SambaNova Systems Subagents API
The Subagents API from SambaNova Systems — 4 operation(s) for subagents.
OpenAPI Specification
openapi: 3.1.0
info:
title: Sambanova Agents Service Audio Subagents API
description: Service for Sambanova agents
version: 0.0.1
termsOfService: https://sambanova.ai/cloud-end-user-license-agreement
contact:
email: info@sambanova.ai
name: SambaNova information
license:
name: Apache 2.0
url: https://www.apache.org/licenses/LICENSE-2.0.html
servers:
- url: https://chat.sambanova.ai/api
security:
- api_key: []
tags:
- name: Subagents
paths:
/agent/coding:
post:
tags:
- Subagents
summary: Coding Agent
description: 'The coding agent executes Python code in a sandboxed environment, fixes errors, and returns results. This fire-and-forget endpoint submits a prompt and returns the final response in a single call.
'
operationId: coding_agent_agent_coding_post
security:
- api_key: []
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CodingAgentRequest'
responses:
'200':
description: Successful Response
content:
application/json:
schema:
$ref: '#/components/schemas/BaseAgentResponse'
'422':
description: Validation Error
content:
application/json:
schema:
$ref: '#/components/schemas/HTTPValidationError'
/agent/datascience:
post:
tags:
- Subagents
description: 'The data science agent analyzes datasets, generates visualizations, and produces comprehensive reports. This fire-and-forget endpoint submits a prompt and returns the final report in a single call.
'
operationId: datascience_agent_and_report_agent_datascience_post
security:
- api_key: []
requestBody:
content:
multipart/form-data:
schema:
$ref: '#/components/schemas/DatascienceAgentRequest'
required: true
responses:
'200':
content:
application/json:
schema:
$ref: '#/components/schemas/DataScienceAgentHTMLResponse'
description: Successful Response
'422':
content:
application/json:
schema:
$ref: '#/components/schemas/HTTPValidationError'
description: Validation Error
summary: Datascience Agent And Report
/agent/deepresearch:
post:
tags:
- Subagents
description: 'The deep research agent conducts multi-iteration research and produces comprehensive reports. This interactive endpoint uses a two-step workflow:
1. Submit a prompt to receive a thread_id and research plan for approval
2. Submit a prompt with thread_id and resume=true to generate the final report
'
operationId: deepresearch_agent_agent_deepresearch_post
security:
- api_key: []
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/DeepResearchRequest'
required: true
responses:
'200':
content:
application/json:
schema:
$ref: '#/components/schemas/BaseAgentResponse'
description: Successful Response
'422':
content:
application/json:
schema:
$ref: '#/components/schemas/HTTPValidationError'
description: Validation Error
summary: Deepresearch Agent
/agent/financialanalysis:
post:
tags:
- Subagents
summary: Financial Analysis Agent
description: 'The financial analysis agent analyzes stocks, companies, and market data. This fire-and-forget endpoint submits a prompt and returns the final response in a single call.
'
operationId: financial_analysis_agent_agent_financialanalysis_post
security:
- api_key: []
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/FinancialAnalysisRequest'
responses:
'200':
description: Successful Response
content:
application/json:
schema:
$ref: '#/components/schemas/BaseAgentResponse'
'422':
description: Validation Error
content:
application/json:
schema:
$ref: '#/components/schemas/HTTPValidationError'
components:
schemas:
CodingAgentRequest:
title: CodingAgentRequest
type: object
description: Request for coding agent json object
additionalProperties: false
properties:
code:
title: Code
description: Code to run
type: string
prompt:
title: Prompt
description: The main prompt for the coding agent
type: string
required:
- prompt
- code
examples:
- prompt: Run this code and explain the output
code: 'import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 2 * np.pi, 100)
y = np.sin(x)
plt.plot(x, y)
plt.savefig("sine_wave.png")
print("Chart created!")
'
DatascienceAgentRequest:
title: DatascienceAgentRequest
type: object
description: Request for data science agent json object
additionalProperties: false
properties:
files:
description: One or more files to be analyzed.
items:
format: binary
type: string
title: Files
type: array
prompt:
description: The main prompt for the data science agent.
title: Prompt
type: string
required:
- prompt
- files
examples:
- prompt: Perform exploratory data analysis on this dataset
files: '@dataset.csv'
ValidationError:
properties:
loc:
items:
anyOf:
- type: string
- type: integer
title: Location
type: array
msg:
title: Message
type: string
type:
title: Error Type
type: string
required:
- loc
- msg
- type
title: ValidationError
type: object
DeepResearchRequest:
title: DeepResearchRequest
type: object
description: Request for deep research agent json object
additionalProperties: false
properties:
prompt:
title: Prompt
description: The main prompt for the deep research agent
type: string
required:
- prompt
examples:
- prompt: Conduct research on quantum computing advances in 2024
DataScienceAgentHTMLResponse:
type: object
title: Data Science Agent HTML Response
description: Generated HTML report for exploratory data analysis (EDA)
additionalProperties: false
properties:
content_type:
title: content_type
description: MIME type of the generated report (should be 'text/html')
type: string
example: text/html
title:
title: title
description: Title of the analysis report
type: string
example: Data Science Analysis Report
html:
title: html
description: Full HTML content of the generated report
type: string
example: "<!DOCTYPE html>\n<html>\n<head>\n <title>Data Science Analysis Report</title>\n <style>/* Professional styling */</style>\n</head>\n<body>\n <h1>Exploratory Data Analysis Report</h1>\n <h2>Dataset Overview</h2>\n <p>The dataset contains 1,000 rows and 15 columns...</p>\n <h2>Statistical Summary</h2>\n <table><!-- Summary statistics --></table>\n <h2>Visualizations</h2>\n <img src=\"data:image/png;base64,...\" alt=\"Distribution Plot\">\n <img src=\"data:image/png;base64,...\" alt=\"Correlation Heatmap\">\n <h2>Key Findings</h2>\n <ul>\n <li>Strong correlation between features X and Y</li>\n <li>Missing values detected in column Z</li>\n </ul>\n</body>\n</html>\n"
required:
- content_type
- title
- html
FinancialAnalysisRequest:
title: FinancialAnalysisRequest
type: object
description: Request for financial agent json object
additionalProperties: false
properties:
prompt:
title: Prompt
description: The main prompt for the financial agent
type: string
required:
- prompt
examples:
- prompt: Perform a financial analysis of Apple
HTTPValidationError:
title: HTTPValidationError
type: object
properties:
detail:
items:
$ref: '#/components/schemas/ValidationError'
title: Detail
type: array
BaseAgentResponse:
type: object
title: Base agent response object
description: Base agent response object
additionalProperties: false
properties:
status:
title: status
description: status of agent gereneration
type: string
result:
title: result
description: results description
type: string
artifacts:
title: artifacts
description: generated artifacts
type: array
items:
type: string
description: id of generated artifact
thread_id:
title: thread_id
description: thread id for persistent context
type: string
required:
- status
- result
- artifacts
- thread_id
example:
status: success
result: I've created the bar chart...
artifacts:
- file-id-123
thread_id: thread-abc
securitySchemes:
api_key:
type: http
description: SambaNova API Key
scheme: bearer
bearerFormat: apiKey
externalDocs:
description: Find out more in the official SambaNova docs
url: https://docs.sambanova.ai/cloud/api-reference/overview