chore: initial snapshot for gitea/github upload
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"""
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Tavily Search API module.
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"""
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from litellm.llms.tavily.search.transformation import TavilySearchConfig
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__all__ = ["TavilySearchConfig"]
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"""
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Calls Tavily's /search endpoint to search the web.
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Tavily API Reference: https://docs.tavily.com/documentation/api-reference/endpoint/search
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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 _TavilySearchRequestRequired(TypedDict):
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"""Required fields for Tavily Search API request."""
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query: str # Required - search query
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class TavilySearchRequest(_TavilySearchRequestRequired, total=False):
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"""
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Tavily Search API request format.
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Based on: https://docs.tavily.com/documentation/api-reference/endpoint/search
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"""
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max_results: int # Optional - maximum number of results (0-20), default 5
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include_domains: List[str] # Optional - list of domains to include (max 300)
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exclude_domains: List[str] # Optional - list of domains to exclude (max 150)
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topic: str # Optional - category of search ('general', 'news', 'finance'), default 'general'
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search_depth: str # Optional - depth of search ('basic', 'advanced'), default 'basic'
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include_answer: Union[bool, str] # Optional - include LLM-generated answer
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include_raw_content: Union[bool, str] # Optional - include raw HTML content
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include_images: bool # Optional - perform image search
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include_image_descriptions: bool # Optional - add descriptions for images
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include_favicon: bool # Optional - include favicon URL
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time_range: str # Optional - time range filter ('day', 'week', 'month', 'year', 'd', 'w', 'm', 'y')
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start_date: str # Optional - start date filter (YYYY-MM-DD)
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end_date: str # Optional - end date filter (YYYY-MM-DD)
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country: str # Optional - country code filter (e.g., 'US', 'GB', 'DE')
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class TavilySearchConfig(BaseSearchConfig):
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TAVILY_API_BASE = "https://api.tavily.com"
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@staticmethod
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def ui_friendly_name() -> str:
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return "Tavily"
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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("TAVILY_API_KEY")
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if not api_key:
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raise ValueError(
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"TAVILY_API_KEY is not set. Set `TAVILY_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 = api_base or get_secret_str("TAVILY_API_BASE") or self.TAVILY_API_BASE
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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 Tavily API format.
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Args:
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query: Search query (string or list of strings). Tavily only supports single string queries.
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optional_params: Optional parameters for the request
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- max_results: Maximum number of search results (0-20)
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- search_domain_filter: List of domains to include (max 300) -> maps to `include_domains`
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- exclude_domains: List of domains to exclude (max 150)
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- topic: Category of search ('general', 'news', 'finance')
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- search_depth: Depth of search ('basic', 'advanced')
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- include_answer: Include LLM-generated answer (bool or 'basic', 'advanced')
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- include_raw_content: Include raw HTML content (bool or 'markdown', 'text')
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- include_images: Perform image search (bool)
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- include_image_descriptions: Add descriptions for images (bool)
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- include_favicon: Include favicon URL (bool)
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- time_range: Time range filter ('day', 'week', 'month', 'year', 'd', 'w', 'm', 'y')
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- start_date: Start date filter (YYYY-MM-DD)
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- end_date: End date filter (YYYY-MM-DD)
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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 TavilySearchRequest spec
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"""
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if isinstance(query, list):
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# Tavily only supports single string queries
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query = " ".join(query)
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request_data: TavilySearchRequest = {
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"query": query,
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}
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# Transform Perplexity unified spec parameters to Tavily format
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if "max_results" in optional_params:
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request_data["max_results"] = optional_params["max_results"]
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if "search_domain_filter" in optional_params:
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request_data["include_domains"] = optional_params["search_domain_filter"]
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if "country" in optional_params:
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# Tavily expects lowercase country names
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request_data["country"] = optional_params["country"].lower()
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# Convert to dict before dynamic key assignments
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result_data = dict(request_data)
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# pass through all other parameters as-is
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for param, value in optional_params.items():
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if (
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param not in self.get_supported_perplexity_optional_params()
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and param not in result_data
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):
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result_data[param] = value
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return result_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 Tavily API response to LiteLLM unified SearchResponse format.
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Tavily → LiteLLM mappings:
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- results[].title → SearchResult.title
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- results[].url → SearchResult.url
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- results[].content → SearchResult.snippet
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- No date/last_updated fields in Tavily response (set to None)
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Args:
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raw_response: Raw httpx response from Tavily 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(
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"content", ""
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), # Tavily uses "content" instead of "snippet"
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date=None, # Tavily doesn't provide date in response
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last_updated=None, # Tavily doesn't provide last_updated in response
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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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