{ "model_id": "anthropic/claude-opus-4.7", "provider_id": "anthropic", "name": "Claude Opus 4.7", "description": "Claude Opus 4.7 is Anthropic's most capable generally available model, with a step-change improvement in agentic coding over Claude Opus 4.6. It uses adaptive thinking to calibrate reasoning per task and supports a one million token context window at standard pricing.", "task": "Text Generation", "tags": [ "LLM", "Coding", "Reasoning", "Enterprise", "Agentic", "Financial Analysis", "Legal" ], "context_length": 1000000, "max_output_tokens": 128000, "schema_version": "1.0.0", "pricing": { "Input tokens (per 1M)": 5, "Output tokens (per 1M)": 25, "Cached input tokens (per 1M)": 0.5, "Cache creation tokens (per 1M)": 6.25 }, "examples": [ { "name": "Simple Question", "description": "Basic message request", "input": { "max_tokens": 1024, "messages": [ { "content": "What are the three laws of thermodynamics?", "role": "user" } ] }, "output": { "text": "# The Three Laws of Thermodynamics\n\n**First Law (Conservation of Energy):**\nEnergy cannot be created or destroyed, only transformed from one form to another. The total energy of an isolated system remains constant.\n- Often expressed as: \u0394U = Q \u2212 W (change in internal energy equals heat added minus work done by the system)\n\n**Second Law (Entropy):**\nThe total entropy (disorder) of an isolated system always increases over time, or remains constant in ideal reversible processes. Heat naturally flows from hot to cold, never the reverse without external work.\n- This law explains why perpetual motion machines are impossible and why processes have a preferred direction.\n\n**Third Law (Absolute Zero):**\nAs a system approaches absolute zero (0 Kelvin or \u2212273.15\u00b0C), its entropy approaches a minimum constant value. It's impossible to reach absolute zero in a finite number of steps.\n- A perfect crystal at absolute zero would have zero entropy.\n\n**Bonus \u2014 Zeroth Law:**\nOften mentioned alongside these: if two systems are each in thermal equilibrium with a third system, they are in thermal equilibrium with each other. This is the basis for temperature measurement." }, "raw_response": { "content": [ { "text": "# The Three Laws of Thermodynamics\n\n**First Law (Conservation of Energy):**\nEnergy cannot be created or destroyed, only transformed from one form to another. The total energy of an isolated system remains constant.\n- Often expressed as: \u0394U = Q \u2212 W (change in internal energy equals heat added minus work done by the system)\n\n**Second Law (Entropy):**\nThe total entropy (disorder) of an isolated system always increases over time, or remains constant in ideal reversible processes. Heat naturally flows from hot to cold, never the reverse without external work.\n- This law explains why perpetual motion machines are impossible and why processes have a preferred direction.\n\n**Third Law (Absolute Zero):**\nAs a system approaches absolute zero (0 Kelvin or \u2212273.15\u00b0C), its entropy approaches a minimum constant value. It's impossible to reach absolute zero in a finite number of steps.\n- A perfect crystal at absolute zero would have zero entropy.\n\n**Bonus \u2014 Zeroth Law:**\nOften mentioned alongside these: if two systems are each in thermal equilibrium with a third system, they are in thermal equilibrium with each other. This is the basis for temperature measurement.", "type": "text" } ], "gatewayMetadata": { "keySource": "BYOK" }, "id": "msg_013pmj6hy6QcjydL7goWQBZ7", "model": "claude-opus-4-7", "role": "assistant", "stop_details": null, "stop_reason": "end_turn", "stop_sequence": null, "type": "message", "usage": { "input_tokens": 25, "output_tokens": 399 } }, "code_snippets": [ { "label": "typescript", "language": "typescript", "code": "const response = await env.AI.run(\n 'anthropic/claude-opus-4.7',\n {\n max_tokens: 1024,\n messages: [{ content: 'What are the three laws of thermodynamics?', role: 'user' }],\n },\n)\nconsole.log(response)" }, { "label": "curl", "language": "bash", "code": "curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/v1/messages \\\n --header \"Authorization: Bearer $CLOUDFLARE_API_TOKEN\" \\\n --header \"Content-Type: application/json\" \\\n --data '{\n \"model\": \"anthropic/claude-opus-4.7\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"content\": \"What are the three laws of thermodynamics?\",\n \"role\": \"user\"\n }\n ]\n}'" } ] }, { "name": "With System Message", "description": "Using a system message to set context", "input": { "max_tokens": 1024, "messages": [ { "content": "How do I read a JSON file in Python?", "role": "user" } ], "system": "You are a helpful coding assistant specializing in Python." }, "output": { "text": "# Reading a JSON File in Python\n\nPython has a built-in `json` module that makes reading JSON files straightforward.\n\n## Basic Example\n\n```python\nimport json\n\nwith open('data.json', 'r') as file:\n data = json.load(file)\n\nprint(data)\n```\n\n## Key Points\n\n- **`json.load()`** reads from a file object and parses JSON into Python objects\n- **`json.loads()`** (with an \"s\") parses JSON from a string\n- JSON objects become Python **dictionaries**, and JSON arrays become **lists**\n\n## Complete Example\n\nSuppose you have `data.json`:\n```json\n{\n \"name\": \"Alice\",\n \"age\": 30,\n \"hobbies\": [\"reading\", \"hiking\"]\n}\n```\n\nYou can read and access it like this:\n\n```python\nimport json\n\nwith open('data.json', 'r', encoding='utf-8') as file:\n data = json.load(file)\n\nprint(data['name']) # Alice\nprint(data['age']) # 30\nprint(data['hobbies'][0]) # reading\n```\n\n## Handling Errors\n\nIt's good practice to handle potential errors:\n\n```python\nimport json\n\ntry:\n with open('data.json', 'r', encoding='utf-8') as file:\n data = json.load(file)\nexcept FileNotFoundError:\n print(\"File not found\")\nexcept json.JSONDecodeError as e:\n print(f\"Invalid JSON: {e}\")\n```\n\n## Bonus: Writing JSON\n\nTo write data back to a JSON file:\n\n```python\nimport json\n\ndata = {\"name\": \"Bob\", \"age\": 25}\n\nwith open('output.json', 'w', encoding='utf-8') as file:\n json.dump(data, file, indent=4)\n```\n\nThe `indent=4` argument makes the output nicely formatted. Let me know if you'd like help with a specific JSON structure!" }, "raw_response": { "content": [ { "text": "# Reading a JSON File in Python\n\nPython has a built-in `json` module that makes reading JSON files straightforward.\n\n## Basic Example\n\n```python\nimport json\n\nwith open('data.json', 'r') as file:\n data = json.load(file)\n\nprint(data)\n```\n\n## Key Points\n\n- **`json.load()`** reads from a file object and parses JSON into Python objects\n- **`json.loads()`** (with an \"s\") parses JSON from a string\n- JSON objects become Python **dictionaries**, and JSON arrays become **lists**\n\n## Complete Example\n\nSuppose you have `data.json`:\n```json\n{\n \"name\": \"Alice\",\n \"age\": 30,\n \"hobbies\": [\"reading\", \"hiking\"]\n}\n```\n\nYou can read and access it like this:\n\n```python\nimport json\n\nwith open('data.json', 'r', encoding='utf-8') as file:\n data = json.load(file)\n\nprint(data['name']) # Alice\nprint(data['age']) # 30\nprint(data['hobbies'][0]) # reading\n```\n\n## Handling Errors\n\nIt's good practice to handle potential errors:\n\n```python\nimport json\n\ntry:\n with open('data.json', 'r', encoding='utf-8') as file:\n data = json.load(file)\nexcept FileNotFoundError:\n print(\"File not found\")\nexcept json.JSONDecodeError as e:\n print(f\"Invalid JSON: {e}\")\n```\n\n## Bonus: Writing JSON\n\nTo write data back to a JSON file:\n\n```python\nimport json\n\ndata = {\"name\": \"Bob\", \"age\": 25}\n\nwith open('output.json', 'w', encoding='utf-8') as file:\n json.dump(data, file, indent=4)\n```\n\nThe `indent=4` argument makes the output nicely formatted. Let me know if you'd like help with a specific JSON structure!", "type": "text" } ], "gatewayMetadata": { "keySource": "BYOK" }, "id": "msg_013KNtXimWjxydHNC1qfHzwP", "model": "claude-opus-4-7", "role": "assistant", "stop_details": null, "stop_reason": "end_turn", "stop_sequence": null, "type": "message", "usage": { "input_tokens": 43, "output_tokens": 587 } }, "code_snippets": [ { "label": "typescript", "language": "typescript", "code": "const response = await env.AI.run(\n 'anthropic/claude-opus-4.7',\n {\n max_tokens: 1024,\n messages: [{ content: 'How do I read a JSON file in Python?', role: 'user' }],\n system: 'You are a helpful coding assistant specializing in Python.',\n },\n)\nconsole.log(response)" }, { "label": "curl", "language": "bash", "code": "curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/v1/messages \\\n --header \"Authorization: Bearer $CLOUDFLARE_API_TOKEN\" \\\n --header \"Content-Type: application/json\" \\\n --data '{\n \"model\": \"anthropic/claude-opus-4.7\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"content\": \"How do I read a JSON file in Python?\",\n \"role\": \"user\"\n }\n ],\n \"system\": \"You are a helpful coding assistant specializing in Python.\"\n}'" } ] }, { "name": "Multi-turn Conversation", "description": "Continuing a conversation with context", "input": { "max_tokens": 1024, "messages": [ { "content": "I need help planning a road trip from San Francisco to Los Angeles.", "role": "user" }, { "content": "I'd be happy to help! The drive is about 380 miles and takes roughly 5-6 hours. Would you like suggestions for scenic routes or interesting stops along the way?", "role": "assistant" }, { "content": "Yes, what are some good places to stop?", "role": "user" } ] }, "output": { "text": "Great choice to explore along the way! Here are some popular stops, organized by route:\n\n## If Taking Highway 1 / Pacific Coast Highway (scenic, ~9-10 hours driving)\n\n- **Half Moon Bay** \u2013 Charming coastal town, great for breakfast\n- **Santa Cruz** \u2013 Boardwalk, beaches, and redwoods\n- **Monterey** \u2013 Famous aquarium and Cannery Row\n- **Carmel-by-the-Sea** \u2013 Quaint village with art galleries\n- **Big Sur** \u2013 Stunning cliffs, Bixby Bridge, McWay Falls\n- **Hearst Castle** (San Simeon) \u2013 Historic mansion tours\n- **Morro Bay** \u2013 Iconic Morro Rock and sea otters\n- **Pismo Beach** \u2013 Sand dunes and beach town vibes\n- **Santa Barbara** \u2013 \"American Riviera,\" wine, and Spanish architecture\n\n## If Taking I-5 (fastest, ~5-6 hours)\n\n- **Harris Ranch** \u2013 Famous steakhouse and rest stop\n- **Kettleman City** \u2013 Gas and snacks (not much else!)\n- I-5 is efficient but pretty barren\u2014mostly farmland\n\n## If Taking US-101 (middle ground, ~6-7 hours)\n\n- **Gilroy** \u2013 Garlic capital, outlet shopping\n- **Paso Robles** \u2013 Excellent wine country\n- **San Luis Obispo** \u2013 College town with great food\n- **Solvang** \u2013 Charming Danish-themed village\n- **Santa Barbara** \u2013 Worth visiting on this route too\n\n## Questions to help narrow it down:\n1. How many days do you have for the trip?\n2. Are you more interested in nature, food, history, or beaches?\n3. Traveling solo, with family, or friends?\n\nLet me know and I can build a more detailed itinerary!" }, "raw_response": { "content": [ { "text": "Great choice to explore along the way! Here are some popular stops, organized by route:\n\n## If Taking Highway 1 / Pacific Coast Highway (scenic, ~9-10 hours driving)\n\n- **Half Moon Bay** \u2013 Charming coastal town, great for breakfast\n- **Santa Cruz** \u2013 Boardwalk, beaches, and redwoods\n- **Monterey** \u2013 Famous aquarium and Cannery Row\n- **Carmel-by-the-Sea** \u2013 Quaint village with art galleries\n- **Big Sur** \u2013 Stunning cliffs, Bixby Bridge, McWay Falls\n- **Hearst Castle** (San Simeon) \u2013 Historic mansion tours\n- **Morro Bay** \u2013 Iconic Morro Rock and sea otters\n- **Pismo Beach** \u2013 Sand dunes and beach town vibes\n- **Santa Barbara** \u2013 \"American Riviera,\" wine, and Spanish architecture\n\n## If Taking I-5 (fastest, ~5-6 hours)\n\n- **Harris Ranch** \u2013 Famous steakhouse and rest stop\n- **Kettleman City** \u2013 Gas and snacks (not much else!)\n- I-5 is efficient but pretty barren\u2014mostly farmland\n\n## If Taking US-101 (middle ground, ~6-7 hours)\n\n- **Gilroy** \u2013 Garlic capital, outlet shopping\n- **Paso Robles** \u2013 Excellent wine country\n- **San Luis Obispo** \u2013 College town with great food\n- **Solvang** \u2013 Charming Danish-themed village\n- **Santa Barbara** \u2013 Worth visiting on this route too\n\n## Questions to help narrow it down:\n1. How many days do you have for the trip?\n2. Are you more interested in nature, food, history, or beaches?\n3. Traveling solo, with family, or friends?\n\nLet me know and I can build a more detailed itinerary!", "type": "text" } ], "gatewayMetadata": { "keySource": "BYOK" }, "id": "msg_01FmPy3fWFf7w6Sx6ECEdKnh", "model": "claude-opus-4-7", "role": "assistant", "stop_details": null, "stop_reason": "end_turn", "stop_sequence": null, "type": "message", "usage": { "input_tokens": 114, "output_tokens": 621 } }, "code_snippets": [ { "label": "typescript", "language": "typescript", "code": "const response = await env.AI.run(\n 'anthropic/claude-opus-4.7',\n {\n max_tokens: 1024,\n messages: [\n {\n content: 'I need help planning a road trip from San Francisco to Los Angeles.',\n role: 'user',\n },\n {\n content:\n \"I'd be happy to help! The drive is about 380 miles and takes roughly 5-6 hours. Would you like suggestions for scenic routes or interesting stops along the way?\",\n role: 'assistant',\n },\n { content: 'Yes, what are some good places to stop?', role: 'user' },\n ],\n },\n)\nconsole.log(response)" }, { "label": "curl", "language": "bash", "code": "curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/v1/messages \\\n --header \"Authorization: Bearer $CLOUDFLARE_API_TOKEN\" \\\n --header \"Content-Type: application/json\" \\\n --data '{\n \"model\": \"anthropic/claude-opus-4.7\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"content\": \"I need help planning a road trip from San Francisco to Los Angeles.\",\n \"role\": \"user\"\n },\n {\n \"content\": \"I'\\''d be happy to help! The drive is about 380 miles and takes roughly 5-6 hours. Would you like suggestions for scenic routes or interesting stops along the way?\",\n \"role\": \"assistant\"\n },\n {\n \"content\": \"Yes, what are some good places to stop?\",\n \"role\": \"user\"\n }\n ]\n}'" } ] }, { "name": "Creative Writing with Adaptive Thinking", "description": "Use adaptive thinking with high effort to steer creative output -- the recommended replacement for the deprecated `temperature` parameter.", "input": { "max_tokens": 2048, "messages": [ { "content": "Write a short story opening about a detective finding an unusual clue.", "role": "user" } ], "output_config": { "effort": "high" }, "thinking": { "type": "adaptive" } }, "output": { "text": "# The Wrong Kind of Silence\n\nDetective Mara Halloran had worked enough crime scenes to know that rooms had voices. A kitchen where someone had fled mid-breakfast hummed with interruption. A bedroom after a struggle kept the echo of it in the disarranged sheets, the lamp knocked just-so.\n\nBut the study at 14 Pearsmont Lane was quiet in a way she didn't recognize.\n\nShe stood in the doorway, coffee going cold in her hand, and tried to name it. The body had already been photographed and carried out\u2014Gerald Finch, seventy-two, retired cartographer, found slumped over his desk by the housekeeper at half past six. No forced entry. No wound. The coroner was calling it natural until the tox screen said otherwise.\n\nMara stepped inside. Bookshelves. A globe. The smell of pipe tobacco clinging to the curtains like an old apology. Everything where a dead man's things ought to be.\n\nExcept.\n\nOn the desk, beside the blotter where Finch's forehead had rested, someone had laid out seven grains of rice in a perfect, deliberate row.\n\nNot spilled. Not scattered. *Placed.*\n\nShe crouched until her eyes were level with the desktop. The grains were evenly spaced, each one turned so its seam faced the same direction\u2014north, if she was reading the window light right. The housekeeper hadn't mentioned them. The first responders hadn't logged them. And Gerald Finch, according to three separate statements, hadn't eaten rice in forty years. Couldn't stand the stuff, his sister had said. Something about the war.\n\nMara straightened slowly, her knees protesting, and felt the quiet of the room press against her ears.\n\nSeven grains. Facing north. On the desk of a man who drew maps for a living.\n\n\"Well, Gerald,\" she murmured, reaching for her notebook. \"Who were you trying to tell?\"" }, "raw_response": { "content": [ { "text": "# The Wrong Kind of Silence\n\nDetective Mara Halloran had worked enough crime scenes to know that rooms had voices. A kitchen where someone had fled mid-breakfast hummed with interruption. A bedroom after a struggle kept the echo of it in the disarranged sheets, the lamp knocked just-so.\n\nBut the study at 14 Pearsmont Lane was quiet in a way she didn't recognize.\n\nShe stood in the doorway, coffee going cold in her hand, and tried to name it. The body had already been photographed and carried out\u2014Gerald Finch, seventy-two, retired cartographer, found slumped over his desk by the housekeeper at half past six. No forced entry. No wound. The coroner was calling it natural until the tox screen said otherwise.\n\nMara stepped inside. Bookshelves. A globe. The smell of pipe tobacco clinging to the curtains like an old apology. Everything where a dead man's things ought to be.\n\nExcept.\n\nOn the desk, beside the blotter where Finch's forehead had rested, someone had laid out seven grains of rice in a perfect, deliberate row.\n\nNot spilled. Not scattered. *Placed.*\n\nShe crouched until her eyes were level with the desktop. The grains were evenly spaced, each one turned so its seam faced the same direction\u2014north, if she was reading the window light right. The housekeeper hadn't mentioned them. The first responders hadn't logged them. And Gerald Finch, according to three separate statements, hadn't eaten rice in forty years. Couldn't stand the stuff, his sister had said. Something about the war.\n\nMara straightened slowly, her knees protesting, and felt the quiet of the room press against her ears.\n\nSeven grains. Facing north. On the desk of a man who drew maps for a living.\n\n\"Well, Gerald,\" she murmured, reaching for her notebook. \"Who were you trying to tell?\"", "type": "text" } ], "gatewayMetadata": { "keySource": "BYOK" }, "id": "msg_019oiL5qvRdHBpPLrsS5x3Ux", "model": "claude-opus-4-7", "role": "assistant", "stop_details": null, "stop_reason": "end_turn", "stop_sequence": null, "type": "message", "usage": { "input_tokens": 31, "output_tokens": 628 } }, "code_snippets": [ { "label": "typescript", "language": "typescript", "code": "const response = await env.AI.run(\n 'anthropic/claude-opus-4.7',\n {\n max_tokens: 2048,\n messages: [\n {\n content: 'Write a short story opening about a detective finding an unusual clue.',\n role: 'user',\n },\n ],\n output_config: { effort: 'high' },\n thinking: { type: 'adaptive' },\n },\n)\nconsole.log(response)" }, { "label": "curl", "language": "bash", "code": "curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/v1/messages \\\n --header \"Authorization: Bearer $CLOUDFLARE_API_TOKEN\" \\\n --header \"Content-Type: application/json\" \\\n --data '{\n \"model\": \"anthropic/claude-opus-4.7\",\n \"max_tokens\": 2048,\n \"messages\": [\n {\n \"content\": \"Write a short story opening about a detective finding an unusual clue.\",\n \"role\": \"user\"\n }\n ],\n \"output_config\": {\n \"effort\": \"high\"\n },\n \"thinking\": {\n \"type\": \"adaptive\"\n }\n}'" } ] }, { "name": "Streaming Response", "description": "Enable streaming for real-time output", "input": { "max_tokens": 1024, "messages": [ { "content": "Explain the concept of recursion with a simple example.", "role": "user" } ], "stream": true }, "output": { "text": [ "# Recursion", " Explained\n\n**Recursion** is a programming concept where a function calls itself to solve a smaller version of the same problem,", " until it reaches a simple case it can solve directly.\n\n## Two Ess", "ential Parts\n\nEvery recursive function needs:\n\n1. **Base case** \u2014 a condition that st", "ops the recursion (prevents infinite loops)\n2. **Recursive case** \u2014 the function calling itself with a", " smaller/simpler input\n\n## Simple Example: Factorial\n\nThe factorial of a number `", "n` (written `n!`) is the product of all positive integers up to `n`.\n\n- `", "5! = 5 \u00d7 4 \u00d7 3 \u00d7 2 \u00d7 1 = 120`\n\nNotice that `5! = 5 \u00d7 4!", "`, and `4! = 4 \u00d7 3!`, and so on. This self-similar p", "attern is perfect for recursion.\n\n```python\ndef factorial(n):\n # Base case: st", "op when n is 0 or 1\n if n <= 1:\n return 1\n # Recursive case: n \u00d7 factorial of (", "n-1)\n return n * factorial(n - 1)\n\nprint(factorial(5)) # Output: 120\n```\n\n## How", " It Works (Step by Step)\n\nWhen you call `factorial(5)`:\n\n```\nfactorial(5) = 5 \u00d7 factorial", "(4)\n = 5 \u00d7 (4 \u00d7 factorial(3))\n = 5 \u00d7 (4 \u00d7 (3 \u00d7 factorial(2)))\n = 5 \u00d7 (4 \u00d7 (3 \u00d7 (2 \u00d7 factorial", "(1))))\n = 5 \u00d7 (4 \u00d7 (3 \u00d7 (2 \u00d7 1))) \u2190 base case hit!\n = 120", "\n```\n\n## Real-World Analogy\n\nThink of **Russian nesting dolls** \ud83e\ude86", ". To find the smallest doll, you open one, find another in", "side, open that, find another... until finally you reach the tiniest doll that", " doesn't open. That \"tiniest doll\" is your base case.\n\n## Key Takeaway\n\nRecursion", " is elegant for problems that can be broken into **sm", "aller versions of themselves** \u2014 like traversing trees, nav", "igating folders, or solving puzzles like the Tower of Hanoi. Just remember: **", "always include a base case**, or your program will cr", "ash with a stack overflow!" ] }, "raw_response": [ { "message": { "content": [], "id": "msg_018UiizftMy3k3UwQepmrFxq", "model": "claude-opus-4-7", "role": "assistant", "stop_details": null, "stop_reason": null, "stop_sequence": null, "type": "message", "usage": { "cache_creation": { "ephemeral_1h_input_tokens": 0, "ephemeral_5m_input_tokens": 0 }, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0, "inference_geo": "global", "input_tokens": 27, "output_tokens": 6, "service_tier": "standard" } }, "type": "message_start" }, { "content_block": { "text": "", "type": "text" }, "index": 0, "type": "content_block_start" }, { "type": "ping" }, { "delta": { "text": "# Recursion", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": " Explained\n\n**Recursion** is a programming concept where a function calls itself to solve a smaller version of the same problem,", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": " until it reaches a simple case it can solve directly.\n\n## Two Ess", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "ential Parts\n\nEvery recursive function needs:\n\n1. **Base case** \u2014 a condition that st", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "ops the recursion (prevents infinite loops)\n2. **Recursive case** \u2014 the function calling itself with a", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": " smaller/simpler input\n\n## Simple Example: Factorial\n\nThe factorial of a number `", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "n` (written `n!`) is the product of all positive integers up to `n`.\n\n- `", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "5! = 5 \u00d7 4 \u00d7 3 \u00d7 2 \u00d7 1 = 120`\n\nNotice that `5! = 5 \u00d7 4!", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "`, and `4! = 4 \u00d7 3!`, and so on. This self-similar p", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "attern is perfect for recursion.\n\n```python\ndef factorial(n):\n # Base case: st", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "op when n is 0 or 1\n if n <= 1:\n return 1\n # Recursive case: n \u00d7 factorial of (", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "n-1)\n return n * factorial(n - 1)\n\nprint(factorial(5)) # Output: 120\n```\n\n## How", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": " It Works (Step by Step)\n\nWhen you call `factorial(5)`:\n\n```\nfactorial(5) = 5 \u00d7 factorial", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "(4)\n = 5 \u00d7 (4 \u00d7 factorial(3))\n = 5 \u00d7 (4 \u00d7 (3 \u00d7 factorial(2)))\n = 5 \u00d7 (4 \u00d7 (3 \u00d7 (2 \u00d7 factorial", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "(1))))\n = 5 \u00d7 (4 \u00d7 (3 \u00d7 (2 \u00d7 1))) \u2190 base case hit!\n = 120", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "\n```\n\n## Real-World Analogy\n\nThink of **Russian nesting dolls** \ud83e\ude86", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": ". To find the smallest doll, you open one, find another in", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "side, open that, find another... until finally you reach the tiniest doll that", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": " doesn't open. That \"tiniest doll\" is your base case.\n\n## Key Takeaway\n\nRecursion", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": " is elegant for problems that can be broken into **sm", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "aller versions of themselves** \u2014 like traversing trees, nav", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "igating folders, or solving puzzles like the Tower of Hanoi. Just remember: **", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "always include a base case**, or your program will cr", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "delta": { "text": "ash with a stack overflow!", "type": "text_delta" }, "index": 0, "type": "content_block_delta" }, { "index": 0, "type": "content_block_stop" }, { "delta": { "stop_details": null, "stop_reason": "end_turn", "stop_sequence": null }, "type": "message_delta", "usage": { "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0, "input_tokens": 27, "output_tokens": 695 } }, { "type": "message_stop" } ], "code_snippets": [ { "label": "typescript", "language": "typescript", "code": "const response = await env.AI.run(\n 'anthropic/claude-opus-4.7',\n {\n max_tokens: 1024,\n messages: [{ content: 'Explain the concept of recursion with a simple example.', role: 'user' }],\n stream: true,\n },\n)\nconsole.log(response)" }, { "label": "curl", "language": "bash", "code": "curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/v1/messages \\\n --header \"Authorization: Bearer $CLOUDFLARE_API_TOKEN\" \\\n --header \"Content-Type: application/json\" \\\n --data '{\n \"model\": \"anthropic/claude-opus-4.7\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"content\": \"Explain the concept of recursion with a simple example.\",\n \"role\": \"user\"\n }\n ],\n \"stream\": true\n}'" } ] }, { "name": "Web Search", "description": "Letting Claude use Anthropic's server-side web search tool to answer with current information", "input": { "max_tokens": 4096, "messages": [ { "content": "What were the top news stories about Cloudflare this week? Summarise in three bullets.", "role": "user" } ], "tools": [ { "max_uses": 3, "name": "web_search", "type": "web_search_20250305" } ] }, "output": { "text": "I'll search for recent Cloudflare news from this week." }, "raw_response": { "id": "msg_01BWg8R9cfU4m8VTrQPMZdAd", "type": "message", "role": "assistant", "content": [ { "type": "text", "text": "I'll search for recent Cloudflare news from this week." }, { "type": "server_tool_use", "id": "srvtoolu_013S4aGzYgyxQ9sNuA6ALc9i", "name": "web_search", "input": { "query": "Cloudflare news this week" } }, { "type": "web_search_tool_result", "tool_use_id": "srvtoolu_013S4aGzYgyxQ9sNuA6ALc9i", "content": [ { "type": "web_search_result", "title": "Cloudflare Status", "url": "https://www.cloudflarestatus.com/", "encrypted_content": 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"page_age": "May 7, 2026" }, { "type": "web_search_result", "title": "Building for the future", "url": "https://blog.cloudflare.com/building-for-the-future/", "encrypted_content": 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"page_age": "May 11, 2026" }, { "type": "web_search_result", "title": "Cloudflare Lays Off 1,100 Employees in AI-Driven Restructuring - SecurityWeek", "url": "https://www.securityweek.com/cloudflare-lays-off-1100-employees-in-ai-driven-restructuring/", "encrypted_content": 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"page_age": "6 hours ago" } ], "caller": { "type": "direct" } }, { "type": "text", "text": "Here are the top Cloudflare news stories from this week:\n\n- **Major network outage from fiber cut (June 22):** " }, { "type": "text", "text": "Cloudflare began investigating increased error rates and latency across multiple services starting at 13:35 UTC on June 22, 2026.", "citations": [ { "type": "web_search_result_location", "cited_text": "Jun 22, 2026 - 14:37 UTC \u00b7 Investigating - Cloudflare is investigating increased error rates and latency in multiple services beginning 13:35 UTC. Jun...", "url": "https://www.cloudflarestatus.com/", "title": "Cloudflare Status", "encrypted_index": "EpEBCioIERgCIiQ5ODY2MTIzNC03NmUwLTRlMGQtYTgyMS1iZThmOGMzNDc0ZDYSDKIgAlfdsdXj60aT0RoMsBH02m47wETNOvvAIjBLDmGOePFD0z1O/7VJbskFcOUhUgUFi/MEnAgz8slJh6UItTYXx5WYNUhNsVRYui0qFZosx8bxhoBlES9skQkNXumGC3CmuxgE" } ] }, { "type": "text", "text": " " }, { "type": "text", "text": "The issue stemmed from a fiber cut in Eastern North America, causing customers connecting through North America or accessing services in Europe to see increased latencies and timeouts as engineers worked to mitigate.", "citations": [ { "type": "web_search_result_location", "cited_text": "Customers connecting through North America or accessing services in Europe may see increased latencies and timeouts as Cloudflare engineers look to mi...", "url": "https://www.cloudflarestatus.com/", "title": "Cloudflare Status", "encrypted_index": "Eo8BCioIERgCIiQ5ODY2MTIzNC03NmUwLTRlMGQtYTgyMS1iZThmOGMzNDc0ZDYSDONNMQ3hx2HNo3hMVBoMK9yznwCtjF30uQgnIjDOcpSkMkZ9EK980zgvb9qiI4PBVllapkwEZVsNhXQ2B+ef7YPJ2nQWV/rjFomIIqcqEwNv/qvuOIbkQGFEc49TWKYuIEQYBA==" } ] }, { "type": "text", "text": "\n\n- **Workers AI degraded availability:** " }, { "type": "text", "text": "Cloudflare reported and investigated Workers AI experiencing degraded availability in some models", "citations": [ { "type": "web_search_result_location", "cited_text": "Jun 22, 2026 01:00 - Jun 23, 2026 09:00 UTC \u00b7 Workers AI experiencing degraded availability in some models \u00b7 Update - Cloudflare is aware of and inves...", "url": "https://www.cloudflarestatus.com/", "title": "Cloudflare Status", "encrypted_index": "EpMBCioIERgCIiQ5ODY2MTIzNC03NmUwLTRlMGQtYTgyMS1iZThmOGMzNDc0ZDYSDEIRITCaaEzMBPrVGBoM+L61CK+1lcgEROXlIjAGAa0AAKRY/iuIj+BbKIDOzADpFzcEAghwcy11LX2cZ3nTw6rsX7qv2J7R4tXzvKsqF2ghIUa9JyyawJEw8BeksjPpySb/HUuuGAQ=" } ] }, { "type": "text", "text": ", adding to the week's reliability concerns alongside scheduled maintenance windows in Newark, Minneapolis, and Stockholm datacenters.\n\n- **Stock volatility continues:** " }, { "type": "text", "text": "Cloudflare (NET) is experiencing significant volatility, with a 4.8% drop and an 11.7% decline in June, though analysts are cautiously optimistic, noting potential for a rebound as the stock tests key moving averages and earnings estimates rise dramatically.", "citations": [ { "type": "web_search_result_location", "cited_text": "Learn more ... Cloudflare (NET) is experiencing significant volatility, with a 4.8% drop today following an 11.7% decline in June. Analysts are cautio...", "url": "https://finance.yahoo.com/quote/NET/", "title": "Cloudflare, Inc. 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Summarise in three bullets.\",\n \"role\": \"user\"\n }\n ],\n \"tools\": [\n {\n \"max_uses\": 3,\n \"name\": \"web_search\",\n \"type\": \"web_search_20250305\"\n }\n ]\n}'" } ] } ], "default_example": null, "code_snippets": [], "supports_async": false, "zdr": true, "zdr_comment": null, "external_info": "https://www.anthropic.com/claude/opus", "terms": "https://www.anthropic.com/legal/commercial-terms", "cover_image_url": "https://pub-26f1392c1b674324be6786695bd72257.r2.dev/anthropic/claude-opus-4.7.png", "metadata": { "Adaptive Thinking": "Yes", "Architecture": "Transformer", "fedrampAvailable": "true" }, "request_formats": [ "anthropic-messages" ], "providers": null, "provider_details": [ { "id": "anthropic", "pricing": { "input_tokens": 5, "output_tokens": 25, "input_cached_tokens": 0.5, "input_cache_creation_tokens": 6.25 } } ], "banner": null, "created_at": "2026-05-22 17:52:55", "schema": { "input": { "$schema": "https://json-schema.org/draft/2020-12/schema", "type": "object", "properties": { "messages": { "type": "array", "items": { "type": "object", "properties": { "role": { "type": "string", "enum": [ "user", "assistant", "system" ] }, "content": { "anyOf": [ { "type": "string" }, { "type": "array", "items": { "type": "object", "properties": { "type": { "type": "string" }, "text": { "type": "string" }, "source": {}, "cache_control": { "type": "object", "properties": { "type": { "type": "string", "const": "ephemeral" }, "ttl": { "type": "string", "enum": [ "5m", "1h" ] } }, "required": [ "type" ], "additionalProperties": false } }, "required": [ "type" ], "additionalProperties": {} } } ] } }, "required": [ "role", "content" ], "additionalProperties": false } }, "max_tokens": { "type": "number", "exclusiveMinimum": 0 }, "system": { "anyOf": [ { "type": "string" }, { "type": "array", "items": { "type": "object", "properties": { "type": { "type": "string", "const": "text" }, "text": { "type": "string" }, "cache_control": { "type": "object", "properties": { "type": { "type": "string", "const": "ephemeral" }, "ttl": { "type": "string", "enum": [ "5m", "1h" ] } }, "required": [ "type" ], "additionalProperties": false } }, "required": [ "type", "text" ], "additionalProperties": {} } } ] }, "stream": { "type": "boolean" }, "metadata": { "type": "object", "propertyNames": { "type": "string" }, "additionalProperties": {} } }, "required": [ "messages", "max_tokens" ], "additionalProperties": {} }, "output": { "$schema": "https://json-schema.org/draft/2020-12/schema", "type": "object", "properties": { "id": { "type": "string" }, "type": { "type": "string", "const": "message" }, "role": { "type": "string", "const": "assistant" }, "content": { "type": "array", "items": { "type": "object", "properties": { "type": { "type": "string" }, "text": { "type": "string" } }, "required": [ "type" ], "additionalProperties": {} } }, "model": { "type": "string" }, "stop_reason": { "type": [ "string", "null" ] }, "usage": { "type": "object", "properties": { "input_tokens": { "type": "number" }, "output_tokens": { "type": "number" }, "cache_creation_input_tokens": { "type": [ "number", "null" ] }, "cache_read_input_tokens": { "type": [ "number", "null" ] }, "speed": { "type": [ "string", "null" ] } }, "required": [ "input_tokens", "output_tokens" ], "additionalProperties": {} } }, "required": [ "id", "type", "role", "content", "model", "stop_reason", "usage" ], "additionalProperties": {} } } }