chore: initial public snapshot for github upload
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"""
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Calls Perplexity's /search endpoint to search the web.
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"""
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from typing import Dict, List, Optional, TypedDict, Union
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import httpx
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from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
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from litellm.llms.base_llm.search.transformation import (
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BaseSearchConfig,
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SearchResponse,
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SearchResult,
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)
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from litellm.secret_managers.main import get_secret_str
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class _PerplexitySearchRequestRequired(TypedDict):
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"""Required fields for Perplexity Search API request."""
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query: Union[str, List[str]] # Required - search query or queries
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class PerplexitySearchRequest(_PerplexitySearchRequestRequired, total=False):
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"""
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Perplexity Search API request format.
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Based on: https://docs.perplexity.ai/api-reference/search-post
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"""
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max_results: int # Optional - maximum number of results (1-20), default 10
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search_domain_filter: List[str] # Optional - list of domains to filter (max 20)
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max_tokens_per_page: int # Optional - max tokens per page, default 1024
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country: str # Optional - country code filter (e.g., 'US', 'GB', 'DE')
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class PerplexitySearchConfig(BaseSearchConfig):
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PERPLEXITY_API_BASE = "https://api.perplexity.ai"
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@staticmethod
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def ui_friendly_name() -> str:
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return "Perplexity"
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def validate_environment(
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self,
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headers: Dict,
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api_key: Optional[str] = None,
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api_base: Optional[str] = None,
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**kwargs,
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) -> Dict:
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"""
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Validate environment and return headers.
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"""
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api_key = api_key or get_secret_str("PERPLEXITYAI_API_KEY")
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if not api_key:
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raise ValueError(
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"PERPLEXITYAI_API_KEY is not set. Set `PERPLEXITYAI_API_KEY` environment variable."
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)
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headers["Authorization"] = f"Bearer {api_key}"
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headers["Content-Type"] = "application/json"
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return headers
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def get_complete_url(
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self,
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api_base: Optional[str],
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optional_params: dict,
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data: Optional[Union[Dict, List[Dict]]] = None,
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**kwargs,
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) -> str:
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"""
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Get complete URL for Search endpoint.
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"""
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api_base = (
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api_base
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or get_secret_str("PERPLEXITY_API_BASE")
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or self.PERPLEXITY_API_BASE
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)
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# append "/search" to the api base if it's not already there
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if not api_base.endswith("/search"):
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api_base = f"{api_base}/search"
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return api_base
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def transform_search_request(
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self,
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query: Union[str, List[str]],
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optional_params: dict,
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**kwargs,
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) -> Dict:
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"""
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Transform Search request to Perplexity API format.
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Note: LiteLLM's native spec is the perplexity search spec.
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There's no transformation needed for the request data.
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https://docs.perplexity.ai/api-reference/search-post
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Args:
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query: Search query (string or list of strings)
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optional_params: Optional parameters for the request
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- max_results: Maximum number of search results (1-20)
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- search_domain_filter: List of domains to filter (max 20)
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- max_tokens_per_page: Max tokens per page (default 1024)
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- country: Country code filter (e.g., 'US', 'GB', 'DE')
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Returns:
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Dict with typed request data following PerplexitySearchRequest spec
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"""
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request_data: PerplexitySearchRequest = {
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"query": query,
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}
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# Add optional parameters following Perplexity API spec (only if not None)
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max_results = optional_params.get("max_results")
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if max_results is not None:
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request_data["max_results"] = max_results
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search_domain_filter = optional_params.get("search_domain_filter")
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if search_domain_filter is not None:
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request_data["search_domain_filter"] = search_domain_filter
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max_tokens_per_page = optional_params.get("max_tokens_per_page")
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if max_tokens_per_page is not None:
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request_data["max_tokens_per_page"] = max_tokens_per_page
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country = optional_params.get("country")
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if country is not None:
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request_data["country"] = country
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return dict(request_data)
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def transform_search_response(
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self,
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raw_response: httpx.Response,
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logging_obj: LiteLLMLoggingObj,
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**kwargs,
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) -> SearchResponse:
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"""
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Transform Perplexity API response to standard SearchResponse format.
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Args:
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raw_response: Raw httpx response from Perplexity API
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logging_obj: Logging object for tracking
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Returns:
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SearchResponse with standardized format
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"""
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response_json = raw_response.json()
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# Transform results to SearchResult objects
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results = []
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for result in response_json.get("results", []):
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search_result = SearchResult(
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title=result.get("title", ""),
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url=result.get("url", ""),
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snippet=result.get("snippet", ""),
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date=result.get("date"),
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last_updated=result.get("last_updated"),
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)
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results.append(search_result)
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return SearchResponse(
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results=results,
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object="search",
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)
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