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Perplexity API
Perplexity API
Tool

perplexity_chat_completions

Generates a model’s response for the given chat conversation.


Pricing

Per call

$0.02

Model

flat


Pay only for what you use. No subscriptions.
Inputs

reasoning_effort

string

return_images

boolean

search_mode

string

presence_penalty

number

search_after_date_filter

string

disable_search

boolean

web_search_options

object

top_p

number

last_updated_before_filter

string

frequency_penalty

number

response_format

object

stream

boolean

top_k

number

temperature

number

model *

string

search_domain_filter

string

last_updated_after_filter

string

return_related_questions

boolean

search_before_date_filter

string

max_tokens

integer

enable_search_classifier

boolean

language_preference

string

messages *

array

search_recency_filter

string

media_response

object
Try It
API
MCP Config
Input Parameters
reasoning_effort
Perplexity-Specific: Controls how much computational effort the AI dedicates to each query for deep research models. 'low' provides faster, simpler answers with reduced token usage, 'medium' offers a balanced approach, and 'high' delivers deeper, more thorough responses with increased token usage. This parameter directly impacts the amount of reasoning tokens consumed. WARNING: This parameter is ONLY applicable for sonar-deep-research. Defaults to 'medium' when used with sonar-deep-research.
search_mode
Controls search mode: 'academic' prioritizes scholarly sources, 'sec' prioritizes SEC filings, 'web' uses general web search. See academic guide and SEC guide.
presence_penalty
OpenAI Compatible: Positive values increase the likelihood of discussing new topics. Applies a penalty to tokens that have already appeared in the text, encouraging the model to talk about new concepts. Values typically range from 0 (no penalty) to 2.0 (strong penalty). Higher values reduce repetition but may lead to more off-topic text.
search_after_date_filter
Perplexity-Specific: Filters search results to only include content published after this date. Format should be %m/%d/%Y (e.g. 3/1/2025)
web_search_options
Perplexity-Specific: Configuration for using web search in model responses.
top_p
OpenAI Compatible: The nucleus sampling threshold, valued between 0 and 1. Controls the diversity of generated text by considering only the tokens whose cumulative probability exceeds the top_p value. Lower values (e.g., 0.5) make the output more focused and deterministic, while higher values (e.g., 0.95) allow for more diverse outputs. Often used as an alternative to temperature.
last_updated_before_filter
Perplexity-Specific: Filters search results to only include content last updated before this date. Format should be %m/%d/%Y (e.g. 3/1/2025)
frequency_penalty
OpenAI Compatible: Decreases likelihood of repetition based on prior frequency. Applies a penalty to tokens based on how frequently they've appeared in the text so far. Values typically range from 0 (no penalty) to 2.0 (strong penalty). Higher values (e.g., 1.5) reduce repetition of the same words and phrases. Useful for preventing the model from getting stuck in loops.
response_format
Enables structured JSON output formatting.
top_k
OpenAI Compatible: The number of tokens to keep for top-k filtering. Limits the model to consider only the k most likely next tokens at each step. Lower values (e.g., 20) make the output more focused and deterministic, while higher values allow for more diverse outputs. A value of 0 disables this filter. Often used in conjunction with top_p to control output randomness.
temperature
The amount of randomness in the response, valued between 0 and 2. Lower values (e.g., 0.1) make the output more focused, deterministic, and less creative. Higher values (e.g., 1.5) make the output more random and creative. Use lower values for factual/information retrieval tasks and higher values for creative applications.
model *
The name of the model that will complete your prompt. Choose from our available Sonar models: sonar (lightweight search), sonar-pro (advanced search), sonar-deep-research (exhaustive research), or sonar-reasoning-pro (premier reasoning).
search_domain_filter
A list of domains to limit search results to. Currently limited to 20 domains for Allowlisting and Denylisting. For Denylisting, add a - at the beginning of the domain string. More information about this here.
last_updated_after_filter
Perplexity-Specific: Filters search results to only include content last updated after this date. Format should be %m/%d/%Y (e.g. 3/1/2025)
search_before_date_filter
Perplexity-Specific: Filters search results to only include content published before this date. Format should be %m/%d/%Y (e.g. 3/1/2025)
max_tokens
OpenAI Compatible: The maximum number of completion tokens returned by the API. Controls the length of the model's response. If the response would exceed this limit, it will be truncated. Higher values allow for longer responses but may increase processing time and costs.
language_preference
Perplexity-Specific: Specifies the preferred language for the chat completion response (i.e., English, Korean, Spanish, etc.) of the response content. This parameter is supported only by the sonar and sonar-pro models. Using it with other models is on a best-effort basis and may not produce consistent results.
messages *
A list of messages comprising the conversation so far.
search_recency_filter
Perplexity-Specific: Filters search results based on time (e.g., 'week', 'day').
media_response
Perplexity-Specific: Configuration for controlling media content in responses, such as videos and images. Use the overrides property to enable specific media types.
Cost per run
Execution cost
$0.02
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