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This commit is contained in:
Kesku
Sameer Kankute
parent
003cdc43df
commit
35a83fe8f7
2 changed files with 111 additions and 75 deletions
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@ -34,7 +34,7 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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"""
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Configuration for Perplexity Agent API (Responses API)
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Reference: https://docs.perplexity.ai/docs/agent-api/overview
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"""
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@ -45,7 +45,7 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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def get_supported_openai_params(self, model: str) -> list:
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"""
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Perplexity Responses API supports a different set of parameters
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Ref: https://docs.perplexity.ai/api-reference/responses-post
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Params aligned with response-echo fields and Open Responses spec.
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"""
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@ -83,16 +83,15 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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) -> dict:
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"""Validate environment and set up headers"""
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# Get API key from environment
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api_key = (
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get_secret_str("PERPLEXITYAI_API_KEY")
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or get_secret_str("PERPLEXITY_API_KEY")
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api_key = get_secret_str("PERPLEXITYAI_API_KEY") or get_secret_str(
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"PERPLEXITY_API_KEY"
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)
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if api_key:
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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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@ -102,15 +101,17 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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) -> str:
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"""Get the complete URL for the Perplexity Responses API"""
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if api_base is None:
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api_base = get_secret_str("PERPLEXITY_API_BASE") or "https://api.perplexity.ai"
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api_base = (
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get_secret_str("PERPLEXITY_API_BASE") or "https://api.perplexity.ai"
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)
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# Ensure api_base doesn't end with a slash
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api_base = api_base.rstrip("/")
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# Add the responses endpoint
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return f"{api_base}/v1/responses"
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def map_openai_params(
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def map_openai_params( # noqa: PLR0915
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self,
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response_api_optional_params: ResponsesAPIOptionalRequestParams,
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model: str,
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@ -118,65 +119,75 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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) -> Dict:
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"""
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Map OpenAI Responses API parameters to Perplexity format
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Key differences:
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- Supports 'preset' parameter for predefined configurations
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- Supports 'instructions' parameter for system-level guidance
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- Tools are specified differently (web_search, fetch_url)
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"""
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mapped_params: Dict[str, Any] = {}
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# Map standard parameters
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if response_api_optional_params.get("max_output_tokens"):
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mapped_params["max_output_tokens"] = response_api_optional_params["max_output_tokens"]
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mapped_params["max_output_tokens"] = response_api_optional_params[
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"max_output_tokens"
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]
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if response_api_optional_params.get("temperature"):
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mapped_params["temperature"] = response_api_optional_params["temperature"]
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if response_api_optional_params.get("top_p"):
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mapped_params["top_p"] = response_api_optional_params["top_p"]
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if response_api_optional_params.get("stream"):
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mapped_params["stream"] = response_api_optional_params["stream"]
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if response_api_optional_params.get("stream_options"):
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mapped_params["stream_options"] = response_api_optional_params["stream_options"]
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mapped_params["stream_options"] = response_api_optional_params[
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"stream_options"
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]
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# Map Perplexity-specific parameters (using .get() with Any dict access)
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preset = response_api_optional_params.get("preset") # type: ignore
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if preset:
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mapped_params["preset"] = preset
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instructions = response_api_optional_params.get("instructions") # type: ignore
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if instructions:
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mapped_params["instructions"] = instructions
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if response_api_optional_params.get("reasoning"):
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mapped_params["reasoning"] = response_api_optional_params["reasoning"]
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tools = response_api_optional_params.get("tools")
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if tools:
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# Convert tools to list of dicts for transformation
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tools_list = [dict(tool) if hasattr(tool, '__dict__') else tool for tool in tools] # type: ignore
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tools_list = [dict(tool) if hasattr(tool, "__dict__") else tool for tool in tools] # type: ignore
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mapped_params["tools"] = self._transform_tools(tools_list) # type: ignore
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# Tool control
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if response_api_optional_params.get("tool_choice"):
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mapped_params["tool_choice"] = response_api_optional_params["tool_choice"]
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if response_api_optional_params.get("parallel_tool_calls") is not None:
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mapped_params["parallel_tool_calls"] = response_api_optional_params["parallel_tool_calls"]
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mapped_params["parallel_tool_calls"] = response_api_optional_params[
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"parallel_tool_calls"
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]
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if response_api_optional_params.get("max_tool_calls"):
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mapped_params["max_tool_calls"] = response_api_optional_params["max_tool_calls"]
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mapped_params["max_tool_calls"] = response_api_optional_params[
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"max_tool_calls"
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]
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# Structured outputs
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text_param = response_api_optional_params.get("text")
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if text_param:
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mapped_params["text"] = text_param
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# Conversation continuity
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if response_api_optional_params.get("previous_response_id"):
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mapped_params["previous_response_id"] = response_api_optional_params["previous_response_id"]
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mapped_params["previous_response_id"] = response_api_optional_params[
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"previous_response_id"
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]
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# Storage and lifecycle
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if response_api_optional_params.get("store") is not None:
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mapped_params["store"] = response_api_optional_params["store"]
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@ -184,52 +195,60 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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mapped_params["background"] = response_api_optional_params["background"]
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if response_api_optional_params.get("truncation"):
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mapped_params["truncation"] = response_api_optional_params["truncation"]
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# Metadata
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if response_api_optional_params.get("metadata"):
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mapped_params["metadata"] = response_api_optional_params["metadata"]
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if response_api_optional_params.get("safety_identifier"):
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mapped_params["safety_identifier"] = response_api_optional_params["safety_identifier"]
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mapped_params["safety_identifier"] = response_api_optional_params[
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"safety_identifier"
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]
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if response_api_optional_params.get("user"):
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mapped_params["user"] = response_api_optional_params["user"]
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# Additional
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if response_api_optional_params.get("top_logprobs") is not None:
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mapped_params["top_logprobs"] = response_api_optional_params["top_logprobs"]
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if response_api_optional_params.get("prompt_cache_key"):
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mapped_params["prompt_cache_key"] = response_api_optional_params["prompt_cache_key"]
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mapped_params["prompt_cache_key"] = response_api_optional_params[
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"prompt_cache_key"
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]
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if response_api_optional_params.get("frequency_penalty") is not None:
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mapped_params["frequency_penalty"] = response_api_optional_params["frequency_penalty"]
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mapped_params["frequency_penalty"] = response_api_optional_params[
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"frequency_penalty"
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]
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if response_api_optional_params.get("presence_penalty") is not None:
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mapped_params["presence_penalty"] = response_api_optional_params["presence_penalty"]
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mapped_params["presence_penalty"] = response_api_optional_params[
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"presence_penalty"
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]
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if response_api_optional_params.get("service_tier"):
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mapped_params["service_tier"] = response_api_optional_params["service_tier"]
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return mapped_params
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def _transform_tools(self, tools: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""
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Transform tools to Perplexity format.
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Perplexity supports (per public OpenAPI spec):
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- web_search: Performs web searches
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- fetch_url: Fetches content from URLs
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- function: Function Calling
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"""
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perplexity_tools = []
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for tool in tools:
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if isinstance(tool, dict):
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tool_type = tool.get("type", "")
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# Direct Perplexity tool format
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if tool_type in ["web_search", "fetch_url"]:
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perplexity_tools.append(tool)
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# Function tools: Perplexity supports them natively
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elif tool_type == "function":
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perplexity_tools.append(tool)
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return perplexity_tools
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def transform_responses_api_request(
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@ -262,24 +281,26 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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"model": model,
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"input": self._format_input(input),
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}
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# Add all optional parameters
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for key, value in response_api_optional_request_params.items():
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data[key] = value
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return data
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def _format_input(self, input: Union[str, ResponseInputParam]) -> Union[str, List[Dict[str, Any]]]:
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def _format_input(
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self, input: Union[str, ResponseInputParam]
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) -> Union[str, List[Dict[str, Any]]]:
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"""
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Format input for Perplexity Responses API
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The API accepts either:
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- A simple string for single-turn queries
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- An array of message objects for multi-turn conversations
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"""
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if isinstance(input, str):
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return input
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# Handle ResponseInputParam format
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if isinstance(input, list):
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formatted_messages = []
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@ -292,7 +313,7 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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}
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formatted_messages.append(formatted_message)
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return formatted_messages
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return str(input)
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def transform_response_api_response(
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@ -325,10 +346,14 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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# Transform usage to handle Perplexity's cost structure
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usage_data = raw_response_json.get("usage", {})
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transformed_usage_dict = self._transform_usage(usage_data)
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# Convert usage dict to ResponseAPIUsage object
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usage_obj = ResponseAPIUsage(**transformed_usage_dict) if transformed_usage_dict else None
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usage_obj = (
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ResponseAPIUsage(**transformed_usage_dict)
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if transformed_usage_dict
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else None
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)
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# Map Perplexity response to OpenAI Responses API format
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response = ResponsesAPIResponse(
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id=raw_response_json.get("id", ""),
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@ -341,11 +366,11 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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)
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return response
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def _transform_usage(self, usage_data: Dict[str, Any]) -> Dict[str, Any]:
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"""
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Transform Perplexity usage data to OpenAI format
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Perplexity returns:
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{
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"input_tokens": 100,
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@ -358,7 +383,7 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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"total_cost": 0.0003
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}
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}
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OpenAI expects:
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{
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"input_tokens": 100,
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@ -372,7 +397,7 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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"output_tokens": usage_data.get("output_tokens", 0),
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"total_tokens": usage_data.get("total_tokens", 0),
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}
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# Transform cost from Perplexity format (dict) to OpenAI format (float)
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cost_obj = usage_data.get("cost")
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if isinstance(cost_obj, dict) and "total_cost" in cost_obj:
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@ -380,20 +405,20 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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verbose_logger.debug(
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"Transformed Perplexity cost object to float: %s -> %s",
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cost_obj,
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cost_obj["total_cost"]
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cost_obj["total_cost"],
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)
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elif cost_obj is not None:
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# If cost is already a float/number, use it as-is
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transformed["cost"] = cost_obj
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# Add input_tokens_details if present
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if "input_tokens_details" in usage_data:
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transformed["input_tokens_details"] = usage_data["input_tokens_details"]
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# Add output_tokens_details if present
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if "output_tokens_details" in usage_data:
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transformed["output_tokens_details"] = usage_data["output_tokens_details"]
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return transformed
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def transform_streaming_response(
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@ -411,10 +436,10 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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event_pydantic_model = PerplexityResponsesConfig.get_event_model_class(
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event_type=event_type
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)
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# Transform Perplexity-specific fields to OpenAI format
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parsed_chunk = self._transform_perplexity_chunk(parsed_chunk)
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# Defensive: Handle error.code being null (similar to OpenAI implementation)
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try:
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error_obj = parsed_chunk.get("error")
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@ -433,13 +458,13 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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def _transform_perplexity_chunk(self, chunk: dict) -> dict:
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"""
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Transform Perplexity-specific fields in a streaming chunk to OpenAI format.
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This handles:
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- Converting Perplexity's cost object to a simple float
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"""
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# Make a copy to avoid modifying the original
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chunk = dict(chunk)
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# Transform usage.cost from Perplexity format to OpenAI format
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# Perplexity: {"currency": "USD", "input_cost": 0.0001, "output_cost": 0.0002, "total_cost": 0.0003}
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# OpenAI: 0.0003 (just the total_cost as a float)
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@ -458,10 +483,10 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig):
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verbose_logger.debug(
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"Transformed Perplexity cost object to float: %s -> %s",
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cost_obj,
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cost_obj["total_cost"]
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cost_obj["total_cost"],
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)
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except Exception as e:
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# If transformation fails, log and continue with original chunk
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verbose_logger.debug("Failed to transform Perplexity cost object: %s", e)
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return chunk
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@ -6,13 +6,12 @@ transformations for the Agent API (Responses API).
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Source: litellm/llms/perplexity/responses/transformation.py
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"""
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import os
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import sys
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sys.path.insert(0, os.path.abspath("../../../../.."))
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import pytest
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from litellm.llms.perplexity.responses.transformation import PerplexityResponsesConfig
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from litellm.types.llms.openai import ResponsesAPIOptionalRequestParams
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from litellm.types.utils import LlmProviders
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@ -37,7 +36,10 @@ class TestPerplexityResponsesTransformation:
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"type": "object",
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"properties": {
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"location": {"type": "string"},
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"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
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"unit": {
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"type": "string",
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"enum": ["celsius", "fahrenheit"],
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},
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},
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},
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},
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@ -55,7 +57,9 @@ class TestPerplexityResponsesTransformation:
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assert len(result["tools"]) == 1
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assert result["tools"][0]["type"] == "function"
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assert result["tools"][0]["function"]["name"] == "get_weather"
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assert result["tools"][0]["function"]["description"] == "Get the current weather"
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assert (
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result["tools"][0]["function"]["description"] == "Get the current weather"
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)
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assert "parameters" in result["tools"][0]["function"]
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def test_web_search_tool_passthrough(self):
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@ -123,7 +127,9 @@ class TestPerplexityResponsesTransformation:
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"""tool_choice passes through"""
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config = PerplexityResponsesConfig()
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params = ResponsesAPIOptionalRequestParams(tool_choice="required", temperature=0.7)
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params = ResponsesAPIOptionalRequestParams(
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tool_choice="required", temperature=0.7
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)
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result = config.map_openai_params(
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response_api_optional_params=params,
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@ -137,7 +143,9 @@ class TestPerplexityResponsesTransformation:
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"""parallel_tool_calls passes through"""
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config = PerplexityResponsesConfig()
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params = ResponsesAPIOptionalRequestParams(parallel_tool_calls=True, temperature=0.7)
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params = ResponsesAPIOptionalRequestParams(
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parallel_tool_calls=True, temperature=0.7
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)
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result = config.map_openai_params(
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response_api_optional_params=params,
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@ -169,7 +177,10 @@ class TestPerplexityResponsesTransformation:
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"format": {
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"type": "json_schema",
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"name": "weather_response",
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"schema": {"type": "object", "properties": {"temp": {"type": "number"}}},
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"schema": {
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"type": "object",
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||||
"properties": {"temp": {"type": "number"}},
|
||||
},
|
||||
"strict": True,
|
||||
}
|
||||
}
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue