Übersicht
LemonData unterstützt das native Anthropic Messages API-Format. Verwenden Sie das offizielle Anthropic SDK mit LemonData, um auf Claude-Modelle zuzugreifen.
Installation
Konfiguration
from anthropic import Anthropic
client = Anthropic(
api_key="sk-your-lemondata-key",
base_url="https://api.lemondata.cc"
)
Hinweis: Die Basis-URL für das Anthropic SDK ist https://api.lemondata.cc (ohne /v1).
Grundlegende Verwendung
message = client.messages.create(
model="claude-sonnet-4-5",
max_tokens=1024,
messages=[
{"role": "user", "content": "Hello, Claude!"}
]
)
print(message.content[0].text)
Mit System-Prompt
message = client.messages.create(
model="claude-sonnet-4-5",
max_tokens=1024,
system="You are a helpful coding assistant.",
messages=[
{"role": "user", "content": "Write a Python function to reverse a string"}
]
)
Streaming
with client.messages.stream(
model="claude-sonnet-4-5",
max_tokens=1024,
messages=[{"role": "user", "content": "Tell me a story"}]
) as stream:
for text in stream.text_stream:
print(text, end="", flush=True)
Vision
import base64
# From URL
message = client.messages.create(
model="claude-sonnet-4-5",
max_tokens=1024,
messages=[{
"role": "user",
"content": [
{"type": "text", "text": "What's in this image?"},
{
"type": "image",
"source": {
"type": "url",
"url": "https://example.com/image.jpg"
}
}
]
}]
)
# From base64
with open("image.png", "rb") as f:
image_data = base64.b64encode(f.read()).decode()
message = client.messages.create(
model="claude-sonnet-4-5",
max_tokens=1024,
messages=[{
"role": "user",
"content": [
{"type": "text", "text": "Describe this image"},
{
"type": "image",
"source": {
"type": "base64",
"media_type": "image/png",
"data": image_data
}
}
]
}]
)
message = client.messages.create(
model="claude-sonnet-4-5",
max_tokens=1024,
tools=[{
"name": "get_weather",
"description": "Get the weather for a location",
"input_schema": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "City name"}
},
"required": ["location"]
}
}],
messages=[{"role": "user", "content": "What's the weather in Tokyo?"}]
)
# Check for tool use
for block in message.content:
if block.type == "tool_use":
print(f"Tool: {block.name}")
print(f"Input: {block.input}")
Extended Thinking (Claude Opus 4.5)
Für Modelle, die Extended Thinking unterstützen:
message = client.messages.create(
model="claude-opus-4-5",
max_tokens=16000,
thinking={
"type": "enabled",
"budget_tokens": 10000
},
messages=[{"role": "user", "content": "Solve this complex math problem..."}]
)
# Access thinking blocks
for block in message.content:
if block.type == "thinking":
print(f"Thinking: {block.thinking}")
elif block.type == "text":
print(f"Response: {block.text}")
Verfügbare Claude-Modelle
| Modell | Bestens geeignet für |
|---|
claude-opus-4-5 | Komplexes logisches Schließen, Extended Thinking |
claude-sonnet-4-5 | Allgemeine Zwecke, Programmierung |
claude-haiku-4-5 | Schnelle Antworten |
Fehlerbehandlung
from anthropic import APIError, APIStatusError, APIConnectionError
try:
message = client.messages.create(
model="claude-sonnet-4-5",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello"}]
)
except APIStatusError as e:
if e.status_code == 401:
print("Invalid API key")
elif e.status_code == 429:
print("Rate limit exceeded")
else:
print(f"API error: {e.status_code}")
except APIConnectionError:
print("Connection error")
except APIError as e:
print(f"Unexpected error: {e}")
Vergleich: OpenAI SDK vs. Anthropic SDK
Beide funktionieren mit LemonData für Claude-Modelle:
| Funktion | OpenAI SDK | Anthropic SDK |
|---|
| Basis-URL | https://api.lemondata.cc/v1 | https://api.lemondata.cc |
| Endpunkt | /chat/completions | /v1/messages |
| System-Prompt | Im messages-Array | Separater system-Parameter |
| Extended Thinking | Nicht unterstützt | Unterstützt |
