perplexityaiproject
Tools (1) Resources (0) Errors (0) PERPLEXITYAI_PERPLEXITY_AI_SEARCH Perplexity ai search interfaces with perplexity ai to perform search queries and return responses from a range of models. this action manages requests to perplexity ai and processes the resulting completions, which may include text, citations, and images based on selected models and settings. key features include: autoprompting to enhance and refine queries, choice of ai models for various content and performance requirements, temperature settings to manage response randomness, top k and top p filters to fine-tune response generation. beta features include citations and images in results, and response streaming for dynamic interaction. note: the parameters 'presence penalty' and 'frequency penalty' are mutually exclusive and cannot be used simultaneously. Parameters frequency_penalty Multiplicative penalty for new tokens based on their frequency in the text to avoid repetition. Mutually exclusive with the 'presence_penalty' parameter. For example: 0.5, 1.0, 1.5. max_tokens The maximum number of tokens to generate. Sum of max_tokens and prompt tokens should not exceed the model's context window limit. Unspecified leads to generation until stop token or context window end. For e.g 100, 150, 200 model The name of the model to use for generating completions. Choose a model based on the desired balance between performance and resource usage. For more information check https://docs.perplexity.ai/guides/model-cards presence_penalty Penalty for new tokens based on their current presence in the text, encouraging topic variety. Mutually exclusive with the 'frequency_penalty' parameter. For example: -2.0, 0.0, 2.0. return_citations Whether to include citations in the model's response. Citations feature is in closed beta. For e.g True, False return_images Whether to include images in the model's response. Image generation feature is in closed beta. For e.g True, False stream Whether to stream the response incrementally using server-sent events. For e.g True, False systemContent* The system's Content for specifying instructions. For e.g Be precise and concise., Be elaborate and descriptive temperature Controls generation randomness, with 0 being deterministic and values approaching 2 being more random. For e.g 0.0, 0.7, 1.5 top_k Limits the number of high-probability tokens to consider for generation. Set to 0 to disable. For e.g 0, 40, 80 top_p Nucleus sampling threshold, controlling the token selection pool based on cumulative probability. For e.g 0.1, 0.9, 1.0 userContent* The user's Content for asking questions or providing input. For e.g How many stars are there in our galaxy?