Riferimento API
Guide all'integrazione
Prezzi e fatturazione
Anthropic Messages
Usa l’API Anthropic Messages tramite CometAPI per accedere ai modelli Claude con extended thinking, prompt caching, uso di tool, web search/fetch, streaming e controllo dell’effort.
import anthropic
client = anthropic.Anthropic(
base_url="https://api.cometapi.com",
api_key="<COMETAPI_KEY>",
)
message = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=1024,
system="You are a helpful assistant.",
messages=[
{"role": "user", "content": "Hello, world"}
],
)
print(message.content[0].text){
"id": "<string>",
"type": "message",
"role": "assistant",
"content": [
{
"type": "text",
"text": "<string>",
"thinking": "<string>",
"signature": "<string>",
"id": "<string>",
"name": "<string>",
"input": {}
}
],
"model": "<string>",
"stop_reason": "end_turn",
"stop_sequence": "<string>",
"usage": {
"input_tokens": 123,
"output_tokens": 123,
"cache_creation_input_tokens": 123,
"cache_read_input_tokens": 123,
"cache_creation": {
"ephemeral_5m_input_tokens": 123,
"ephemeral_1h_input_tokens": 123
}
}
}Panoramica
CometAPI supporta nativamente l’API Anthropic Messages, offrendoti accesso diretto ai modelli Claude con tutte le funzionalità specifiche di Anthropic. Usa questo endpoint per capacità esclusive di Claude come extended thinking, prompt caching e controllo dell’effort.Avvio rapido
Usa l’SDK ufficiale di Anthropic — ti basta impostare l’URL di base su CometAPI:import anthropic
client = anthropic.Anthropic(
base_url="https://api.cometapi.com",
api_key="<COMETAPI_KEY>",
)
message = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello!"}],
)
print(message.content[0].text)
x-api-key sia Authorization: Bearer per l’autenticazione. Gli SDK ufficiali di Anthropic usano x-api-key per impostazione predefinita.Extended Thinking
Abilita il ragionamento passo dopo passo di Claude con il parametrothinking. La risposta include blocchi di contenuto thinking che mostrano il ragionamento interno di Claude prima della risposta finale.
message = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=16000,
thinking={
"type": "enabled",
"budget_tokens": 10000,
},
messages=[
{"role": "user", "content": "Prove that there are infinitely many primes."}
],
)
for block in message.content:
if block.type == "thinking":
print(f"Thinking: {block.thinking[:200]}...")
elif block.type == "text":
print(f"Answer: {block.text}")
budget_tokens pari a 1,024. I token di thinking vengono conteggiati nel limite max_tokens — imposta max_tokens a un valore sufficientemente alto per includere sia il thinking sia la risposta.Prompt Caching
Memorizza nella cache prompt di sistema di grandi dimensioni o prefissi di conversazione per ridurre latenza e costo nelle richieste successive. Aggiungicache_control ai blocchi di contenuto che devono essere memorizzati nella cache:
message = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=1024,
system=[
{
"type": "text",
"text": "You are an expert code reviewer. [Long detailed instructions...]",
"cache_control": {"type": "ephemeral"},
}
],
messages=[{"role": "user", "content": "Review this code..."}],
)
usage della risposta:
cache_creation_input_tokens— token scritti nella cache (fatturati a una tariffa più alta)cache_read_input_tokens— token letti dalla cache (fatturati a una tariffa ridotta)
Streaming
Trasmetti le risposte in Streaming usando Server-Sent Events (SSE) impostandostream: true. Gli eventi arrivano in questo ordine:
message_start— contiene i metadati del messaggio e l’utilizzo inizialecontent_block_start— indica l’inizio di ciascun blocco di contenutocontent_block_delta— frammenti di testo incrementali (text_delta)content_block_stop— indica la fine di ciascun blocco di contenutomessage_delta—stop_reasonfinale eusagecompletomessage_stop— segnala la fine dello stream
with client.messages.stream(
model="claude-sonnet-4-6",
max_tokens=256,
messages=[{"role": "user", "content": "Hello"}],
) as stream:
for text in stream.text_stream:
print(text, end="")
Controllo dell’effort
Controlla quanto effort Claude mette nella generazione di una risposta conoutput_config.effort:
message = client.messages.create(
model="claude-opus-4-6",
max_tokens=4096,
messages=[
{"role": "user", "content": "Summarize this briefly."}
],
output_config={"effort": "low"}, # "low", "medium", or "high"
)
Server Tools
Claude supporta strumenti lato server che vengono eseguiti sull’infrastruttura di Anthropic:- Web Fetch
- Web Search
message = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=1024,
messages=[
{"role": "user", "content": "Analyze the content at https://arxiv.org/abs/1512.03385"}
],
tools=[
{"type": "web_fetch_20250910", "name": "web_fetch", "max_uses": 5}
],
)
message = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=1024,
messages=[
{"role": "user", "content": "What are the latest developments in AI?"}
],
tools=[
{"type": "web_search_20250305", "name": "web_search", "max_uses": 5}
],
)
Esempio di risposta
Una risposta tipica dall’endpoint Anthropic di CometAPI:{
"id": "msg_bdrk_01UjHdmSztrL7QYYm7CKBDFB",
"type": "message",
"role": "assistant",
"content": [
{
"type": "text",
"text": "Hello!"
}
],
"model": "claude-sonnet-4-6",
"stop_reason": "end_turn",
"stop_sequence": null,
"usage": {
"input_tokens": 19,
"cache_creation_input_tokens": 0,
"cache_read_input_tokens": 0,
"cache_creation": {
"ephemeral_5m_input_tokens": 0,
"ephemeral_1h_input_tokens": 0
},
"output_tokens": 4
}
}
Differenze principali rispetto all’endpoint compatibile con OpenAI
| Funzionalità | Anthropic Messages (/v1/messages) | OpenAI-Compatible (/v1/chat/completions) |
|---|---|---|
| Extended thinking | parametro thinking con budget_tokens | Non disponibile |
| Prompt caching | cache_control sui blocchi di contenuto | Non disponibile |
| Controllo dell’effort | output_config.effort | Non disponibile |
| Web fetch/search | Server tools (web_fetch, web_search) | Non disponibile |
| Header di autenticazione | x-api-key o Bearer | Solo Bearer |
| Formato della risposta | formato Anthropic (content blocks) | formato OpenAI (choices, message) |
| Modelli | Solo Claude | Multi-provider (GPT, Claude, Gemini, ecc.) |
Autorizzazioni
Your CometAPI key passed via the x-api-key header. Authorization: Bearer <key> is also supported.
Intestazioni
The Anthropic API version to use. Defaults to 2023-06-01.
"2023-06-01"
Comma-separated list of beta features to enable. Examples: max-tokens-3-5-sonnet-2024-07-15, pdfs-2024-09-25, output-128k-2025-02-19.
Corpo
The Claude model to use. See the Models page for current Claude model IDs.
"claude-sonnet-4-6"
The conversation messages. Must alternate between user and assistant roles. Each message's content can be a string or an array of content blocks (text, image, document, tool_use, tool_result). There is a limit of 100,000 messages per request.
Show child attributes
Show child attributes
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.
x >= 11024
System prompt providing context and instructions to Claude. Can be a plain string or an array of content blocks (useful for prompt caching).
Controls randomness in the response. Range: 0.0–1.0. Use lower values for analytical tasks and higher values for creative tasks. Defaults to 1.0.
0 <= x <= 1Nucleus sampling threshold. Only tokens with cumulative probability up to this value are considered. Range: 0.0–1.0. Use either temperature or top_p, not both.
0 <= x <= 1Only sample from the top K most probable tokens. Recommended for advanced use cases only.
x >= 0If 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.
Custom strings that cause the model to stop generating when encountered. The stop sequence is not included in the response.
Enable extended thinking — Claude's step-by-step reasoning process. When enabled, the response includes thinking content blocks before the answer. Requires a minimum budget_tokens of 1,024.
Show child attributes
Show child attributes
Tools the model may use. Supports client-defined functions, web search (web_search_20250305), web fetch (web_fetch_20250910), code execution (code_execution_20250522), and more.
Show child attributes
Show child attributes
Controls how the model uses tools.
Show child attributes
Show child attributes
Request metadata for tracking and analytics.
Show child attributes
Show child attributes
Configuration for output behavior.
Show child attributes
Show child attributes
The service tier to use. auto tries priority capacity first, standard_only uses only standard capacity.
auto, standard_only Risposta
Successful response. When stream is true, the response is a stream of SSE events.
Unique identifier for this message (e.g., msg_01XFDUDYJgAACzvnptvVoYEL).
Always message.
message Always assistant.
assistant The response content blocks. May include text, thinking, tool_use, and other block types.
Show child attributes
Show child attributes
The specific model version that generated this response (e.g., claude-sonnet-4-6).
Why the model stopped generating.
end_turn, max_tokens, stop_sequence, tool_use, pause_turn The stop sequence that caused the model to stop, if applicable.
Token usage statistics.
Show child attributes
Show child attributes
import anthropic
client = anthropic.Anthropic(
base_url="https://api.cometapi.com",
api_key="<COMETAPI_KEY>",
)
message = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=1024,
system="You are a helpful assistant.",
messages=[
{"role": "user", "content": "Hello, world"}
],
)
print(message.content[0].text){
"id": "<string>",
"type": "message",
"role": "assistant",
"content": [
{
"type": "text",
"text": "<string>",
"thinking": "<string>",
"signature": "<string>",
"id": "<string>",
"name": "<string>",
"input": {}
}
],
"model": "<string>",
"stop_reason": "end_turn",
"stop_sequence": "<string>",
"usage": {
"input_tokens": 123,
"output_tokens": 123,
"cache_creation_input_tokens": 123,
"cache_read_input_tokens": 123,
"cache_creation": {
"ephemeral_5m_input_tokens": 123,
"ephemeral_1h_input_tokens": 123
}
}
}