> ## Documentation Index > Fetch the complete documentation index at: https://docs.honeyhive.ai/llms.txt > Use this file to discover all available pages before exploring further. # Create a batch of events (deprecated) > Deprecated. Use `POST /v1/events/batch` instead. The legacy route accepts the deprecated `is_single_session` and `session` aliases and lets per-event objects carry the deprecated `project` field; the v1 route rejects all three at the SDK boundary. ## OpenAPI ````yaml post /events/batch openapi: 3.0.3 info: title: HoneyHive API version: 1.0.1 servers: - url: https://api.honeyhive.ai security: - BearerAuth: [] paths: /events/batch: post: tags: - Events summary: Create a batch of events description: Please refer to our instrumentation guide for detailed information operationId: createEventBatch requestBody: required: true content: application/json: schema: type: object properties: events: type: array items: $ref: '#/components/schemas/CreateEventRequest' is_single_session: type: boolean description: >- Default is false. If true, all events will be associated with the same session required: - events responses: '200': description: Events created content: application/json: schema: type: object properties: event_ids: type: array items: type: string session_id: type: string success: type: boolean example: event_ids: - 7f22137a-6911-4ed3-bc36-110f1dde6b66 - 7f22137a-6911-4ed3-bc36-110f1dde6b67 session_id: caf77ace-3417-4da4-944d-f4a0688f3c23 success: true '500': description: Events partially created content: application/json: schema: type: object properties: event_ids: type: array items: type: string errors: type: array items: type: string description: >- Any failure messages for events that could not be created success: type: boolean example: event_ids: - 7f22137a-6911-4ed3-bc36-110f1dde6b66 - 7f22137a-6911-4ed3-bc36-110f1dde6b67 errors: - Could not create event due to missing inputs - Could not create event due to missing source success: true x-codeSamples: - lang: python label: createEventBatch source: >- import honeyhive from honeyhive.models import components, operations s = honeyhive.HoneyHive( bearer_auth="", ) res = s.events.create_event_batch(request=operations.CreateEventBatchRequestBody( events=[ components.CreateEventRequest( project='Simple RAG', source='playground', event_name='Model Completion', event_type=components.CreateEventRequestEventType.MODEL, event_id='7f22137a-6911-4ed3-bc36-110f1dde6b66', session_id='caf77ace-3417-4da4-944d-f4a0688f3c23', parent_id='caf77ace-3417-4da4-944d-f4a0688f3c23', children_ids=[ '', ], config={ 'model': 'gpt-3.5-turbo', 'version': 'v0.1', 'provider': 'openai', 'hyperparameters': { 'temperature': 0, 'top_p': 1, 'max_tokens': 1000, 'presence_penalty': 0, 'frequency_penalty': 0, 'stop': [ '', ], 'n': 1, }, 'template': [ { 'role': 'system', 'content': 'Answer the user\'s question only using provided context. Context: {{ context }}', }, { 'role': 'user', 'content': '{{question}}', }, ], 'type': 'chat', }, inputs={ 'context': 'Hello world', 'question': 'What is in the context?', 'chat_history': [ { 'role': 'system', 'content': 'Answer the user\'s question only using provided context. Context: Hello world', }, { 'role': 'user', 'content': 'What is in the context?', }, ], }, outputs={ 'role': 'assistant', 'content': 'Hello world', }, error=None, start_time=1714978764301, end_time=1714978765301, duration=999.8056, metadata={ 'cost': 0.00008, 'completion_tokens': 23, 'prompt_tokens': 35, 'total_tokens': 58, }, feedback={ }, metrics={ 'Answer Faithfulness': 5, 'Answer Faithfulness_explanation': 'The AI assistant\'s answer is a concise and accurate description of Ramp\'s API. It provides a clear explanation of what the API does and how developers can use it to integrate Ramp\'s financial services into their own applications. The answer is faithful to the provided context.', 'Number of words': 18, }, user_properties={ 'user': 'google-oauth2|111840237613341303366', }, ), ], )) if res.object is not None: # handle response pass - lang: typescript label: createEventBatch source: >- import { HoneyHive } from "honeyhive"; import { CreateEventRequestEventType } from "honeyhive/dist/models/components"; async function run() { const sdk = new HoneyHive({ bearerAuth: "", }); const res = await sdk.events.createEventBatch({ events: [ { project: "Simple RAG", source: "playground", eventName: "Model Completion", eventType: CreateEventRequestEventType.Model, eventId: "7f22137a-6911-4ed3-bc36-110f1dde6b66", sessionId: "caf77ace-3417-4da4-944d-f4a0688f3c23", parentId: "caf77ace-3417-4da4-944d-f4a0688f3c23", childrenIds: [ "", ], config: { "model": "gpt-3.5-turbo", "version": "v0.1", "provider": "openai", "hyperparameters": { "temperature": 0, "top_p": 1, "max_tokens": 1000, "presence_penalty": 0, "frequency_penalty": 0, "stop": [ "", ], "n": 1, }, "template": [ { "role": "system", "content": "Answer the user's question only using provided context. Context: {{ context }}", }, { "role": "user", "content": "{{question}}", }, ], "type": "chat", }, inputs: { "context": "Hello world", "question": "What is in the context?", "chat_history": [ { "role": "system", "content": "Answer the user's question only using provided context. Context: Hello world", }, { "role": "user", "content": "What is in the context?", }, ], }, outputs: { "role": "assistant", "content": "Hello world", }, error: null, startTime: 1714978764301, endTime: 1714978765301, duration: 999.8056, metadata: { "cost": 0.00008, "completion_tokens": 23, "prompt_tokens": 35, "total_tokens": 58, }, feedback: { }, metrics: { "Answer Faithfulness": 5, "Answer Faithfulness_explanation": "The AI assistant's answer is a concise and accurate description of Ramp's API. It provides a clear explanation of what the API does and how developers can use it to integrate Ramp's financial services into their own applications. The answer is faithful to the provided context.", "Number of words": 18, }, userProperties: { "user": "google-oauth2|111840237613341303366", }, }, ], }); if (res.statusCode == 200) { // handle response } } run(); components: schemas: CreateEventRequest: type: object properties: project: type: string description: Project associated with the event source: type: string description: Source of the event - production, staging, etc event_name: type: string description: Name of the event event_type: type: string enum: - model - tool - chain description: Specify whether the event is of "model", "tool" or "chain" type event_id: type: string description: Unique id of the event, if not set, it will be auto-generated session_id: type: string description: >- Unique id of the session associated with the event, if not set, it will be auto-generated parent_id: type: string description: Id of the parent event if nested children_ids: type: array items: type: string description: Id of events that are nested within the event config: type: object additionalProperties: true description: >- Associated configuration JSON for the event - model name, vector index name, etc inputs: type: object additionalProperties: true description: Input JSON given to the event - prompt, chunks, etc properties: chat_history: type: array items: type: object additionalProperties: true description: Messages passed to the model outputs: type: object additionalProperties: true description: Final output JSON of the event error: type: string description: Any error description if event failed start_time: type: number description: UTC timestamp (in milliseconds) for the event start end_time: type: integer description: UTC timestamp (in milliseconds) for the event end duration: type: number description: How long the event took in milliseconds metadata: type: object additionalProperties: true description: Any system or application metadata associated with the event feedback: type: object additionalProperties: true description: Any user feedback provided for the event output metrics: type: object additionalProperties: true description: Any values computed over the output of the event user_properties: type: object additionalProperties: true description: Any user properties associated with the event required: - project - event_type - event_name - source - config - inputs - duration example: project: Simple RAG event_type: model event_name: Model Completion source: playground session_id: caf77ace-3417-4da4-944d-f4a0688f3c23 event_id: 7f22137a-6911-4ed3-bc36-110f1dde6b66 parent_id: caf77ace-3417-4da4-944d-f4a0688f3c23 children_ids: [] config: model: gpt-3.5-turbo version: v0.1 provider: openai hyperparameters: temperature: 0 top_p: 1 max_tokens: 1000 presence_penalty: 0 frequency_penalty: 0 stop: [] 'n': 1 template: - role: system content: |- Answer the user's question only using provided context. Context: {{ context }} - role: user content: '{{question}}' type: chat inputs: context: Hello world question: What is in the context? chat_history: - role: system content: |- Answer the user's question only using provided context. Context: Hello world - role: user content: What is in the context? outputs: role: assistant content: Hello world error: null start_time: 1714978764301 end_time: 1714978765301 duration: 999.8056 metadata: cost: 0.00008 completion_tokens: 23 prompt_tokens: 35 total_tokens: 58 feedback: {} metrics: Answer Faithfulness: 5 Answer Faithfulness_explanation: >- The AI assistant's answer is a concise and accurate description of Ramp's API. It provides a clear explanation of what the API does and how developers can use it to integrate Ramp's financial services into their own applications. The answer is faithful to the provided context. Number of words: 18 user_properties: user: google-oauth2|111840237613341303366 securitySchemes: BearerAuth: type: http scheme: bearer ````