fix: allow gen_ai.request.seed to accept both string and integer types

schemas/llm_span_attributes.json

@@ -163,7 +163,7 @@
       "description": "The number of search units used in the request."
     },
     "gen_ai.request.seed": {
-      "type": "string",
+      "type": ["string", "integer"],
       "description": "Seed from the input request"
     },
     "gen_ai.request.frequency_penalty": {
@@ -240,4 +240,4 @@
     "url.full",
     "url.path"
   ]
-}
+}

scripts/generate_python.sh

@@ -15,6 +15,7 @@ SCHEMA_NAME="${SCHEMA_FILENAME%.*}"
 OUTPUT_FILE="src/python/langtrace/trace_attributes/models/${SCHEMA_NAME}.py"
 
 # Generate the Python model
-datamodel-codegen --input "$SCHEMA_FILE" --input-file-type jsonschema --output "$OUTPUT_FILE"
+datamodel-codegen --input "$SCHEMA_FILE" --input-file-type jsonschema --output "$OUTPUT_FILE" \
+  --output-model-type pydantic_v2.BaseModel --allow-extra-fields
 
 echo "Generated Python model at: $OUTPUT_FILE"

setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name="trace-attributes",  # Choose a unique name for PyPI
-    version="7.1.1",
+    version="7.1.2",
     author="Karthik Kalyanaraman",
     author_email="karthik@scale3labs.com",
     description="LangTrace - Trace Attributes",

src/python/langtrace/trace_attributes/models/llm_span_attributes.py

@@ -1,237 +1,241 @@
 # generated by datamodel-codegen:
 #   filename:  llm_span_attributes.json
-#   timestamp: 2024-07-24T15:56:12+00:00
+#   timestamp: 2025-01-28T14:02:08+00:00
 
 from __future__ import annotations
 
-from typing import List, Optional
+from typing import List, Optional, Union
 
 from pydantic import BaseModel, ConfigDict, Field
 
 
 class LLMSpanAttributes(BaseModel):
-    model_config = ConfigDict(extra="allow")
-
+    model_config = ConfigDict(
+        extra='allow',
+    )
+    langtrace_span_name: Optional[str] = Field(
+        None, alias='langtrace.span.name', description='Name of the span'
+    )
     langtrace_service_name: str = Field(
         ...,
-        alias="langtrace.service.name",
-        description="Name of the service. Includes all supported service providers by langtrace",
+        alias='langtrace.service.name',
+        description='Name of the service. Includes all supported service providers by langtrace',
     )
     langtrace_service_type: str = Field(
         ...,
-        alias="langtrace.service.type",
-        description="Type of the service. Allowed values: [llm, vectordb, framework]",
+        alias='langtrace.service.type',
+        description='Type of the service. Allowed values: [llm, vectordb, framework]',
     )
     langtrace_service_version: Optional[str] = Field(
         None,
-        alias="langtrace.service.version",
-        description="Version of the service provider client",
+        alias='langtrace.service.version',
+        description='Version of the service provider client',
     )
-    langtrace_version: str = Field(..., alias="langtrace.version")
-    langtrace_sdk_name: str = Field(..., alias="langtrace.sdk.name")
-    url_full: str = Field(..., alias="url.full", description="Full URL of the request")
-    url_path: str = Field(..., alias="url.path", description="Path of the request")
+    langtrace_version: str = Field(..., alias='langtrace.version')
+    langtrace_sdk_name: str = Field(..., alias='langtrace.sdk.name')
+    url_full: str = Field(..., alias='url.full', description='Full URL of the request')
+    url_path: str = Field(..., alias='url.path', description='Path of the request')
     gen_ai_operation_name: str = Field(
         ...,
-        alias="gen_ai.operation.name",
-        description="The name of the operation being performed.",
+        alias='gen_ai.operation.name',
+        description='The name of the operation being performed.',
     )
     gen_ai_request_model: str = Field(
         ...,
-        alias="gen_ai.request.model",
-        description="Model name from the input request",
+        alias='gen_ai.request.model',
+        description='Model name from the input request',
     )
     gen_ai_response_model: Optional[str] = Field(
-        None, alias="gen_ai.response.model", description="Model name from the response"
+        None, alias='gen_ai.response.model', description='Model name from the response'
     )
     gen_ai_request_temperature: Optional[float] = Field(
         None,
-        alias="gen_ai.request.temperature",
-        description="Temperature value from the input request",
+        alias='gen_ai.request.temperature',
+        description='Temperature value from the input request',
     )
     gen_ai_request_logit_bias: Optional[str] = Field(
         None,
-        alias="gen_ai.request.logit_bias",
-        description="Likelihood bias of the specified tokens the input request.",
+        alias='gen_ai.request.logit_bias',
+        description='Likelihood bias of the specified tokens the input request.',
     )
     gen_ai_request_logprobs: Optional[bool] = Field(
         None,
-        alias="gen_ai.request.logprobs",
-        description="Logprobs flag returns log probabilities.",
+        alias='gen_ai.request.logprobs',
+        description='Logprobs flag returns log probabilities.',
     )
     gen_ai_request_top_logprobs: Optional[float] = Field(
         None,
-        alias="gen_ai.request.top_logprobs",
-        description="Integer between 0 and 5 specifying the number of most likely tokens to return.",
+        alias='gen_ai.request.top_logprobs',
+        description='Integer between 0 and 5 specifying the number of most likely tokens to return.',
     )
     gen_ai_request_top_p: Optional[float] = Field(
         None,
-        alias="gen_ai.request.top_p",
-        description="Top P value from the input request",
+        alias='gen_ai.request.top_p',
+        description='Top P value from the input request',
     )
     gen_ai_request_top_k: Optional[float] = Field(
         None,
-        alias="gen_ai.request.top_k",
-        description="Top K results to return from the input request",
+        alias='gen_ai.request.top_k',
+        description='Top K results to return from the input request',
     )
     gen_ai_user: Optional[str] = Field(
-        None, alias="gen_ai.user", description="User ID from the input request"
+        None, alias='gen_ai.user', description='User ID from the input request'
     )
     gen_ai_prompt: Optional[str] = Field(
-        None, alias="gen_ai.prompt", description="Prompt text from the input request"
+        None, alias='gen_ai.prompt', description='Prompt text from the input request'
     )
     gen_ai_completion: Optional[str] = Field(
         None,
-        alias="gen_ai.completion",
+        alias='gen_ai.completion',
         description='Completion text from the response. This will be an array of json objects with the following format {"role": "", "content": ""}. Role can be one of the following values: [system, user, assistant, tool]',
     )
     gen_ai_request_stream: Optional[bool] = Field(
         None,
-        alias="gen_ai.request.stream",
-        description="Stream flag from the input request",
+        alias='gen_ai.request.stream',
+        description='Stream flag from the input request',
     )
     gen_ai_request_encoding_formats: Optional[List[str]] = Field(
         None,
-        alias="gen_ai.request.encoding_formats",
+        alias='gen_ai.request.encoding_formats',
         description="Encoding formats from the input request. Allowed values: ['float', 'int8','uint8', 'binary', 'ubinary', 'base64']",
     )
     gen_ai_completion_chunk: Optional[str] = Field(
         None,
-        alias="gen_ai.completion.chunk",
-        description="Chunk text from the response",
+        alias='gen_ai.completion.chunk',
+        description='Chunk text from the response',
     )
     gen_ai_request_dimensions: Optional[float] = Field(
         None,
-        alias="gen_ai.request.dimensions",
-        description="Dimensions from the input request",
+        alias='gen_ai.request.dimensions',
+        description='Dimensions from the input request',
     )
     gen_ai_response_id: Optional[str] = Field(
         None,
-        alias="gen_ai.response_id",
-        description="Response ID from the output response",
+        alias='gen_ai.response_id',
+        description='Response ID from the output response',
     )
     gen_ai_response_finish_reasons: Optional[List[str]] = Field(
         None,
-        alias="gen_ai.response.finish_reasons",
-        description="Array of reasons the model stopped generating tokens, corresponding to each generation received",
+        alias='gen_ai.response.finish_reasons',
+        description='Array of reasons the model stopped generating tokens, corresponding to each generation received',
     )
     gen_ai_system_fingerprint: Optional[str] = Field(
         None,
-        alias="gen_ai.system_fingerprint",
-        description="System fingerprint of the system that generated the response",
+        alias='gen_ai.system_fingerprint',
+        description='System fingerprint of the system that generated the response',
     )
     gen_ai_request_documents: Optional[str] = Field(
         None,
-        alias="gen_ai.request.documents",
-        description="Array of documents from the input request json stringified",
+        alias='gen_ai.request.documents',
+        description='Array of documents from the input request json stringified',
     )
     gen_ai_request_is_search_required: Optional[bool] = Field(
         None,
-        alias="gen_ai.request.is_search_required",
-        description="Search flag from the input request",
+        alias='gen_ai.request.is_search_required',
+        description='Search flag from the input request',
     )
     gen_ai_request_tool_choice: Optional[str] = Field(
         None,
-        alias="gen_ai.request.tool_choice",
-        description="Tool choice from the input request",
+        alias='gen_ai.request.tool_choice',
+        description='Tool choice from the input request',
     )
     gen_ai_response_tool_calls: Optional[str] = Field(
         None,
-        alias="gen_ai.response.tool_calls",
-        description="Array of tool calls from the response json stringified",
+        alias='gen_ai.response.tool_calls',
+        description='Array of tool calls from the response json stringified',
     )
     gen_ai_request_max_tokens: Optional[float] = Field(
         None,
-        alias="gen_ai.request.max_tokens",
-        description="The maximum number of tokens the LLM generates for a request.",
+        alias='gen_ai.request.max_tokens',
+        description='The maximum number of tokens the LLM generates for a request.',
     )
     gen_ai_usage_input_tokens: Optional[float] = Field(
         None,
-        alias="gen_ai.usage.input_tokens",
-        description="The number of tokens used in the llm prompt.",
+        alias='gen_ai.usage.input_tokens',
+        description='The number of tokens used in the llm prompt.',
     )
     gen_ai_usage_total_tokens: Optional[float] = Field(
         None,
-        alias="gen_ai.usage.total_tokens",
-        description="The total number of tokens used in the llm request.",
+        alias='gen_ai.usage.total_tokens',
+        description='The total number of tokens used in the llm request.',
     )
     gen_ai_usage_output_tokens: Optional[float] = Field(
         None,
-        alias="gen_ai.usage.output_tokens",
-        description="The number of tokens in the llm response.",
+        alias='gen_ai.usage.output_tokens',
+        description='The number of tokens in the llm response.',
     )
     gen_ai_usage_search_units: Optional[float] = Field(
         None,
-        alias="gen_ai.usage.search_units",
-        description="The number of search units used in the request.",
+        alias='gen_ai.usage.search_units',
+        description='The number of search units used in the request.',
     )
-    gen_ai_request_seed: Optional[str | int] = Field(
-        None, alias="gen_ai.request.seed", description="Seed from the input request"
+    gen_ai_request_seed: Optional[Union[str, int]] = Field(
+        None, alias='gen_ai.request.seed', description='Seed from the input request'
     )
     gen_ai_request_frequency_penalty: Optional[float] = Field(
         None,
-        alias="gen_ai.request.frequency_penalty",
-        description="Frequency penalty from the input request",
+        alias='gen_ai.request.frequency_penalty',
+        description='Frequency penalty from the input request',
     )
     gen_ai_request_presence_penalty: Optional[float] = Field(
         None,
-        alias="gen_ai.request.presence_penalty",
-        description="Presence penalty from the input request",
+        alias='gen_ai.request.presence_penalty',
+        description='Presence penalty from the input request',
     )
     gen_ai_request_connectors: Optional[str] = Field(
         None,
-        alias="gen_ai.request.connectors",
-        description="An array of connectors from the input request json stringified",
+        alias='gen_ai.request.connectors',
+        description='An array of connectors from the input request json stringified',
     )
     gen_ai_request_tools: Optional[str] = Field(
         None,
-        alias="gen_ai.request.tools",
-        description="An array of tools from the input request json stringified",
+        alias='gen_ai.request.tools',
+        description='An array of tools from the input request json stringified',
     )
     gen_ai_request_tool_results: Optional[str] = Field(
         None,
-        alias="gen_ai.request.tool_results",
-        description="An array of tool results from the input request json stringified",
+        alias='gen_ai.request.tool_results',
+        description='An array of tool results from the input request json stringified',
     )
     gen_ai_request_embedding_inputs: Optional[str] = Field(
         None,
-        alias="gen_ai.request.embedding_inputs",
-        description="An array of embedding inputs from the input request json stringified",
+        alias='gen_ai.request.embedding_inputs',
+        description='An array of embedding inputs from the input request json stringified',
     )
     gen_ai_request_embedding_dataset_id: Optional[str] = Field(
         None,
-        alias="gen_ai.request.embedding_dataset_id",
-        description="Embedding dataset ID from the input request",
+        alias='gen_ai.request.embedding_dataset_id',
+        description='Embedding dataset ID from the input request',
     )
     gen_ai_request_embedding_input_type: Optional[str] = Field(
         None,
-        alias="gen_ai.request.embedding_input_type",
+        alias='gen_ai.request.embedding_input_type',
         description="Embedding input type from the input request. Allowed values: [ 'search_document', 'search_query', 'classification', 'clustering']",
     )
     gen_ai_request_embedding_job_name: Optional[str] = Field(
         None,
-        alias="gen_ai.request.embedding_job_name",
-        description="Embedding job name from the input request",
+        alias='gen_ai.request.embedding_job_name',
+        description='Embedding job name from the input request',
     )
     gen_ai_image_size: Optional[str] = Field(
         None,
-        alias="gen_ai.image.size",
+        alias='gen_ai.image.size',
         description="Image size from the input request. Allowed values: ['256x256', '512x512', '1024x1024']",
     )
     gen_ai_request_response_format: Optional[str] = Field(
         None,
-        alias="gen_ai.request.response_format",
+        alias='gen_ai.request.response_format',
         description="Response format from the input request. Allowed values: ['url', 'b64_json']",
     )
-    http_max_retries: Optional[int] = Field(None, alias="http.max.retries")
-    http_timeout: Optional[int] = Field(None, alias="http.timeout")
+    http_max_retries: Optional[int] = Field(None, alias='http.max.retries')
+    http_timeout: Optional[int] = Field(None, alias='http.timeout')
     gen_ai_cohere_rerank_query: Optional[str] = Field(
         None,
-        alias="gen_ai.cohere.rerank.query",
-        description="Query from the input request for the rerank api",
+        alias='gen_ai.cohere.rerank.query',
+        description='Query from the input request for the rerank api',
     )
     gen_ai_cohere_rerank_results: Optional[str] = Field(
         None,
-        alias="gen_ai.cohere.rerank.results",
-        description="Results from the rerank api",
+        alias='gen_ai.cohere.rerank.results',
+        description='Results from the rerank api',
     )

src/typescript/models/llm_span_attributes.d.ts

@@ -147,7 +147,7 @@ export interface LLMSpanAttributes {
   /**
    * Seed from the input request
    */
-  "gen_ai.request.seed"?: string;
+  "gen_ai.request.seed"?: string | number;
   /**
    * Frequency penalty from the input request
    */