message': "No prompt provided"} # Run the model input_ids = tokenizer.encode(prompt, return_tensors='pt').cuda() output = model.generate( input_ids, max_length=100, do_sample=True, top_k=50, top_p=0.95, num_return_sequences=1, temperature=0.9, early_stopping=True, no_repeat_ngram_size=3, num_beams=5, length_penalty=1.5, repetition_penalty=1.5, bad_words_ids=[[tokenizer.encode(' ', add_prefix_space=True)[0]]] ) result = tokenizer.decode(output[0], skip_special_tokens=True) # Return the results as a dictionary result = {'output': result} return result ``` You can find a full example of a Banana app [here](https://github.com/conceptofmind/serverless-template-palmyra-base/blob/main/app.py). ## Wrappers ### LLM There exists an Banana LLM wrapper, which you can access with ```python from langchain.llms import Banana ``` You need to provide a model key located in the dashboard: ```python llm = Banana(model_key="YOUR_MODEL_KEY") ```