# Tensorlake

## Docs

- [Root](https://docs.tensorlake.ai/api-reference/root.md)
- [Create Dataset](https://docs.tensorlake.ai/api-reference/v2/datasets/create.md)
- [Data](https://docs.tensorlake.ai/api-reference/v2/datasets/data.md)
- [Delete](https://docs.tensorlake.ai/api-reference/v2/datasets/delete.md)
- [Get](https://docs.tensorlake.ai/api-reference/v2/datasets/get.md)
- [List Datasets](https://docs.tensorlake.ai/api-reference/v2/datasets/list.md)
- [Parse](https://docs.tensorlake.ai/api-reference/v2/datasets/parse.md)
- [Update a dataset's settings](https://docs.tensorlake.ai/api-reference/v2/datasets/update.md)
- [Edit Document](https://docs.tensorlake.ai/api-reference/v2/edit.md)
- [Delete file](https://docs.tensorlake.ai/api-reference/v2/files/delete.md)
- [Get file metadata](https://docs.tensorlake.ai/api-reference/v2/files/get-metadata.md)
- [List Files](https://docs.tensorlake.ai/api-reference/v2/files/list.md)
- [Upload File](https://docs.tensorlake.ai/api-reference/v2/files/upload.md)
- [Introduction](https://docs.tensorlake.ai/api-reference/v2/introduction.md): Tensorlake API Reference for Document Ingestion
- [Classify Document](https://docs.tensorlake.ai/api-reference/v2/parse/classify.md)
- [Delete Parse Jobs](https://docs.tensorlake.ai/api-reference/v2/parse/delete.md)
- [Extract Document](https://docs.tensorlake.ai/api-reference/v2/parse/extract.md)
- [Get Parse Result](https://docs.tensorlake.ai/api-reference/v2/parse/get.md)
- [List Parse Jobs](https://docs.tensorlake.ai/api-reference/v2/parse/list.md)
- [Parse](https://docs.tensorlake.ai/api-reference/v2/parse/parse.md)
- [Read Document](https://docs.tensorlake.ai/api-reference/v2/parse/read.md)
- [Architecture](https://docs.tensorlake.ai/applications/architecture.md): How Tensorlake's Application Runtime runs your code under the hood
- [Async Functions](https://docs.tensorlake.ai/applications/async-functions.md): Use Python async/await with Tensorlake async functions. Run them concurrently to optimize resource usage and reduce latency.
- [Building Workflows](https://docs.tensorlake.ai/applications/building-workflows.md): Build multi-step data workflows with parallel execution and optimized resource usage
- [SDK Reference](https://docs.tensorlake.ai/applications/concepts.md): Functions, applications, decorators, request context, and lifecycle reference
- [Crash Recovery](https://docs.tensorlake.ai/applications/crash-recovery.md): How agents survive failures and resume without losing work
- [Cron Scheduler](https://docs.tensorlake.ai/applications/cron-scheduler.md): Schedule recurring invocations of your Orchestration endpoints.
- [Durable Execution](https://docs.tensorlake.ai/applications/durability.md)
- [Error handling](https://docs.tensorlake.ai/applications/error-handling.md)
- [Futures](https://docs.tensorlake.ai/applications/futures.md): Use Futures to run multiple function calls in parallel to optimize resource usage and reduce latency.
- [Autoscaling](https://docs.tensorlake.ai/applications/guides/autoscaling.md): This content now lives in the Scaling Agents guide
- [Logging](https://docs.tensorlake.ai/applications/guides/logging.md)
- [Progress Updates](https://docs.tensorlake.ai/applications/guides/streaming-progress.md): Stream real-time progress updates from functions
- [Container Images](https://docs.tensorlake.ai/applications/images.md)
- [Introduction](https://docs.tensorlake.ai/applications/introduction.md): Add serverless orchestration to any agent
- [Map-Reduce](https://docs.tensorlake.ai/applications/map-reduce.md)
- [Observability](https://docs.tensorlake.ai/applications/observability.md): Built-in tracing, execution timelines and monitoring
- [Programming Agents](https://docs.tensorlake.ai/applications/overview.md): Core concepts and common patterns for running agents on Tensorlake
- [Parallel Sub-Agents](https://docs.tensorlake.ai/applications/parallel-sub-agents.md): Fan out work to specialist agents that run in parallel
- [Troubleshooting](https://docs.tensorlake.ai/applications/production/troubleshooting.md): Common issues building Tensorlake applications and how to debug them
- [Quickstart](https://docs.tensorlake.ai/applications/quickstart.md)
- [Retries & Rate Limits](https://docs.tensorlake.ai/applications/retries.md): Handle LLM rate limits, transient failures, and structured output validation with durable retries
- [Sandboxes](https://docs.tensorlake.ai/applications/sandboxes.md): Two patterns for running agents with isolated code execution
- [Scale-Out & Queuing](https://docs.tensorlake.ai/applications/scale-out-queuing.md): Workflows scale automatically as endpoints are called, with configurable scaling per function
- [Autoscaling](https://docs.tensorlake.ai/applications/scaling-agents.md): Autoscaling guide for Orchestration endpoints
- [Secrets](https://docs.tensorlake.ai/applications/secrets.md): Providing secrets to Tensorlake functions
- [Timeouts](https://docs.tensorlake.ai/applications/timeouts.md): How function timeouts work and how progress updates reset them
- [Claude](https://docs.tensorlake.ai/claude.md)
- [Create Datasets](https://docs.tensorlake.ai/document-ingestion/datasets/create.md)
- [Retrieve Dataset Data](https://docs.tensorlake.ai/document-ingestion/datasets/data.md): Retrieve the data stored in a Tensorlake Dataset.
- [Managing Files](https://docs.tensorlake.ai/document-ingestion/file-management/overview.md)
- [Overview](https://docs.tensorlake.ai/document-ingestion/overview.md)
- [Barcode Detection](https://docs.tensorlake.ai/document-ingestion/parsing/barcode.md): Detecting and decoding barcodes from document pages, returning type, value, and bounding boxes as structured output.
- [Chart Extraction](https://docs.tensorlake.ai/document-ingestion/parsing/chart-extraction.md): Extract structured, plottable data from charts embedded in documents — bar, line, scatter, and pie charts output as standardized JSON.
- [Docx Parsing with Tracked Changes](https://docs.tensorlake.ai/document-ingestion/parsing/docx-parsing.md): Learn how to parse Docx documents, including tracked changes and comments.
- [Edit Documents](https://docs.tensorlake.ai/document-ingestion/parsing/edit.md): Fill forms and modify documents
- [Cross-page Header Correction](https://docs.tensorlake.ai/document-ingestion/parsing/header-correction.md): Automatically detect and correct document header hierarchy across pages, even when OCR misidentifies header levels.
- [Key-Value Extraction](https://docs.tensorlake.ai/document-ingestion/parsing/key-value-extraction.md): Template-free extraction of structured field data from forms — text inputs, checkboxes, radio buttons, dropdowns, and signature lines.
- [On-premise deployment](https://docs.tensorlake.ai/document-ingestion/parsing/on-prem.md)
- [Page Classification](https://docs.tensorlake.ai/document-ingestion/parsing/page-classification.md): Classify pages using semantic descriptions in natural language
- [Parsed Document Reference](https://docs.tensorlake.ai/document-ingestion/parsing/parse-output.md): Understand the output from calling the Parse API.
- [Read Documents](https://docs.tensorlake.ai/document-ingestion/parsing/read.md)
- [Signature Detection](https://docs.tensorlake.ai/document-ingestion/parsing/signature.md): Detect signatures in documents
- [Structured Data Extraction](https://docs.tensorlake.ai/document-ingestion/parsing/structured-extraction.md)
- [Summarization](https://docs.tensorlake.ai/document-ingestion/parsing/summarization.md): Summarize Tables, Figures and Charts in Documents
- [Table Merging](https://docs.tensorlake.ai/document-ingestion/parsing/table-merging.md): Automatically merge table fragments that span multiple pages or columns into a single unified table for LLM-ready output.
- [Document Parsing Benchmarks](https://docs.tensorlake.ai/document-ingestion/production/benchmarks.md)
- [Integration Guide](https://docs.tensorlake.ai/document-ingestion/production/integration.md)
- [Quickstart](https://docs.tensorlake.ai/document-ingestion/quickstart.md)
- [Agent with Tool Calling](https://docs.tensorlake.ai/examples/agentic-applications/agent-with-tools.md): Build a Claude agent that orchestrates complex workflows using tool calls.
- [Code Interpreter Agent](https://docs.tensorlake.ai/examples/agentic-applications/code-interpreter.md): Build a secure code execution environment using Tensorlake and OpenAI.
- [Deep Research Agent](https://docs.tensorlake.ai/examples/agentic-applications/deep-research.md): Build a multi-agent deep research pipeline with Tensorlake and OpenAI.
- [Personal Finance Manager](https://docs.tensorlake.ai/examples/agentic-applications/personal-finance-manager.md): Build an AI-powered finance manager that parses statements and answers spending questions.
- [Weather Agent](https://docs.tensorlake.ai/examples/agentic-applications/weather-agent.md): Build a conversational weather agent using Tensorlake and OpenWeatherMap.
- [Web Scraper to MongoDB Atlas](https://docs.tensorlake.ai/examples/agentic-applications/web-scraper.md): Build a scalable web scraper that stores vector embeddings in MongoDB Atlas.
- [Bounding Boxes](https://docs.tensorlake.ai/examples/code-snippets/bounding-boxes.md)
- [Build Smart Document Understanding Agents with Tensorlake and OpenAI Agent SDK](https://docs.tensorlake.ai/examples/cookbooks/build-smarter-agents-with-doc-understanding.md)
- [Chonkie](https://docs.tensorlake.ai/examples/cookbooks/chonkie.md): Build semantic chunking pipelines that preserve context and respect document structure
- [Detect Buyer and Seller Signatures with Tensorlake SDK](https://docs.tensorlake.ai/examples/cookbooks/detect-buyer-and-seller-signatures-sdk.md)
- [Outlines](https://docs.tensorlake.ai/examples/cookbooks/outlines.md): Build schema-enforced document extraction pipelines with guaranteed valid outputs
- [Parse Resumes with Tensorlake](https://docs.tensorlake.ai/examples/cookbooks/resume-parsing.md)
- [Recipe Alert Slack if Buyer Has Not Signed](https://docs.tensorlake.ai/examples/cookbooks/signature-detection/alert-slack-buyer-not-signed.md)
- [Detect Buyer and Seller Signatures with the Tensorlake Playground](https://docs.tensorlake.ai/examples/cookbooks/signature-detection/detect-buyer-and-seller-signatures-playground.md)
- [Recipe Route to Manual Review if Seller Has Not Signed](https://docs.tensorlake.ai/examples/cookbooks/signature-detection/route-seller-not-signed.md)
- [Extract Structured Data from Images](https://docs.tensorlake.ai/examples/cookbooks/structured-extraction-from-images.md): Build an application that extracts structured data from driver's license images using OpenAI's vision model
- [Examples](https://docs.tensorlake.ai/examples/overview.md): Tutorials, cookbooks, and use cases for building with Tensorlake.
- [Product Scrapper](https://docs.tensorlake.ai/examples/tutorials/product-scraper.md): Learning how to leverage secrets and images on Tensorlake Serverless.
- [Query SEC Filings Stored in Databricks](https://docs.tensorlake.ai/examples/tutorials/query-sec-filings-databricks.md): Track how AI risk disclosures evolved across major tech companies from 2021-2025 by parsing SEC filings, extracting structured risk data, and running SQL analytics in Databricks.
- [Query SEC Filings Stored in MotherDuck](https://docs.tensorlake.ai/examples/tutorials/query-sec-filings-motherduck.md): Track how AI risk disclosures evolved across Microsoft, Google, and Meta from 2021-2025 by parsing 40 SEC filings, extracting structured risk data, and running SQL analytics in MotherDuck.
- [Real Estate Agent with LangGraph (using CLI)](https://docs.tensorlake.ai/examples/tutorials/real-estate-agent-with-langgraph-cli.md): Build a real estate agent using LangGraph to interact with purchase agreements and answer agent queries.
- [Workflow Tutorial](https://docs.tensorlake.ai/examples/tutorials/workflow-tutorial.md): Running an Hello World workflow on Tensorlake Serverless.
- [Directory of files faq](https://docs.tensorlake.ai/faqs/directory-of-files-faq.md)
- [Document Ignestion](https://docs.tensorlake.ai/faqs/document-ingestion-faq.md)
- [Supported File Types](https://docs.tensorlake.ai/faqs/supported-file-types-faq.md)
- [Workflows](https://docs.tensorlake.ai/faqs/workflows-faq.md)
- [ChromaDB](https://docs.tensorlake.ai/integrations/chroma.md): Build citation-aware RAG systems that trace every AI answer back to exact source locations
- [Databricks](https://docs.tensorlake.ai/integrations/databricks.md): Build serverless pipelines to ingest unstructured data into Databricks Data Intelligence Platform.
- [LangChain](https://docs.tensorlake.ai/integrations/langchain.md): Build agentic workflows that automatically parse documents on-demand
- [MotherDuck](https://docs.tensorlake.ai/integrations/motherduck.md): Build serverless pipelines to ingest unstructured data into DuckDB and MotherDuck.
- [Integrations](https://docs.tensorlake.ai/integrations/overview.md): Connect Tensorlake with your favorite AI frameworks, vector databases, and data platforms.
- [Qdrant](https://docs.tensorlake.ai/integrations/qdrant.md): Build RAG applications with richer embeddings from tables, figures, and structured metadata
- [Welcome to Tensorlake](https://docs.tensorlake.ai/introduction.md)
- [Deployment](https://docs.tensorlake.ai/opensource/ce_engine.md): Learn how to deploy the Workflow Engine on Your Own Infrastructure
- [Configuration](https://docs.tensorlake.ai/opensource/configuration.md)
- [Deployment](https://docs.tensorlake.ai/opensource/deployment.md)
- [Indexify](https://docs.tensorlake.ai/opensource/indexify.md): Open Source Compute Engine for Agentic Data Applications
- [Monitoring and Troubleshooting](https://docs.tensorlake.ai/opensource/monitoring.md)
- [Access Control](https://docs.tensorlake.ai/platform/access-control.md): Organization and project hierarchy, role-based permissions, and user management.
- [Authentication](https://docs.tensorlake.ai/platform/authentication.md): Learn how to make API requests to the Tensorlake APIs
- [Billing](https://docs.tensorlake.ai/platform/billing.md)
- [EU Endpoints](https://docs.tensorlake.ai/platform/eu-data-residency.md)
- [Overview](https://docs.tensorlake.ai/platform/playground/overview.md): Get started with the Tensorlake Cloud Playground
- [Sample Documents](https://docs.tensorlake.ai/platform/playground/sample-documents.md): Understand Tensorlake's capabilities through our sample documents, available in the Playground
- [Security Policies](https://docs.tensorlake.ai/platform/security.md)
- [Single Sign-On (SSO)](https://docs.tensorlake.ai/platform/sso.md): Configure and enforce SSO for your organization using OIDC or SAML 2.0 identity providers.
- [Configuration](https://docs.tensorlake.ai/platform/webhooks/configuration.md)
- [Webhooks](https://docs.tensorlake.ai/platform/webhooks/overview.md): Learn how to use webhooks to get notified when Tensorlake Jobs finishes.
- [Webhook Payload](https://docs.tensorlake.ai/platform/webhooks/payloads/document-ingestion.md)
- [Webhook Payload](https://docs.tensorlake.ai/platform/webhooks/payloads/workflows.md)
- [Signature Verification](https://docs.tensorlake.ai/platform/webhooks/signature-verification.md)
- [Testing Webhooks](https://docs.tensorlake.ai/platform/webhooks/testing.md)
- [Agentic Autoresearch Loop](https://docs.tensorlake.ai/sandboxes/agentic-autoresearch.md): Autonomously improve an ML training script overnight using an LLM agent that proposes code modifications, races them in parallel sandboxes, and hill-climbs toward lower validation loss.
- [Agentic Dungeons & Dragons](https://docs.tensorlake.ai/sandboxes/agentic-d&g.md): Build a dynamic D&D-style game where parallel AI agents act as scene writers and a Dungeon Master agent orchestrates the story.
- [Reproducible Environments for RL Rollouts](https://docs.tensorlake.ai/sandboxes/agentic-rl-reproducible-env.md): Use Tensorlake sandboxes to guarantee isolated, deterministic rollouts for reinforcement learning training.
- [Agentic Swarm Intelligence](https://docs.tensorlake.ai/sandboxes/agentic-swarm-intelligence.md): Orchestrate a swarm of LLM agents running specialized tasks in parallel sandboxes.
- [AI Code Execution](https://docs.tensorlake.ai/sandboxes/ai-code-execution.md): Run LLM-generated code in isolated containers with network restrictions and resource limits. Integrate sandboxes as tools in agentic workflows.
- [CICD & Build Systems](https://docs.tensorlake.ai/sandboxes/cicd-build.md): Execute build steps and run tests in isolated, reproducible environments.
- [Execute Commands](https://docs.tensorlake.ai/sandboxes/commands.md): Run commands with output capture, streaming, and error handling
- [Data Analysis](https://docs.tensorlake.ai/sandboxes/data-analysis.md): Perform parallel data analysis and model benchmarking in isolated sandboxes.
- [File Operations](https://docs.tensorlake.ai/sandboxes/file-operations.md): Copy, read, write, and manage files in sandboxes
- [RL Training with GSPO](https://docs.tensorlake.ai/sandboxes/gspo-agentic-rl.md): Fine-tune a language model on code generation tasks using Group Sequence Policy Optimization, with TensorLake sandboxes as the reward oracle.
- [Sandboxes](https://docs.tensorlake.ai/sandboxes/introduction.md): Isolated and stateful execution environments for your agents.
- [Lifecycle](https://docs.tensorlake.ai/sandboxes/lifecycle.md): Sandbox states, resource configuration, timeouts, and lifecycle operations
- [Networking](https://docs.tensorlake.ai/sandboxes/networking.md): Control internet access and block specific outbound destinations for sandboxes
- [Process Management](https://docs.tensorlake.ai/sandboxes/processes.md): Start, monitor, and manage background processes in sandboxes
- [Snapshots](https://docs.tensorlake.ai/sandboxes/snapshots.md): Save and restore sandbox filesystem and memory state
- [Templates](https://docs.tensorlake.ai/sandboxes/templates.md): Create reusable named starting points for sandboxes from application images.
- [Parsing ACORD Forms for Insurance Workflows](https://docs.tensorlake.ai/use-cases/insurance-financial-services/acord-form-processing.md)

## OpenAPI Specs

- [openapi](https://docs.tensorlake.ai/api-reference/openapi.yaml)
- [package](https://docs.tensorlake.ai/package.json)
- [package-lock](https://docs.tensorlake.ai/package-lock.json)
- [settings](https://docs.tensorlake.ai/.vscode/settings.json)


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