Call Claude through the CometAPI Messages endpoint with text and image input, adaptive thinking, prompt caching, streaming, and tools.
POST
/
v1
/
messages
import os
import anthropic
client = anthropic.Anthropic(
base_url="https://api.cometapi.com",
api_key=os.environ["COMETAPI_KEY"],
)
message = client.messages.create(
model="claude-opus-5",
max_tokens=1000,
messages=[
{
"role": "user",
"content": "Suggest three search queries about renewable energy storage.",
},
],
)
for block in message.content:
if block.type == "text":
print(block.text)
{
"id": "msg_example",
"type": "message",
"role": "assistant",
"model": "claude-opus-5",
"content": [
{
"type": "text",
"text": "Here are three search queries covering different angles of the topic:\n\n1. **\"grid-scale battery storage cost trends 2024 2025\"**\n — Targets economics and recent price data for lithium-ion and other utility-scale systems.\n\n2. **\"long-duration energy storage technologies comparison flow battery vs compressed air vs thermal\"**\n — Surfaces technical comparisons of options for storage beyond the 4–8 hour range, where lithium-ion becomes less cost-effective.\n\n3. **\"green hydrogen seasonal storage feasibility round-trip efficiency\"**\n — Digs into the viability of hydrogen for multi-week or seasonal balancing, including its efficiency penalties.\n\n**A few tips for refining these:**\n- Add `site:.gov` or `site:.edu` to prioritize research and agency reports (e.g., NREL, IEA, DOE).\n- Append a region like `Europe`, `India`, or `California` if you need location-specific policy or deployment data.\n- Try `filetype:pdf` to pull up technical white papers and government studies directly.\n\nWant me to tailor these toward a specific use case — academic research, investment analysis, or policy work?"
}
],
"stop_reason": "end_turn",
"stop_sequence": null,
"usage": {
"input_tokens": 23,
"cache_creation_input_tokens": 0,
"cache_read_input_tokens": 0,
"cache_creation": {
"ephemeral_5m_input_tokens": 0,
"ephemeral_1h_input_tokens": 0
},
"output_tokens": 437,
"output_tokens_details": {
"thinking_tokens": 50
}
}
}
Use POST /v1/messages to send Claude requests in the Anthropic Messages format.
The examples configure the official Anthropic SDK with the CometAPI base URL and
read your API key from $COMETAPI_KEY.
The following examples request three search queries. Set $COMETAPI_KEY before
running them. Install anthropic for Python or @anthropic-ai/sdk for JavaScript:
Set thinking.type to adaptive and choose an output_config.effort value.
The following example uses xhigh and reads the completed message from a stream:
import osimport anthropicclient = anthropic.Anthropic( base_url="https://api.cometapi.com", api_key=os.environ["COMETAPI_KEY"],)with client.messages.stream( model="claude-opus-5", max_tokens=4096, messages=[ { "role": "user", "content": "A shop sells notebooks for $7 each. Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps.", }, ], thinking={ "type": "adaptive", }, output_config={ "effort": "xhigh", },) as stream: message = stream.get_final_message()for block in message.content: if block.type == "text": print(block.text)
Thinking contributes to the max_tokens output limit. Leave room for the final
answer as well as thinking. A response can contain text without a visible
thinking block. Preserve any returned thinking blocks unchanged in conversation
history.For the model-specific thinking configuration, see
Thinking.
The examples omit temperature, top_p, and top_k; consult the selected
model’s parameter documentation before adding sampling controls.
Place a cache breakpoint on reference material that you reuse between requests.
Save your reference material in a UTF-8 reference.txt file before running this
example. Use a prefix that meets the selected model’s
minimum cacheable length:
import osfrom pathlib import Pathimport anthropicclient = anthropic.Anthropic( base_url="https://api.cometapi.com", api_key=os.environ["COMETAPI_KEY"],)reference = Path("reference.txt").read_text(encoding="utf-8")with client.messages.stream( model="claude-sonnet-5", max_tokens=1024, messages=[ { "role": "user", "content": "How long can customers return damaged books, and what must they provide?", }, ], system=[ { "type": "text", "text": reference, "cache_control": { "type": "ephemeral", }, }, ],) as stream: message = stream.get_final_message()for block in message.content: if block.type == "text": print(block.text)print(message.usage.model_dump_json())
Run the request again with the same model, reference text, and thinking settings.
Inspect the usage counters to determine whether the request reused a prefix:
cache_creation_input_tokens counts tokens written to the cache.
cache_read_input_tokens counts tokens read from the cache.
input_tokens counts input processed outside those cache counters.
On repeated requests, cache_read_input_tokens reports how many input tokens
were read from the cache. The OpenAPI Prompt Cache
example contains a complete fictional reference that you can save as
reference.txt to try the sample.
Set stream: true for Server-Sent Events. The SDK exposes text fragments as they
arrive:
import osimport anthropicclient = anthropic.Anthropic( base_url="https://api.cometapi.com", api_key=os.environ["COMETAPI_KEY"],)with client.messages.stream( model="claude-opus-5", max_tokens=1024, messages=[ { "role": "user", "content": "Write a two-line poem about a comet.", }, ],) as stream: for text in stream.text_stream: print(text, end="", flush=True)
A message stream contains message_start, content block events, message_delta,
and message_stop. Content blocks can contain text, thinking, or tool activity.
For a text block, content_block_delta contains a text_delta. Read final usage
and the stop reason from message_delta.
Server tools execute during the API request and return result blocks alongside
Claude’s answer.
Web Fetch
Web Search
Fetch a paper and ask Claude to use the retrieved document in its answer.
This example streams the response and inspects both the final text and the
web_fetch_tool_result block:
import osimport anthropicclient = anthropic.Anthropic( base_url="https://api.cometapi.com", api_key=os.environ["COMETAPI_KEY"],)with client.messages.stream( model="claude-sonnet-5", max_tokens=2048, messages=[ { "role": "user", "content": "Fetch https://arxiv.org/abs/1512.03385 and state the paper title and the proposed learning framework in two sentences.", }, ], tools=[ { "type": "web_fetch_20250910", "name": "web_fetch", "max_uses": 3, }, ],) as stream: message = stream.get_final_message()for block in message.content: if block.type == "text": print(block.text)for block in message.content: if block.type == "web_fetch_tool_result": print(block.model_dump_json())
The response pairs a server_tool_use block with a web_fetch_tool_result
containing the fetched document or a tool error.
Search for an official release date and ask Claude to cite its source.
This example streams the response, collects the final message, and prints the
returned search sources:
import osimport anthropicclient = anthropic.Anthropic( base_url="https://api.cometapi.com", api_key=os.environ["COMETAPI_KEY"],)with client.messages.stream( model="claude-sonnet-5", max_tokens=4096, messages=[ { "role": "user", "content": "Search the web for the official Python 3.14 release date. Answer with the date and cite a source.", }, ], tools=[ { "type": "web_search_20250305", "name": "web_search", "max_uses": 3, }, ],) as stream: message = stream.get_final_message()for block in message.content: if block.type == "text": print(block.text)for block in message.content: if block.type == "web_search_tool_result": if isinstance(block.content, list): for result in block.content: if result.type == "web_search_result": print(result.title, result.url)
The response pairs a server_tool_use block with a web_search_tool_result
containing sources. Read the source titles and URLs from this result block.
For a client tool, Claude returns a tool_use block. Run your application function
and send its result in a tool_result block with the matching tool_use_id.
Preserve the complete assistant content between the two requests.This example supplies a fictional order result and asks Claude to use that result:
import jsonimport osimport anthropicclient = anthropic.Anthropic( base_url="https://api.cometapi.com", api_key=os.environ["COMETAPI_KEY"],)tools = [{ "name": "get_order_status", "description": "Look up the status of a demonstration order.", "input_schema": { "type": "object", "properties": { "order_id": { "type": "string", "description": "The order reference.", }, }, "required": ["order_id"], },}]messages = [{ "role": "user", "content": "Check the status of demo-order-42 using the order tool.",}]with client.messages.stream( model="claude-opus-5", max_tokens=1000, messages=messages, tools=tools,) as stream: message = stream.get_final_message()tool_call = next(b for b in message.content if b.type == "tool_use")messages.append({ "role": "assistant", "content": [block.model_dump() for block in message.content],})messages.append({ "role": "user", "content": [{ "type": "tool_result", "tool_use_id": tool_call.id, "content": json.dumps({ "status": "ready_for_pickup", "pickup_code": "COMET42", }), }],})with client.messages.stream( model="claude-opus-5", max_tokens=1000, messages=messages, tools=tools,) as stream: follow_up = stream.get_final_message()for block in follow_up.content: if block.type == "text": print(block.text)
A non-streaming request returns a message object. The following example shows its
text and usage fields with an illustrative message identifier:
{ "id": "msg_example", "type": "message", "role": "assistant", "model": "claude-opus-5", "content": [ { "type": "text", "text": "Here are three search queries covering different angles of the topic:\n\n1. **\"grid-scale battery storage cost trends 2024 2025\"**\n — Targets economics and recent price data for lithium-ion and other utility-scale systems.\n\n2. **\"long-duration energy storage technologies comparison flow battery vs compressed air vs thermal\"**\n — Surfaces technical comparisons of options for storage beyond the 4–8 hour range, where lithium-ion becomes less cost-effective.\n\n3. **\"green hydrogen seasonal storage feasibility round-trip efficiency\"**\n — Digs into the viability of hydrogen for multi-week or seasonal balancing, including its efficiency penalties.\n\n**A few tips for refining these:**\n- Add `site:.gov` or `site:.edu` to prioritize research and agency reports (e.g., NREL, IEA, DOE).\n- Append a region like `Europe`, `India`, or `California` if you need location-specific policy or deployment data.\n- Try `filetype:pdf` to pull up technical white papers and government studies directly.\n\nWant me to tailor these toward a specific use case — academic research, investment analysis, or policy work?" } ], "stop_reason": "end_turn", "stop_sequence": null, "usage": { "input_tokens": 23, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0, "cache_creation": { "ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 0 }, "output_tokens": 437, "output_tokens_details": { "thinking_tokens": 50 } }}
The stop reason describes the next action. end_turn completes the answer,
max_tokens means output reached the limit, and tool_use requests a client tool
result. For a server-tool turn that returns pause_turn, continue with the
returned assistant content unchanged.
Conversation history. Use user and assistant messages with text strings or content-block arrays. Return complete assistant content blocks when continuing a tool call.
The maximum number of tokens to generate. The model may stop before reaching this limit. When using thinking, the thinking tokens count towards this limit.
If true, stream the response incrementally using Server-Sent Events (SSE). Events include message_start, content_block_start, content_block_delta, content_block_stop, message_delta, and message_stop.
import os
import anthropic
client = anthropic.Anthropic(
base_url="https://api.cometapi.com",
api_key=os.environ["COMETAPI_KEY"],
)
message = client.messages.create(
model="claude-opus-5",
max_tokens=1000,
messages=[
{
"role": "user",
"content": "Suggest three search queries about renewable energy storage.",
},
],
)
for block in message.content:
if block.type == "text":
print(block.text)
{
"id": "msg_example",
"type": "message",
"role": "assistant",
"model": "claude-opus-5",
"content": [
{
"type": "text",
"text": "Here are three search queries covering different angles of the topic:\n\n1. **\"grid-scale battery storage cost trends 2024 2025\"**\n — Targets economics and recent price data for lithium-ion and other utility-scale systems.\n\n2. **\"long-duration energy storage technologies comparison flow battery vs compressed air vs thermal\"**\n — Surfaces technical comparisons of options for storage beyond the 4–8 hour range, where lithium-ion becomes less cost-effective.\n\n3. **\"green hydrogen seasonal storage feasibility round-trip efficiency\"**\n — Digs into the viability of hydrogen for multi-week or seasonal balancing, including its efficiency penalties.\n\n**A few tips for refining these:**\n- Add `site:.gov` or `site:.edu` to prioritize research and agency reports (e.g., NREL, IEA, DOE).\n- Append a region like `Europe`, `India`, or `California` if you need location-specific policy or deployment data.\n- Try `filetype:pdf` to pull up technical white papers and government studies directly.\n\nWant me to tailor these toward a specific use case — academic research, investment analysis, or policy work?"
}
],
"stop_reason": "end_turn",
"stop_sequence": null,
"usage": {
"input_tokens": 23,
"cache_creation_input_tokens": 0,
"cache_read_input_tokens": 0,
"cache_creation": {
"ephemeral_5m_input_tokens": 0,
"ephemeral_1h_input_tokens": 0
},
"output_tokens": 437,
"output_tokens_details": {
"thinking_tokens": 50
}
}
}
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Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps.\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` ],`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` thinking`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`{`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"adaptive\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#953800`,\"--shiki-dark\":`#9CDCFE`},children:` output_config`}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`{`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"effort\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"xhigh\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` },`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`) `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`as`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` stream:`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` message `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`=`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` stream.get_final_message()`})]}),`\n`,_jsx(_components.span,{className:`line`}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`for`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` block `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`in`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` message.content:`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:` if`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` block.type `}),_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#D4D4D4`},children:`==`}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:` \"text\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`:`})]}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#0550AE`,\"--shiki-dark\":`#DCDCAA`},children:` print`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`(block.text)`})]}),`\n`]})})}),`\n`,_jsxs(_components.p,{children:[`Thinking contributes to the `,_jsx(_components.code,{children:`max_tokens`}),` output limit. Leave room for the final\nanswer as well as thinking. A response can contain text without a visible\nthinking block. Preserve any returned thinking blocks unchanged in conversation\nhistory.`]}),`\n`,_jsxs(_components.p,{children:[`For the model-specific thinking configuration, see\n`,_jsx(_components.a,{href:`https://platform.claude.com/docs/en/build-with-claude/extended-thinking`,children:`Thinking`}),`.\nThe examples omit `,_jsx(_components.code,{children:`temperature`}),`, `,_jsx(_components.code,{children:`top_p`}),`, and `,_jsx(_components.code,{children:`top_k`}),`; consult the selected\nmodel’s parameter documentation before adding sampling controls.`]}),`\n`,_jsx(Heading,{level:`2`,id:`cache-prompts`,children:`Cache prompts`}),`\n`,_jsxs(_components.p,{children:[`Place a cache breakpoint on reference material that you reuse between requests.\nSave your reference material in a UTF-8 `,_jsx(_components.code,{children:`reference.txt`}),` file before running this\nexample. Use a prefix that meets the selected model’s\n`,_jsx(_components.a,{href:`https://platform.claude.com/docs/en/build-with-claude/prompt-caching#cache-limitations`,children:`minimum cacheable length`}),`:`]}),`\n`,_jsx(CodeBlock,{filename:``,numberOfLines:`37`,language:`python`,children:_jsx(_components.pre,{className:`shiki shiki-themes github-light-default dark-plus`,style:{backgroundColor:`#ffffff`,\"--shiki-dark-bg\":`#0B0C0E`,color:`#1f2328`,\"--shiki-dark\":`#D4D4D4`},language:`python`,children:_jsxs(_components.code,{language:`python`,numberOfLines:`37`,children:[_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#CF222E`,\"--shiki-dark\":`#C586C0`},children:`import`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` 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[`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:` {`})}),`\n`,_jsxs(_components.span,{className:`line`,children:[_jsx(_components.span,{style:{color:`#116329`,\"--shiki-dark\":`#9CDCFE`},children:` \"type\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`: `}),_jsx(_components.span,{style:{color:`#0A3069`,\"--shiki-dark\":`#CE9178`},children:`\"text\"`}),_jsx(_components.span,{style:{color:`#1F2328`,\"--shiki-dark\":`#D4D4D4`},children:`,`})]}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{children:' \"text\": \"Here are three search queries covering different angles of the topic:\\\\n\\\\n1. **\\\\\"grid-scale battery storage cost trends 2024 2025\\\\\"**\\\\n — Targets economics and recent price data for lithium-ion and other utility-scale systems.\\\\n\\\\n2. **\\\\\"long-duration energy storage technologies comparison flow battery vs compressed air vs thermal\\\\\"**\\\\n — Surfaces technical comparisons of options for storage beyond the 4–8 hour range, where lithium-ion becomes less cost-effective.\\\\n\\\\n3. **\\\\\"green hydrogen seasonal storage feasibility round-trip efficiency\\\\\"**\\\\n — Digs into the viability of hydrogen for multi-week or seasonal balancing, including its efficiency penalties.\\\\n\\\\n**A few tips for refining these:**\\\\n- Add `site:.gov` or `site:.edu` to prioritize research and agency reports (e.g., NREL, IEA, DOE).\\\\n- Append a region like `Europe`, `India`, or `California` if you need location-specific policy or deployment data.\\\\n- Try `filetype:pdf` to pull up technical white papers and government studies directly.\\\\n\\\\nWant me to tailor these toward a specific use case — academic research, investment analysis, or policy 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Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps.\",\n },\n ],\n thinking={\n \"type\": \"adaptive\",\n },\n output_config={\n \"effort\": \"xhigh\",\n },\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n"},{"lang":"Python","label":"Effort control","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-opus-5\",\n max_tokens=1000,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Summarize the benefit of automated tests in one sentence.\",\n },\n ],\n output_config={\n \"effort\": \"low\",\n },\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n"},{"lang":"Python","label":"Streaming","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-opus-5\",\n max_tokens=1024,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Write a two-line poem about a comet.\",\n },\n ],\n) as stream:\n for text in stream.text_stream:\n print(text, end=\"\", flush=True)\n"},{"lang":"Python","label":"Web Fetch","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-sonnet-5\",\n max_tokens=2048,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Fetch https://arxiv.org/abs/1512.03385 and state the paper title and the proposed learning framework in two sentences.\",\n },\n ],\n tools=[\n {\n \"type\": \"web_fetch_20250910\",\n \"name\": \"web_fetch\",\n \"max_uses\": 3,\n },\n ],\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n\nfor block in message.content:\n if block.type == \"web_fetch_tool_result\":\n print(block.model_dump_json())\n"},{"lang":"Python","label":"Image Input","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-opus-5\",\n max_tokens=1000,\n messages=[\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"image\",\n \"source\": {\n \"type\": \"url\",\n \"url\": \"https://picsum.photos/seed/comet/800/600.jpg\",\n },\n },\n {\n \"type\": \"text\",\n \"text\": \"Describe the visible scene in one sentence.\",\n },\n ],\n },\n ],\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n"},{"lang":"JavaScript","label":"Basic","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst message = await client.messages.create({\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Suggest three search queries about renewable energy storage.\"\n }\n ]\n});\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n"},{"lang":"JavaScript","label":"Prompt Cache","source":"import Anthropic from \"@anthropic-ai/sdk\";\nimport fs from \"node:fs\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst reference = fs.readFileSync(\"reference.txt\", \"utf8\");\n\nconst stream = client.messages.stream({\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"How long can customers return damaged books, and what must they provide?\"\n }\n ],\n \"system\": [\n {\n \"type\": \"text\",\n \"text\": reference,\n \"cache_control\": {\n \"type\": \"ephemeral\"\n }\n }\n ]\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n\nconsole.log(message.usage);\n"},{"lang":"JavaScript","label":"Adaptive thinking","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 4096,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"A shop sells notebooks for $7 each. Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps.\"\n }\n ],\n \"thinking\": {\n \"type\": \"adaptive\"\n },\n \"output_config\": {\n \"effort\": \"xhigh\"\n }\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n"},{"lang":"JavaScript","label":"Effort control","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the benefit of automated tests in one sentence.\"\n }\n ],\n \"output_config\": {\n \"effort\": \"low\"\n }\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n"},{"lang":"JavaScript","label":"Streaming","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Write a two-line poem about a comet.\"\n }\n ]\n});\nstream.on(\"text\", (text) => process.stdout.write(text));\nawait stream.finalMessage();\n"},{"lang":"JavaScript","label":"Web Fetch","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 2048,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Fetch https://arxiv.org/abs/1512.03385 and state the paper title and the proposed learning framework in two sentences.\"\n }\n ],\n \"tools\": [\n {\n \"type\": \"web_fetch_20250910\",\n \"name\": \"web_fetch\",\n \"max_uses\": 3\n }\n ]\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n\nfor (const block of message.content) {\n if (block.type === \"web_fetch_tool_result\") console.log(block);\n}\n"},{"lang":"JavaScript","label":"Image Input","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"image\",\n \"source\": {\n \"type\": \"url\",\n \"url\": \"https://picsum.photos/seed/comet/800/600.jpg\"\n }\n },\n {\n \"type\": \"text\",\n \"text\": \"Describe the visible scene in one sentence.\"\n }\n ]\n }\n ]\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n"},{"lang":"Shell","label":"Basic","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n -d '{\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Suggest three search queries about renewable energy storage.\"\n }\n ]\n}'\n"},{"lang":"Shell","label":"Prompt Cache","source":"request_body=$(jq -n --rawfile reference reference.txt '\n{\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"How long can customers return damaged books, and what must they provide?\"\n }\n ],\n \"system\": [\n {\n \"type\": \"text\",\n \"text\": $reference,\n \"cache_control\": {\n \"type\": \"ephemeral\"\n }\n }\n ],\n \"stream\": true\n}\n')\n\ncurl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n --data-binary \"$request_body\"\n"},{"lang":"Shell","label":"Adaptive thinking","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 4096,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"A shop sells notebooks for $7 each. Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps.\"\n }\n ],\n \"thinking\": {\n \"type\": \"adaptive\"\n },\n \"output_config\": {\n \"effort\": \"xhigh\"\n },\n \"stream\": true\n}'\n"},{"lang":"Shell","label":"Effort control","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the benefit of automated tests in one sentence.\"\n }\n ],\n \"output_config\": {\n \"effort\": \"low\"\n },\n \"stream\": true\n}'\n"},{"lang":"Shell","label":"Streaming","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Write a two-line poem about a comet.\"\n }\n ],\n \"stream\": true\n}'\n"},{"lang":"Shell","label":"Web Fetch","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 2048,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Fetch https://arxiv.org/abs/1512.03385 and state the paper title and the proposed learning framework in two sentences.\"\n }\n ],\n \"tools\": [\n {\n \"type\": \"web_fetch_20250910\",\n \"name\": \"web_fetch\",\n \"max_uses\": 3\n }\n ],\n \"stream\": true\n}'\n"},{"lang":"Shell","label":"Image Input","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"image\",\n \"source\": {\n \"type\": \"url\",\n \"url\": \"https://picsum.photos/seed/comet/800/600.jpg\"\n }\n },\n {\n \"type\": \"text\",\n \"text\": \"Describe the visible scene in one sentence.\"\n }\n ]\n }\n ],\n \"stream\": true\n}'\n"},{"lang":"Python","label":"Web Search","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-sonnet-5\",\n max_tokens=4096,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Search the web for the official Python 3.14 release date. Answer with the date and cite a source.\",\n },\n ],\n tools=[\n {\n \"type\": \"web_search_20250305\",\n \"name\": \"web_search\",\n \"max_uses\": 3,\n },\n ],\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n\nfor block in message.content:\n if block.type == \"web_search_tool_result\":\n if isinstance(block.content, list):\n for result in block.content:\n if result.type == \"web_search_result\":\n print(result.title, result.url)\n"},{"lang":"JavaScript","label":"Web Search","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 4096,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Search the web for the official Python 3.14 release date. Answer with the date and cite a source.\"\n }\n ],\n \"tools\": [\n {\n \"type\": \"web_search_20250305\",\n \"name\": \"web_search\",\n \"max_uses\": 3\n }\n ]\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n if (block.type === \"web_search_tool_result\" \u0026\u0026 Array.isArray(block.content)) {\n for (const result of block.content) {\n if (result.type === \"web_search_result\") console.log(result.title, result.url);\n }\n }\n}\n"},{"lang":"Shell","label":"Web Search","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 4096,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Search the web for the official Python 3.14 release date. Answer with the date and cite a source.\"\n }\n ],\n \"tools\": [\n {\n \"type\": \"web_search_20250305\",\n \"name\": \"web_search\",\n \"max_uses\": 3\n }\n ],\n \"stream\": true\n}'\n"}],"method":"post","type":"path","servers":["42ec33ae-30ca-46e9-8152-affa55393c1d"],"security":["ec2a85d8-bb88-476c-8d6e-56cae8457eeb"],"path":"/v1/messages","baseUrlOptions":["https://api.cometapi.com"],"title":"Anthropic Messages","codeSamples":[{"label":"Basic","lang":"Python","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nmessage = client.messages.create(\n model=\"claude-opus-5\",\n max_tokens=1000,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Suggest three search queries about renewable energy storage.\",\n },\n ],\n)\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n"},{"label":"Prompt Cache","lang":"Python","source":"import os\nfrom pathlib import Path\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nreference = Path(\"reference.txt\").read_text(encoding=\"utf-8\")\n\nwith client.messages.stream(\n model=\"claude-sonnet-5\",\n max_tokens=1024,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"How long can customers return damaged books, and what must they provide?\",\n },\n ],\n system=[\n {\n \"type\": \"text\",\n \"text\": reference,\n \"cache_control\": {\n \"type\": \"ephemeral\",\n },\n },\n ],\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n\nprint(message.usage.model_dump_json())\n"},{"label":"Adaptive thinking","lang":"Python","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-opus-5\",\n max_tokens=4096,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"A shop sells notebooks for $7 each. Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps.\",\n },\n ],\n thinking={\n \"type\": \"adaptive\",\n },\n output_config={\n \"effort\": \"xhigh\",\n },\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n"},{"label":"Effort control","lang":"Python","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-opus-5\",\n max_tokens=1000,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Summarize the benefit of automated tests in one sentence.\",\n },\n ],\n output_config={\n \"effort\": \"low\",\n },\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n"},{"label":"Streaming","lang":"Python","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-opus-5\",\n max_tokens=1024,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Write a two-line poem about a comet.\",\n },\n ],\n) as stream:\n for text in stream.text_stream:\n print(text, end=\"\", flush=True)\n"},{"label":"Web Fetch","lang":"Python","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-sonnet-5\",\n max_tokens=2048,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Fetch https://arxiv.org/abs/1512.03385 and state the paper title and the proposed learning framework in two sentences.\",\n },\n ],\n tools=[\n {\n \"type\": \"web_fetch_20250910\",\n \"name\": \"web_fetch\",\n \"max_uses\": 3,\n },\n ],\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n\nfor block in message.content:\n if block.type == \"web_fetch_tool_result\":\n print(block.model_dump_json())\n"},{"label":"Image Input","lang":"Python","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-opus-5\",\n max_tokens=1000,\n messages=[\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"image\",\n \"source\": {\n \"type\": \"url\",\n \"url\": \"https://picsum.photos/seed/comet/800/600.jpg\",\n },\n },\n {\n \"type\": \"text\",\n \"text\": \"Describe the visible scene in one sentence.\",\n },\n ],\n },\n ],\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n"},{"label":"Basic","lang":"JavaScript","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst message = await client.messages.create({\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Suggest three search queries about renewable energy storage.\"\n }\n ]\n});\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n"},{"label":"Prompt Cache","lang":"JavaScript","source":"import Anthropic from \"@anthropic-ai/sdk\";\nimport fs from \"node:fs\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst reference = fs.readFileSync(\"reference.txt\", \"utf8\");\n\nconst stream = client.messages.stream({\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"How long can customers return damaged books, and what must they provide?\"\n }\n ],\n \"system\": [\n {\n \"type\": \"text\",\n \"text\": reference,\n \"cache_control\": {\n \"type\": \"ephemeral\"\n }\n }\n ]\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n\nconsole.log(message.usage);\n"},{"label":"Adaptive thinking","lang":"JavaScript","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 4096,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"A shop sells notebooks for $7 each. Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps.\"\n }\n ],\n \"thinking\": {\n \"type\": \"adaptive\"\n },\n \"output_config\": {\n \"effort\": \"xhigh\"\n }\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n"},{"label":"Effort control","lang":"JavaScript","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the benefit of automated tests in one sentence.\"\n }\n ],\n \"output_config\": {\n \"effort\": \"low\"\n }\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n"},{"label":"Streaming","lang":"JavaScript","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Write a two-line poem about a comet.\"\n }\n ]\n});\nstream.on(\"text\", (text) => process.stdout.write(text));\nawait stream.finalMessage();\n"},{"label":"Web Fetch","lang":"JavaScript","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 2048,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Fetch https://arxiv.org/abs/1512.03385 and state the paper title and the proposed learning framework in two sentences.\"\n }\n ],\n \"tools\": [\n {\n \"type\": \"web_fetch_20250910\",\n \"name\": \"web_fetch\",\n \"max_uses\": 3\n }\n ]\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n\nfor (const block of message.content) {\n if (block.type === \"web_fetch_tool_result\") console.log(block);\n}\n"},{"label":"Image Input","lang":"JavaScript","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"image\",\n \"source\": {\n \"type\": \"url\",\n \"url\": \"https://picsum.photos/seed/comet/800/600.jpg\"\n }\n },\n {\n \"type\": \"text\",\n \"text\": \"Describe the visible scene in one sentence.\"\n }\n ]\n }\n ]\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n}\n"},{"label":"Basic","lang":"Shell","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n -d '{\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Suggest three search queries about renewable energy storage.\"\n }\n ]\n}'\n"},{"label":"Prompt Cache","lang":"Shell","source":"request_body=$(jq -n --rawfile reference reference.txt '\n{\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"How long can customers return damaged books, and what must they provide?\"\n }\n ],\n \"system\": [\n {\n \"type\": \"text\",\n \"text\": $reference,\n \"cache_control\": {\n \"type\": \"ephemeral\"\n }\n }\n ],\n \"stream\": true\n}\n')\n\ncurl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n --data-binary \"$request_body\"\n"},{"label":"Adaptive thinking","lang":"Shell","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 4096,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"A shop sells notebooks for $7 each. Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps.\"\n }\n ],\n \"thinking\": {\n \"type\": \"adaptive\"\n },\n \"output_config\": {\n \"effort\": \"xhigh\"\n },\n \"stream\": true\n}'\n"},{"label":"Effort control","lang":"Shell","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the benefit of automated tests in one sentence.\"\n }\n ],\n \"output_config\": {\n \"effort\": \"low\"\n },\n \"stream\": true\n}'\n"},{"label":"Streaming","lang":"Shell","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Write a two-line poem about a comet.\"\n }\n ],\n \"stream\": true\n}'\n"},{"label":"Web Fetch","lang":"Shell","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 2048,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Fetch https://arxiv.org/abs/1512.03385 and state the paper title and the proposed learning framework in two sentences.\"\n }\n ],\n \"tools\": [\n {\n \"type\": \"web_fetch_20250910\",\n \"name\": \"web_fetch\",\n \"max_uses\": 3\n }\n ],\n \"stream\": true\n}'\n"},{"label":"Image Input","lang":"Shell","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-opus-5\",\n \"max_tokens\": 1000,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"image\",\n \"source\": {\n \"type\": \"url\",\n \"url\": \"https://picsum.photos/seed/comet/800/600.jpg\"\n }\n },\n {\n \"type\": \"text\",\n \"text\": \"Describe the visible scene in one sentence.\"\n }\n ]\n }\n ],\n \"stream\": true\n}'\n"},{"label":"Web Search","lang":"Python","source":"import os\nimport anthropic\n\nclient = anthropic.Anthropic(\n base_url=\"https://api.cometapi.com\",\n api_key=os.environ[\"COMETAPI_KEY\"],\n)\n\nwith client.messages.stream(\n model=\"claude-sonnet-5\",\n max_tokens=4096,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Search the web for the official Python 3.14 release date. Answer with the date and cite a source.\",\n },\n ],\n tools=[\n {\n \"type\": \"web_search_20250305\",\n \"name\": \"web_search\",\n \"max_uses\": 3,\n },\n ],\n) as stream:\n message = stream.get_final_message()\n\nfor block in message.content:\n if block.type == \"text\":\n print(block.text)\n\nfor block in message.content:\n if block.type == \"web_search_tool_result\":\n if isinstance(block.content, list):\n for result in block.content:\n if result.type == \"web_search_result\":\n print(result.title, result.url)\n"},{"label":"Web Search","lang":"JavaScript","source":"import Anthropic from \"@anthropic-ai/sdk\";\n\nconst client = new Anthropic({\n apiKey: process.env.COMETAPI_KEY,\n baseURL: \"https://api.cometapi.com\",\n});\n\nconst stream = client.messages.stream({\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 4096,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Search the web for the official Python 3.14 release date. Answer with the date and cite a source.\"\n }\n ],\n \"tools\": [\n {\n \"type\": \"web_search_20250305\",\n \"name\": \"web_search\",\n \"max_uses\": 3\n }\n ]\n});\nconst message = await stream.finalMessage();\n\nfor (const block of message.content) {\n if (block.type === \"text\") console.log(block.text);\n if (block.type === \"web_search_tool_result\" \u0026\u0026 Array.isArray(block.content)) {\n for (const result of block.content) {\n if (result.type === \"web_search_result\") console.log(result.title, result.url);\n }\n }\n}\n"},{"label":"Web Search","lang":"Shell","source":"curl \"https://api.cometapi.com/v1/messages\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-api-key: $COMETAPI_KEY\" \\\n -H \"anthropic-version: 2023-06-01\" \\\n --no-buffer \\\n -d '{\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 4096,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Search the web for the official Python 3.14 release date. Answer with the date and cite a source.\"\n }\n ],\n \"tools\": [\n {\n \"type\": \"web_search_20250305\",\n \"name\": \"web_search\",\n \"max_uses\": 3\n }\n ],\n \"stream\": true\n}'\n"}],"requiredOnlyExamples":true,"requestExampleType":"codeSamples","responseExampleType":"generated","prefillPlaygroundWithExample":true,"prefillPlaygroundExamples":[{"body.model":"claude-opus-5","body.messages.items.0.role":"user","body.messages.items.0.content.oneOf.0":"Suggest three search queries about renewable energy storage.","body.max_tokens":1000},{"body.model":"claude-opus-5","body.messages.items.0.role":"user","body.messages.items.0.content.oneOf.1.items.0.type":"image","body.messages.items.0.content.oneOf.1.items.0.source.type":"url","body.messages.items.0.content.oneOf.1.items.0.source.url":"https://picsum.photos/seed/comet/800/600.jpg","body.messages.items.0.content.oneOf.1.items.1.type":"text","body.messages.items.0.content.oneOf.1.items.1.text":"Describe the visible scene in one sentence.","body.max_tokens":1000,"body.stream":true},{"body.model":"claude-sonnet-5","body.messages.items.0.role":"user","body.messages.items.0.content.oneOf.0":"How long can customers return damaged books, and what must they provide?","body.max_tokens":1024,"body.system.oneOf.1.items.0.type":"text","body.system.oneOf.1.items.0.text":"Comet Books sample reference. The following policies describe a fictional bookstore.\n\nSection 1: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 2: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 3: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 4: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 5: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 6: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 7: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 8: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 9: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 10: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 11: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 12: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 13: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 14: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 15: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 16: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 17: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 18: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 19: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 20: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 21: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 22: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 23: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 24: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 25: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 26: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 27: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 28: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.","body.system.oneOf.1.items.0.cache_control.type":"ephemeral","body.stream":true},{"body.model":"claude-opus-5","body.messages.items.0.role":"user","body.messages.items.0.content.oneOf.0":"Write a two-line poem about a comet.","body.max_tokens":1024,"body.stream":true},{"body.model":"claude-sonnet-5","body.messages.items.0.role":"user","body.messages.items.0.content.oneOf.0":"Fetch https://arxiv.org/abs/1512.03385 and state the paper title and the proposed learning framework in two sentences.","body.max_tokens":2048,"body.stream":true,"body.tools.items.0.name":"web_fetch","body.tools.items.0.type":"web_fetch_20250910","body.tools.items.0.max_uses":3},{"body.model":"claude-opus-5","body.messages.items.0.role":"user","body.messages.items.0.content.oneOf.0":"A shop sells notebooks for $7 each. Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps.","body.max_tokens":4096,"body.stream":true,"body.thinking.type":"adaptive","body.output_config.effort":"xhigh"},{"body.model":"claude-opus-5","body.messages.items.0.role":"user","body.messages.items.0.content.oneOf.0":"Summarize the benefit of automated tests in one sentence.","body.max_tokens":1000,"body.stream":true,"body.output_config.effort":"low"},{"body.model":"claude-sonnet-5","body.messages.items.0.role":"user","body.messages.items.0.content.oneOf.0":"Search the web for the official Python 3.14 release date. Answer with the date and cite a source.","body.max_tokens":4096,"body.stream":true,"body.tools.items.0.name":"web_search","body.tools.items.0.type":"web_search_20250305","body.tools.items.0.max_uses":3}]},"dependencies":{"parameters":{"c0c1ea46-657f-4fbb-8cbc-ef036d66b820":{"name":"anthropic-version","in":"header","required":false,"description":"The Anthropic API version to use. Defaults to `2023-06-01`.","schema":{"type":"string","default":"2023-06-01","example":"2023-06-01","isRequired":false,"description":"The Anthropic API version to use. Defaults to `2023-06-01`.","uniqueKey":"","typeLabel":"string"}},"c209249d-4c9e-4e35-be30-3090e0add122":{"name":"anthropic-beta","in":"header","required":false,"description":"Comma-separated feature identifiers required by a specific beta API feature. Omit this header for the examples on this page.","schema":{"type":"string","isRequired":false,"description":"Comma-separated feature identifiers required by a specific beta API feature. Omit this header for the examples on this page.","uniqueKey":"","typeLabel":"string"}}},"requestBody":{"required":true,"content":{"application/json":{"schema":{"type":"object","required":["model","messages","max_tokens"],"properties":{"model":{"type":"string","description":"The Claude model to use. See the [Models page](/overview/models) for available Claude model IDs.","example":"claude-opus-5","default":"claude-opus-5","isRequired":true,"uniqueKey":"model","typeLabel":"string"},"messages":{"type":"array","description":"Conversation history. Use user and assistant messages with text strings or content-block arrays. Return complete assistant content blocks when continuing a tool call.","items":{"type":"object","required":["role","content"],"properties":{"role":{"type":"string","description":"The role of the message author.","enum":["user","assistant"],"isRequired":true,"uniqueKey":"messages.items.[INDEX].role","typeLabel":"enum\u003cstring>"},"content":{"oneOf":[{"type":"string","description":"The message content. Either a plain string or an array of content blocks for multimodal input.","isRequired":true,"uniqueKey":"messages.items.[INDEX].content.oneOf.0","typeLabel":"string"},{"type":"array","items":{"type":"object","properties":{"type":{"type":"string","description":"The content block type.","enum":["text","image","document","thinking","redacted_thinking","tool_use","tool_result","server_tool_use","web_fetch_tool_result","web_search_tool_result"],"uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].type","typeLabel":"enum\u003cstring>"},"text":{"type":"string","description":"Text content (for `text` type blocks).","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].text","typeLabel":"string"},"source":{"type":"object","description":"Source data for `image` or `document` blocks.","properties":{"type":{"type":"string","enum":["base64","url"],"description":"Image source type: `url` for a public image URL, or `base64` for inline data.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].source.type","typeLabel":"enum\u003cstring>"},"media_type":{"type":"string","description":"Image MIME type for base64 sources, such as `image/jpeg` or `image/png`.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].source.media_type","typeLabel":"string"},"data":{"type":"string","description":"Base64-encoded image bytes when `type` is `base64`.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].source.data","typeLabel":"string"},"url":{"type":"string","description":"Public HTTPS URL for the image or document.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].source.url","typeLabel":"string"}},"uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].source","typeLabel":"object"},"cache_control":{"type":"object","description":"Cache control for prompt caching. Set `{\"type\": \"ephemeral\"}` to cache this content block.","properties":{"type":{"type":"string","enum":["ephemeral"],"description":"Cache control type. Use `ephemeral`.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].cache_control.type","typeLabel":"enum\u003cstring>"},"ttl":{"type":"string","enum":["5m","1h"],"description":"Cache lifetime. Use 5m for five minutes or 1h for one hour. The default is 5m.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].cache_control.ttl","typeLabel":"enum\u003cstring>"}},"uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].cache_control","typeLabel":"object"},"id":{"type":"string","description":"The ID from a returned tool_use block. Preserve this value in assistant history.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].id","typeLabel":"string"},"name":{"type":"string","description":"The function name in a tool_use block.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].name","typeLabel":"string"},"input":{"type":"object","description":"Function arguments in a tool_use block.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].input","typeLabel":"object"},"tool_use_id":{"type":"string","description":"The ID of the tool_use block answered by this tool_result.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].tool_use_id","typeLabel":"string"},"content":{"oneOf":[{"type":"string","description":"Tool result content: a string, an array of content blocks, or a server-tool result or error object.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].content.oneOf.0","typeLabel":"string"},{"type":"array","items":{"type":"object","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].content.oneOf.1.items.[INDEX]","typeLabel":"object"},"description":"Tool result content: a string, an array of content blocks, or a server-tool result or error object.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].content.oneOf.1","typeLabel":"object[]"},{"type":"object","description":"Tool result content: a string, an array of content blocks, or a server-tool result or error object.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].content.oneOf.2","typeLabel":"object"}],"uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].content","typeLabel":"string | object[] | object"},"is_error":{"type":"boolean","description":"Set true when a client tool_result reports a failed tool execution.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].is_error","typeLabel":"boolean"},"thinking":{"type":"string","description":"Thinking content returned in an assistant block. Preserve it unchanged in conversation history.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].thinking","typeLabel":"string"},"signature":{"type":"string","description":"Thinking signature returned by the API. Preserve it unchanged with its thinking block.","uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX].signature","typeLabel":"string"}},"uniqueKey":"messages.items.[INDEX].content.oneOf.1.items.[INDEX]","typeLabel":"object"},"description":"The message content. Either a plain string or an array of content blocks for multimodal input.","isRequired":true,"uniqueKey":"messages.items.[INDEX].content.oneOf.1","typeLabel":"object[]"}],"isRequired":true,"uniqueKey":"messages.items.[INDEX].content","typeLabel":"string | object[]"}},"uniqueKey":"messages.items.[INDEX]","typeLabel":"object"},"isRequired":true,"uniqueKey":"messages","typeLabel":"object[]"},"max_tokens":{"type":"integer","description":"The maximum number of tokens to generate. The model may stop before reaching this limit. When using `thinking`, the thinking tokens count towards this limit.","minimum":1,"example":1024,"isRequired":true,"uniqueKey":"max_tokens","typeLabel":"integer"},"system":{"oneOf":[{"type":"string","description":"System prompt providing context and instructions to Claude. Can be a plain string or an array of content blocks (useful for prompt caching).","uniqueKey":"system.oneOf.0","typeLabel":"string"},{"type":"array","items":{"type":"object","properties":{"type":{"type":"string","enum":["text"],"description":"Content block type, `text`.","uniqueKey":"system.oneOf.1.items.[INDEX].type","typeLabel":"enum\u003cstring>"},"text":{"type":"string","description":"System prompt text for this block.","uniqueKey":"system.oneOf.1.items.[INDEX].text","typeLabel":"string"},"cache_control":{"type":"object","properties":{"type":{"type":"string","enum":["ephemeral"],"description":"Cache control type. Use `ephemeral`.","uniqueKey":"system.oneOf.1.items.[INDEX].cache_control.type","typeLabel":"enum\u003cstring>"},"ttl":{"type":"string","enum":["5m","1h"],"description":"Cache lifetime. Use 5m for five minutes or 1h for one hour. The default is 5m.","uniqueKey":"system.oneOf.1.items.[INDEX].cache_control.ttl","typeLabel":"enum\u003cstring>"}},"description":"Marks this system block as a prompt-cache breakpoint.","uniqueKey":"system.oneOf.1.items.[INDEX].cache_control","typeLabel":"object"}},"uniqueKey":"system.oneOf.1.items.[INDEX]","typeLabel":"object"},"description":"System prompt providing context and instructions to Claude. Can be a plain string or an array of content blocks (useful for prompt caching).","uniqueKey":"system.oneOf.1","typeLabel":"object[]"}],"uniqueKey":"system","typeLabel":"string | object[]"},"temperature":{"type":"number","description":"Sampling temperature. The examples omit sampling overrides.","minimum":0,"maximum":1,"uniqueKey":"temperature","typeLabel":"number"},"top_p":{"type":"number","description":"Nucleus sampling threshold. The examples omit sampling overrides.","minimum":0,"maximum":1,"uniqueKey":"top_p","typeLabel":"number"},"top_k":{"type":"integer","description":"Limits sampling to the k most likely tokens. The examples omit sampling overrides.","minimum":0,"uniqueKey":"top_k","typeLabel":"integer"},"stream":{"type":"boolean","description":"If `true`, stream the response incrementally using Server-Sent Events (SSE). Events include `message_start`, `content_block_start`, `content_block_delta`, `content_block_stop`, `message_delta`, and `message_stop`.","default":false,"uniqueKey":"stream","typeLabel":"boolean"},"stop_sequences":{"type":"array","description":"Custom strings that cause the model to stop generating when encountered. The stop sequence is not included in the response.","items":{"type":"string","uniqueKey":"stop_sequences.items.[INDEX]","typeLabel":"string"},"uniqueKey":"stop_sequences","typeLabel":"string[]"},"thinking":{"type":"object","description":"Thinking configuration. The adaptive example uses type adaptive and sets output_config.effort separately.","properties":{"type":{"type":"string","description":"Thinking mode. Use adaptive for the example on this page. Other values depend on the selected model.","enum":["adaptive","disabled","enabled"],"uniqueKey":"thinking.type","typeLabel":"enum\u003cstring>"},"budget_tokens":{"type":"integer","description":"Token budget for models that support manual thinking with type enabled. Omit this field when using type adaptive.","minimum":1024,"uniqueKey":"thinking.budget_tokens","typeLabel":"integer"},"display":{"type":"string","description":"Controls visible thinking blocks on models that support display selection. `summarized` returns a readable thinking summary; `omitted` returns an empty thinking field with continuity metadata where applicable.","enum":["summarized","omitted"],"uniqueKey":"thinking.display","typeLabel":"enum\u003cstring>"}},"uniqueKey":"thinking","typeLabel":"object"},"tools":{"type":"array","description":"Client tools define a name and input_schema. Server tools use a versioned type and name, such as the web_fetch and web_search examples on this page.","items":{"type":"object","properties":{"name":{"type":"string","description":"Tool name. The model repeats it in `tool_use` blocks when it calls the tool.","uniqueKey":"tools.items.[INDEX].name","typeLabel":"string"},"description":{"type":"string","description":"A description of what the tool does.","uniqueKey":"tools.items.[INDEX].description","typeLabel":"string"},"input_schema":{"type":"object","description":"JSON Schema defining the tool's input parameters.","uniqueKey":"tools.items.[INDEX].input_schema","typeLabel":"object"},"type":{"type":"string","description":"Versioned server tool type. The basic examples use web_fetch_20250910 and web_search_20250305.","uniqueKey":"tools.items.[INDEX].type","typeLabel":"string"},"max_uses":{"type":"integer","description":"Maximum uses of this server tool within one request.","uniqueKey":"tools.items.[INDEX].max_uses","typeLabel":"integer"}},"uniqueKey":"tools.items.[INDEX]","typeLabel":"object"},"uniqueKey":"tools","typeLabel":"object[]"},"tool_choice":{"type":"object","description":"Controls how the model uses tools.","properties":{"type":{"type":"string","description":"The tool choice mode: `auto` (model decides), `any` (must use a tool), `tool` (must use a specific tool), or `none` (no tools).","enum":["auto","any","tool","none"],"uniqueKey":"tool_choice.type","typeLabel":"enum\u003cstring>"},"name":{"type":"string","description":"The specific tool name to use. Required when `type` is `tool`.","uniqueKey":"tool_choice.name","typeLabel":"string"},"disable_parallel_tool_use":{"type":"boolean","description":"If `true`, prevent the model from calling multiple tools in parallel.","uniqueKey":"tool_choice.disable_parallel_tool_use","typeLabel":"boolean"}},"uniqueKey":"tool_choice","typeLabel":"object"},"metadata":{"type":"object","description":"Request metadata for tracking and analytics.","properties":{"user_id":{"type":"string","description":"An external identifier for the user making the request. Used for abuse detection.","uniqueKey":"metadata.user_id","typeLabel":"string"}},"uniqueKey":"metadata","typeLabel":"object"},"output_config":{"type":"object","description":"Configuration for reasoning effort and structured output.","properties":{"effort":{"type":"string","description":"Reasoning effort. The examples use low for a brief answer and xhigh with adaptive thinking.","enum":["low","medium","high","xhigh","max"],"example":"medium","uniqueKey":"output_config.effort","typeLabel":"enum\u003cstring>"},"format":{"type":"object","description":"Structured output configuration for supported models. See the [structured outputs documentation](https://platform.claude.com/docs/en/build-with-claude/structured-outputs) for schema requirements.","required":["type","schema"],"properties":{"type":{"type":"string","enum":["json_schema"],"description":"Set json_schema to request output matching the supplied schema.","isRequired":true,"uniqueKey":"output_config.format.type","typeLabel":"enum\u003cstring>"},"schema":{"type":"object","description":"JSON Schema that describes the requested output.","isRequired":true,"uniqueKey":"output_config.format.schema","typeLabel":"object"}},"uniqueKey":"output_config.format","typeLabel":"object"}},"uniqueKey":"output_config","typeLabel":"object"},"service_tier":{"type":"string","description":"The service tier to use. `auto` tries priority capacity first, `standard_only` uses only standard capacity.","enum":["auto","standard_only"],"uniqueKey":"service_tier","typeLabel":"enum\u003cstring>"}},"uniqueKey":"","typeLabel":"object"},"examples":{"Default":{"title":"Default","value":{"model":"claude-opus-5","max_tokens":1000,"messages":[{"role":"user","content":"Suggest three search queries about renewable energy storage."}]}},"Image Input":{"title":"Image Input","value":{"model":"claude-opus-5","max_tokens":1000,"messages":[{"role":"user","content":[{"type":"image","source":{"type":"url","url":"https://picsum.photos/seed/comet/800/600.jpg"}},{"type":"text","text":"Describe the visible scene in one sentence."}]}],"stream":true}},"Prompt Cache":{"title":"Prompt Cache","description":"The code samples read this reference material from a local UTF-8 reference.txt file. Keep the cached prefix unchanged when repeating the request.","value":{"model":"claude-sonnet-5","max_tokens":1024,"messages":[{"role":"user","content":"How long can customers return damaged books, and what must they provide?"}],"system":[{"type":"text","text":"Comet Books sample reference. The following policies describe a fictional bookstore.\n\nSection 1: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 2: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 3: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 4: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 5: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 6: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 7: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 8: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 9: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 10: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 11: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 12: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 13: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 14: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 15: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 16: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 17: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 18: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 19: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 20: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 21: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 22: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 23: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 24: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 25: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 26: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 27: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.\nSection 28: Damaged books may be returned within 30 days. A receipt is required. Unopened stationery may be exchanged within 14 days. Digital downloads are final. Staff record the order reference and explain the return steps clearly.","cache_control":{"type":"ephemeral"}}],"stream":true}},"Streaming":{"title":"Streaming","value":{"model":"claude-opus-5","max_tokens":1024,"messages":[{"role":"user","content":"Write a two-line poem about a comet."}],"stream":true}},"Web Fetch":{"title":"Web Fetch","value":{"model":"claude-sonnet-5","max_tokens":2048,"messages":[{"role":"user","content":"Fetch https://arxiv.org/abs/1512.03385 and state the paper title and the proposed learning framework in two sentences."}],"tools":[{"type":"web_fetch_20250910","name":"web_fetch","max_uses":3}],"stream":true}},"Adaptive Thinking":{"title":"Adaptive Thinking","value":{"model":"claude-opus-5","max_tokens":4096,"messages":[{"role":"user","content":"A shop sells notebooks for $7 each. Buying three earns a $4 discount. A customer pays $20 for three notebooks. Calculate the total and the change, and explain your steps."}],"thinking":{"type":"adaptive"},"output_config":{"effort":"xhigh"},"stream":true}},"Effort control":{"title":"Effort control","value":{"model":"claude-opus-5","max_tokens":1000,"messages":[{"role":"user","content":"Summarize the benefit of automated tests in one sentence."}],"output_config":{"effort":"low"},"stream":true}},"Web Search":{"title":"Web Search","value":{"model":"claude-sonnet-5","max_tokens":4096,"messages":[{"role":"user","content":"Search the web for the official Python 3.14 release date. Answer with the date and cite a source."}],"tools":[{"type":"web_search_20250305","name":"web_search","max_uses":3}],"stream":true}}},"exampleType":"examples"}},"exampleType":"examples"},"responses":{"1032aebb-739d-48e8-8890-b9f6a600141a":{"description":"Successful response. When `stream` is `true`, the response is a stream of SSE events.","content":{"application/json":{"schema":{"type":"object","properties":{"id":{"type":"string","description":"Message identifier returned by the API.","uniqueKey":"id","typeLabel":"string"},"type":{"type":"string","description":"Always `message`.","enum":["message"],"uniqueKey":"type","typeLabel":"enum\u003cstring>"},"role":{"type":"string","description":"Always `assistant`.","enum":["assistant"],"uniqueKey":"role","typeLabel":"enum\u003cstring>"},"content":{"type":"array","description":"The response content blocks. May include `text`, `thinking`, `tool_use`, and other block types.","items":{"type":"object","properties":{"type":{"type":"string","description":"Content block type, such as text, thinking, tool_use, server_tool_use, web_fetch_tool_result, or web_search_tool_result.","uniqueKey":"content.items.[INDEX].type","typeLabel":"string"},"text":{"type":"string","description":"The generated text (for `text` blocks).","uniqueKey":"content.items.[INDEX].text","typeLabel":"string"},"thinking":{"type":"string","description":"Thinking text or summary for `thinking` blocks when the selected model returns visible thinking content.","uniqueKey":"content.items.[INDEX].thinking","typeLabel":"string"},"signature":{"type":"string","description":"Cryptographic signature for the thinking block.","uniqueKey":"content.items.[INDEX].signature","typeLabel":"string"},"id":{"type":"string","description":"Tool use ID (for `tool_use` blocks).","uniqueKey":"content.items.[INDEX].id","typeLabel":"string"},"name":{"type":"string","description":"Tool name (for `tool_use` blocks).","uniqueKey":"content.items.[INDEX].name","typeLabel":"string"},"input":{"type":"object","description":"Tool input arguments (for `tool_use` blocks).","uniqueKey":"content.items.[INDEX].input","typeLabel":"object"},"tool_use_id":{"type":"string","description":"The server tool call answered by this result block.","uniqueKey":"content.items.[INDEX].tool_use_id","typeLabel":"string"},"content":{"oneOf":[{"type":"object","description":"Server tool results or an error object. Inspect the block type before reading its fields.","uniqueKey":"content.items.[INDEX].content.oneOf.0","typeLabel":"object"},{"type":"array","items":{"type":"object","uniqueKey":"content.items.[INDEX].content.oneOf.1.items.[INDEX]","typeLabel":"object"},"description":"Server tool results or an error object. Inspect the block type before reading its fields.","uniqueKey":"content.items.[INDEX].content.oneOf.1","typeLabel":"object[]"}],"uniqueKey":"content.items.[INDEX].content","typeLabel":"object | object[]"},"citations":{"type":"array","description":"Source citations attached to a text block when returned.","items":{"type":"object","uniqueKey":"content.items.[INDEX].citations.items.[INDEX]","typeLabel":"object"},"uniqueKey":"content.items.[INDEX].citations","typeLabel":"object[]"}},"uniqueKey":"content.items.[INDEX]","typeLabel":"object"},"uniqueKey":"content","typeLabel":"object[]"},"model":{"type":"string","description":"Model ID reported by the response.","uniqueKey":"model","typeLabel":"string"},"stop_reason":{"type":"string","description":"Why the model stopped generating. `refusal` can be returned as a successful HTTP response when the model declines a request.","enum":["end_turn","max_tokens","stop_sequence","tool_use","pause_turn","refusal"],"uniqueKey":"stop_reason","typeLabel":"enum\u003cstring>"},"stop_sequence":{"oneOf":[{"type":"string","description":"The stop sequence that caused the model to stop, if applicable.","uniqueKey":"stop_sequence.oneOf.0","typeLabel":"string"},{"type":"null","description":"The stop sequence that caused the model to stop, if applicable.","uniqueKey":"stop_sequence.oneOf.1","typeLabel":"null"}],"uniqueKey":"stop_sequence","typeLabel":"string | null"},"usage":{"type":"object","description":"Token usage statistics.","properties":{"input_tokens":{"type":"integer","description":"Uncached input tokens processed for the request. Cache creation and cache reads have separate counters.","uniqueKey":"usage.input_tokens","typeLabel":"integer"},"output_tokens":{"type":"integer","description":"Total output tokens, including thinking when the model uses thinking.","uniqueKey":"usage.output_tokens","typeLabel":"integer"},"cache_creation_input_tokens":{"type":"integer","description":"Number of input tokens used to create the prompt cache.","uniqueKey":"usage.cache_creation_input_tokens","typeLabel":"integer"},"cache_read_input_tokens":{"type":"integer","description":"Number of input tokens read from the prompt cache.","uniqueKey":"usage.cache_read_input_tokens","typeLabel":"integer"},"cache_creation":{"type":"object","description":"Detailed cache creation token breakdown by TTL tier.","properties":{"ephemeral_5m_input_tokens":{"type":"integer","description":"Tokens written to 5-minute ephemeral cache.","uniqueKey":"usage.cache_creation.ephemeral_5m_input_tokens","typeLabel":"integer"},"ephemeral_1h_input_tokens":{"type":"integer","description":"Tokens written to 1-hour ephemeral cache.","uniqueKey":"usage.cache_creation.ephemeral_1h_input_tokens","typeLabel":"integer"}},"uniqueKey":"usage.cache_creation","typeLabel":"object"},"output_tokens_details":{"type":"object","description":"Detailed output token breakdown when returned by the selected model.","properties":{"thinking_tokens":{"type":"integer","description":"Number of output tokens used for model thinking when reported.","uniqueKey":"usage.output_tokens_details.thinking_tokens","typeLabel":"integer"}},"uniqueKey":"usage.output_tokens_details","typeLabel":"object"},"server_tool_use":{"type":"object","description":"Server tool request counts when server tools are used.","properties":{"web_fetch_requests":{"type":"integer","description":"Number of web fetch requests.","uniqueKey":"usage.server_tool_use.web_fetch_requests","typeLabel":"integer"},"web_search_requests":{"type":"integer","description":"Number of web search requests.","uniqueKey":"usage.server_tool_use.web_search_requests","typeLabel":"integer"}},"uniqueKey":"usage.server_tool_use","typeLabel":"object"}},"uniqueKey":"usage","typeLabel":"object"}},"example":{"id":"msg_example","type":"message","role":"assistant","model":"claude-opus-5","content":[{"type":"text","text":"Here are three search queries covering different angles of the topic:\n\n1. **\"grid-scale battery storage cost trends 2024 2025\"**\n — Targets economics and recent price data for lithium-ion and other utility-scale systems.\n\n2. **\"long-duration energy storage technologies comparison flow battery vs compressed air vs thermal\"**\n — Surfaces technical comparisons of options for storage beyond the 4–8 hour range, where lithium-ion becomes less cost-effective.\n\n3. **\"green hydrogen seasonal storage feasibility round-trip efficiency\"**\n — Digs into the viability of hydrogen for multi-week or seasonal balancing, including its efficiency penalties.\n\n**A few tips for refining these:**\n- Add `site:.gov` or `site:.edu` to prioritize research and agency reports (e.g., NREL, IEA, DOE).\n- Append a region like `Europe`, `India`, or `California` if you need location-specific policy or deployment data.\n- Try `filetype:pdf` to pull up technical white papers and government studies directly.\n\nWant me to tailor these toward a specific use case — academic research, investment analysis, or policy work?"}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":23,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":437,"output_tokens_details":{"thinking_tokens":50}}},"uniqueKey":"","typeLabel":"object"},"example":{"id":"msg_example","type":"message","role":"assistant","model":"claude-opus-5","content":[{"type":"text","text":"Here are three search queries covering different angles of the topic:\n\n1. **\"grid-scale battery storage cost trends 2024 2025\"**\n — Targets economics and recent price data for lithium-ion and other utility-scale systems.\n\n2. **\"long-duration energy storage technologies comparison flow battery vs compressed air vs thermal\"**\n — Surfaces technical comparisons of options for storage beyond the 4–8 hour range, where lithium-ion becomes less cost-effective.\n\n3. **\"green hydrogen seasonal storage feasibility round-trip efficiency\"**\n — Digs into the viability of hydrogen for multi-week or seasonal balancing, including its efficiency penalties.\n\n**A few tips for refining these:**\n- Add `site:.gov` or `site:.edu` to prioritize research and agency reports (e.g., NREL, IEA, DOE).\n- Append a region like `Europe`, `India`, or `California` if you need location-specific policy or deployment data.\n- Try `filetype:pdf` to pull up technical white papers and government studies directly.\n\nWant me to tailor these toward a specific use case — academic research, investment analysis, or policy 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