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ratanon/claude-code

claude-code Dataset Description This dataset contains crawled documentation formatted for LLM training and RAG systems. Dataset Statistics Total Pages: 29 Total Words: 27764 Total Chunks: 29 Source URL: https://docs.anthropic.com/en/docs/claude-code/ Crawled Date: 2025-06-24T09:05:29.246208 Directory Structure llm_ready/ - Plain text files optimized for LLM training jsonl/ - JSONL format for fine-tuning chunks/ - Chunked content… See the full description on the dataset page: https://huggingface.co/datasets/ratanon/claude-code.

sourceHugging Faceupdated 1y agoView on Hugging Face
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en__docs__claude-code__third-party-integrations.jsonl2 linesDownload Raw Back to jsonl
1{"messages": [{"role": "system", "content": "You are a helpful assistant with knowledge about general topics."}, {"role": "user", "content": "What information do you have about Enterprise deployment overview - Anthropic?"}, {"role": "assistant", "content": "Anthropic home page English Search... Search... Navigation Deployment Enterprise deployment overview Welcome Developer Guide API Guide Claude Code Model Context Protocol (MCP) Resources Release Notes Documentation Developer Discord Support Getting started Overview Set up Quickstart Memory management Common workflows Build with Claude Add Claude Code to your IDE Model Context Protocol (MCP) GitHub Actions Claude Code SDK Troubleshooting Deployment Overview Amazon Bedrock Google Vertex AI Corporate proxy LLM gateway Development containers Administration Identity and Access Management Security Monitoring Costs Reference CLI reference Interactive mode Slash commands Settings Resources Data usage Legal and compliance This page provides an overview of available deployment options and helps you choose the right configuration for your organization.  Provider comparison Feature Anthropic Amazon Bedrock Google Vertex AI Regions Supported countries Multiple AWS regions Multiple GCP regions Prompt caching Enabled by default Enabled by default Contact Google for enablement Authentication API key AWS credentials (IAM) GCP credentials (OAuth/Service Account) Cost tracking Dashboard AWS Cost Explorer GCP Billing Enterprise features Teams, usage monitoring IAM policies, CloudTrail IAM roles, Cloud Audit Logs  Cloud providers Amazon Bedrock Use Claude models through AWS infrastructure with IAM-based authentication and AWS-native monitoring Google Vertex AI Access Claude models via Google Cloud Platform with enterprise-grade security and compliance  Corporate infrastructure Corporate Proxy Configure Claude Code to work with your organizations proxy servers and SSL/TLS requirements LLM Gateway Deploy centralized model access with usage tracking, budgeting, and audit logging  Configuration overview Claude Code supports flexible configuration options that allow you to combine different providers and infrastructure: Understand the difference between: Corporate proxy : An HTTP/HTTPS proxy for routing traffic (set via HTTPS_PROXY or HTTP_PROXY ) LLM Gateway : A service that handles authentication and provides provider-compatible endpoints (set via ANTHROPIC_BASE_URL , ANTHROPIC_BEDROCK_BASE_URL , or ANTHROPIC_VERTEX_BASE_URL ) Both configurations can be used in tandem.  Using Bedrock with corporate proxy Route Bedrock traffic through a corporate HTTP/HTTPS proxy: export CLAUDE_CODE_USE_BEDROCK = 1 export AWS_REGION = us-east-1 export HTTPS_PROXY = 'https://proxy.example.com:8080'  Using Bedrock with LLM Gateway Use a gateway service that provides Bedrock-compatible endpoints: export CLAUDE_CODE_USE_BEDROCK = 1 export ANTHROPIC_BEDROCK_BASE_URL = 'https://your-llm-gateway.com/bedrock' export CLAUDE_CODE_SKIP_BEDROCK_AUTH = 1  Using Vertex AI with corporate proxy Route Vertex AI traffic through a corporate HTTP/HTTPS proxy: export CLAUDE_CODE_USE_VERTEX = 1 export CLOUD_ML_REGION = us-east5 export ANTHROPIC_VERTEX_PROJECT_ID = your-project-id export HTTPS_PROXY = 'https://proxy.example.com:8080'  Using Vertex AI with LLM Gateway Combine Google Vertex AI models with an LLM gateway for centralized management: export CLAUDE_CODE_USE_VERTEX = 1 export ANTHROPIC_VERTEX_BASE_URL = 'https://your-llm-gateway.com/vertex' export CLAUDE_CODE_SKIP_VERTEX_AUTH = 1  Authentication configuration Claude Code uses the ANTHROPIC_AUTH_TOKEN for both Authorization and Proxy-Authorization headers when needed. The SKIP_AUTH flags ( CLAUDE_CODE_SKIP_BEDROCK_AUTH , CLAUDE_CODE_SKIP_VERTEX_AUTH ) are used in LLM gateway scenarios where the gateway handles provider authentication.  Choosing the right deployment configuration Consider these factors when selecting your deployment approach:  Direct provider access Best for organizations that: Want the simplest setup Have existing AWS or GCP infrastructure Need provider-native monitoring and compliance  Corporate proxy Best for organizations that: Have existing corporate proxy requirements Need traffic monitoring and compliance Must"}]}2