feat(llm): mask API keys in UI responses and prevent masked-key leakage in fetch/test/save payloads
- Add mask_api_key() and is_masked_or_placeholder() to llm_provider service - Return masked keys in all provider CRUD endpoints - Reject masked/placeholder keys in fetch_models and test_provider_config - Show masked key with Change button in ProviderConfig.svelte edit form - Exclude masked keys from fetch-models, test, and submit payloads on frontend - Update semantics-core skill with clarified complexity tier rules - Switch agent modes from subagent to all
This commit is contained in:
248
docs/openapi/litellm/chunks_paths/paths_utils.json
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248
docs/openapi/litellm/chunks_paths/paths_utils.json
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{
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"/utils/dotprompt_json_converter": {
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"post": {
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"tags": [
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"prompts",
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"utils"
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],
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"summary": "Convert Prompt File To Json",
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"description": "Convert a .prompt file to JSON format.\n\nThis endpoint accepts a .prompt file upload and returns the equivalent JSON representation\nthat can be stored in a database or used programmatically.\n\nReturns the JSON structure with 'content' and 'metadata' fields.",
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"operationId": "convert_prompt_file_to_json_utils_dotprompt_json_converter_post",
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"requestBody": {
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"content": {
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"multipart/form-data": {
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"schema": {
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"$ref": "#/components/schemas/Body_convert_prompt_file_to_json_utils_dotprompt_json_converter_post"
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}
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}
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},
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"required": true
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},
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"responses": {
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"200": {
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"description": "Successful Response",
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"content": {
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"application/json": {
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"schema": {
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"additionalProperties": true,
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"type": "object",
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"title": "Response Convert Prompt File To Json Utils Dotprompt Json Converter Post"
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}
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}
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}
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},
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"422": {
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"description": "Validation Error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/HTTPValidationError"
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}
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}
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}
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}
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},
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"security": [
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{
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"APIKeyHeader": []
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}
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]
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}
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},
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"/utils/supported_openai_params": {
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"get": {
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"tags": [
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"llm utils"
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],
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"summary": "Supported Openai Params",
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"description": "Returns supported openai params for a given litellm model name\n\ne.g. `gpt-4` vs `gpt-3.5-turbo`\n\nExample curl:\n```\ncurl -X GET --location 'http://localhost:4000/utils/supported_openai_params?model=gpt-3.5-turbo-16k' --header 'Authorization: Bearer sk-1234'\n```",
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"operationId": "supported_openai_params_utils_supported_openai_params_get",
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"security": [
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{
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"APIKeyHeader": []
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}
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],
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"parameters": [
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{
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"name": "model",
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"in": "query",
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"required": true,
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"schema": {
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"type": "string",
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"title": "Model"
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}
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}
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],
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"responses": {
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"200": {
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"description": "Successful Response",
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"content": {
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"application/json": {
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"schema": {}
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}
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}
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},
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"422": {
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"description": "Validation Error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/HTTPValidationError"
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}
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}
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}
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}
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}
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}
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},
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"/utils/test_policies_and_guardrails": {
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"post": {
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"tags": [
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"utils"
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],
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"summary": "Test Policies And Guardrails",
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"description": "Apply policies and/or guardrails to inputs (for compliance UI testing).\n\nUse inputs_list for batch testing: each input is processed as a separate call so\nper-input block/allow and errors are returned.\n\nUse inputs for a single call (legacy).",
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"operationId": "test_policies_and_guardrails_utils_test_policies_and_guardrails_post",
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"requestBody": {
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/TestPoliciesAndGuardrailsRequest"
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}
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}
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},
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"required": true
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},
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"responses": {
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"200": {
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"description": "Successful Response",
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"content": {
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"application/json": {
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"schema": {}
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}
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}
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},
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"422": {
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"description": "Validation Error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/HTTPValidationError"
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}
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}
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}
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}
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},
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"security": [
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{
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"APIKeyHeader": []
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}
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]
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}
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},
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"/utils/token_counter": {
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"post": {
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"tags": [
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"llm utils"
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],
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"summary": "Token Counter",
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"description": "Args:\n request: TokenCountRequest\n call_endpoint: bool - When set to \"True\" it will call the token counting endpoint - e.g Anthropic or Google AI Studio Token Counting APIs.\n\nReturns:\n TokenCountResponse",
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"operationId": "token_counter_utils_token_counter_post",
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"security": [
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{
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"APIKeyHeader": []
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}
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],
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"parameters": [
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{
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"name": "call_endpoint",
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"in": "query",
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"required": false,
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"schema": {
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"type": "boolean",
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"default": false,
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"title": "Call Endpoint"
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}
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}
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],
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"requestBody": {
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"required": true,
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/TokenCountRequest"
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}
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}
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}
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},
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"responses": {
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"200": {
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"description": "Successful Response",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/TokenCountResponse"
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}
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}
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}
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},
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"422": {
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"description": "Validation Error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/HTTPValidationError"
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}
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}
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}
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}
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}
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}
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},
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"/utils/transform_request": {
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"post": {
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"tags": [
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"llm utils"
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],
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"summary": "Transform Request",
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"operationId": "transform_request_utils_transform_request_post",
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"requestBody": {
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/TransformRequestBody"
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}
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}
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},
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"required": true
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},
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"responses": {
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"200": {
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"description": "Successful Response",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/RawRequestTypedDict"
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}
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}
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}
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},
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"422": {
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"description": "Validation Error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/HTTPValidationError"
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}
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}
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}
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}
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},
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"security": [
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{
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"APIKeyHeader": []
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}
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]
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}
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}
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}
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