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chore: update claude-api skill (#956)
Add shared/model-migration.md and refresh model references, managed agents docs, and skill description across all language guides.
This commit is contained in:
Eric Harmeling
@@ -27,7 +27,7 @@ async_client = anthropic.AsyncAnthropic()
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```python
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[
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{"role": "user", "content": "What is the capital of France?"}
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@@ -46,7 +46,7 @@ for block in response.content:
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```python
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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system="You are a helpful coding assistant. Always provide examples in Python.",
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messages=[{"role": "user", "content": "How do I read a JSON file?"}]
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@@ -66,7 +66,7 @@ with open("image.png", "rb") as f:
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image_data = base64.standard_b64encode(f.read()).decode("utf-8")
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{
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"role": "user",
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@@ -89,7 +89,7 @@ response = client.messages.create(
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```python
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{
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"role": "user",
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@@ -119,7 +119,7 @@ Use top-level `cache_control` to automatically cache the last cacheable block in
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```python
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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cache_control={"type": "ephemeral"}, # auto-caches the last cacheable block
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system="You are an expert on this large document...",
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@@ -133,7 +133,7 @@ For fine-grained control, add `cache_control` to specific content blocks:
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```python
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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system=[{
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"type": "text",
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@@ -145,7 +145,7 @@ response = client.messages.create(
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# With explicit TTL (time-to-live)
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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system=[{
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"type": "text",
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@@ -170,13 +170,13 @@ If `cache_read_input_tokens` is zero across repeated identical-prefix requests,
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## Extended Thinking
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> **Opus 4.6 and Sonnet 4.6:** Use adaptive thinking. `budget_tokens` is deprecated on both Opus 4.6 and Sonnet 4.6.
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> **Opus 4.7, Opus 4.6, and Sonnet 4.6:** Use adaptive thinking. `budget_tokens` is removed on Opus 4.7 (400 if sent); deprecated on Opus 4.6 and Sonnet 4.6.
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> **Older models:** Use `thinking: {type: "enabled", budget_tokens: N}` (must be < `max_tokens`, min 1024).
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```python
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# Opus 4.6: adaptive thinking (recommended)
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# Opus 4.7 / 4.6: adaptive thinking (recommended)
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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thinking={"type": "adaptive"},
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output_config={"effort": "high"}, # low | medium | high | max
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@@ -258,7 +258,7 @@ class ConversationManager:
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# Usage
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conversation = ConversationManager(
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client=anthropic.Anthropic(),
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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system="You are a helpful assistant."
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)
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@@ -275,7 +275,7 @@ response2 = conversation.send("What's my name?") # Claude remembers "Alice"
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### Compaction (long conversations)
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> **Beta, Opus 4.6 and Sonnet 4.6.** When conversations approach the 200K context window, compaction automatically summarizes earlier context server-side. The API returns a `compaction` block; you must pass it back on subsequent requests — append `response.content`, not just the text.
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> **Beta, Opus 4.7, Opus 4.6, and Sonnet 4.6.** When conversations approach the 200K context window, compaction automatically summarizes earlier context server-side. The API returns a `compaction` block; you must pass it back on subsequent requests — append `response.content`, not just the text.
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```python
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import anthropic
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@@ -288,7 +288,7 @@ def chat(user_message: str) -> str:
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response = client.beta.messages.create(
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betas=["compact-2026-01-12"],
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=messages,
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context_management={
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@@ -331,7 +331,7 @@ The `stop_reason` field in the response indicates why the model stopped generati
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```python
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# Automatic caching (simplest — caches the last cacheable block)
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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cache_control={"type": "ephemeral"},
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system=large_document_text, # e.g., 50KB of context
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@@ -347,7 +347,7 @@ response = client.messages.create(
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```python
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# Default to Opus for most tasks
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response = client.messages.create(
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model="claude-opus-4-6", # $5.00/$25.00 per 1M tokens
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model="claude-opus-4-7", # $5.00/$25.00 per 1M tokens
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max_tokens=16000,
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messages=[{"role": "user", "content": "Explain quantum computing"}]
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)
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@@ -371,7 +371,7 @@ simple_response = client.messages.create(
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```python
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count_response = client.messages.count_tokens(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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messages=messages,
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system=system
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)
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@@ -26,7 +26,7 @@ message_batch = client.messages.batches.create(
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Request(
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custom_id="request-1",
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params=MessageCreateParamsNonStreaming(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{"role": "user", "content": "Summarize climate change impacts"}]
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)
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@@ -34,7 +34,7 @@ message_batch = client.messages.batches.create(
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Request(
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custom_id="request-2",
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params=MessageCreateParamsNonStreaming(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{"role": "user", "content": "Explain quantum computing basics"}]
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)
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@@ -117,7 +117,7 @@ message_batch = client.messages.batches.create(
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Request(
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custom_id=f"analysis-{i}",
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params=MessageCreateParamsNonStreaming(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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system=shared_system,
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messages=[{"role": "user", "content": question}]
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@@ -36,7 +36,7 @@ print(f"Size: {uploaded.size_bytes} bytes")
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```python
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response = client.beta.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{
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"role": "user",
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@@ -65,7 +65,7 @@ image_file = client.beta.files.upload(
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)
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response = client.beta.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{
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"role": "user",
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@@ -142,7 +142,7 @@ questions = [
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for question in questions:
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response = client.beta.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{
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"role": "user",
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@@ -4,7 +4,7 @@
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```python
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with client.messages.stream(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=64000,
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messages=[{"role": "user", "content": "Write a story"}]
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) as stream:
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@@ -16,7 +16,7 @@ with client.messages.stream(
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```python
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async with async_client.messages.stream(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=64000,
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messages=[{"role": "user", "content": "Write a story"}]
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) as stream:
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@@ -30,11 +30,11 @@ async with async_client.messages.stream(
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Claude may return text, thinking blocks, or tool use. Handle each appropriately:
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> **Opus 4.6:** Use `thinking: {type: "adaptive"}`. On older models, use `thinking: {type: "enabled", budget_tokens: N}` instead.
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> **Opus 4.7 / Opus 4.6:** Use `thinking: {type: "adaptive"}`. On older models, use `thinking: {type: "enabled", budget_tokens: N}` instead.
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```python
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with client.messages.stream(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=64000,
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thinking={"type": "adaptive"},
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messages=[{"role": "user", "content": "Analyze this problem"}]
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@@ -61,7 +61,7 @@ The Python tool runner currently returns complete messages. Use streaming for in
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```python
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with client.messages.stream(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=64000,
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tools=tools,
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messages=messages
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@@ -79,7 +79,7 @@ with client.messages.stream(
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```python
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with client.messages.stream(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=64000,
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messages=[{"role": "user", "content": "Hello"}]
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) as stream:
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@@ -126,7 +126,7 @@ def stream_with_progress(client, **kwargs):
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```python
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try:
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with client.messages.stream(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=64000,
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messages=[{"role": "user", "content": "Write a story"}]
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) as stream:
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@@ -27,7 +27,7 @@ def get_weather(location: str, unit: str = "celsius") -> str:
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# The tool runner handles the agentic loop automatically
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runner = client.beta.messages.tool_runner(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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tools=[get_weather],
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messages=[{"role": "user", "content": "What's the weather in Paris?"}],
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@@ -72,7 +72,7 @@ async with stdio_client(StdioServerParameters(command="mcp-server")) as (read, w
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tools_result = await mcp_client.list_tools()
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# tool_runner is sync — returns the runner, not a coroutine
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runner = client.beta.messages.tool_runner(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{"role": "user", "content": "Use the available tools"}],
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tools=[async_mcp_tool(t, mcp_client) for t in tools_result.tools],
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@@ -90,7 +90,7 @@ from anthropic.lib.tools.mcp import mcp_message
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prompt = await mcp_client.get_prompt(name="my-prompt")
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response = await client.beta.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[mcp_message(m) for m in prompt.messages],
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)
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@@ -103,7 +103,7 @@ from anthropic.lib.tools.mcp import mcp_resource_to_content
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resource = await mcp_client.read_resource(uri="file:///path/to/doc.txt")
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response = await client.beta.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{
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"role": "user",
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@@ -142,7 +142,7 @@ messages = [{"role": "user", "content": user_input}]
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# Agentic loop: keep going until Claude stops calling tools
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while True:
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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tools=tools,
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messages=messages
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@@ -189,7 +189,7 @@ final_text = next(b.text for b in response.content if b.type == "text")
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```python
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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tools=tools,
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messages=[{"role": "user", "content": "What's the weather in Paris?"}]
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@@ -204,7 +204,7 @@ for block in response.content:
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result = execute_tool(tool_name, tool_input)
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followup = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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tools=tools,
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messages=[
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@@ -241,7 +241,7 @@ for block in response.content:
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# Send all results back at once
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if tool_results:
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followup = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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tools=tools,
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messages=[
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@@ -271,7 +271,7 @@ tool_result = {
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```python
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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tools=tools,
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tool_choice={"type": "tool", "name": "get_weather"}, # Force specific tool
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@@ -291,7 +291,7 @@ import anthropic
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client = anthropic.Anthropic()
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{
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"role": "user",
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@@ -319,7 +319,7 @@ uploaded = client.beta.files.upload(file=open("sales_data.csv", "rb"))
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# 2. Pass to code execution via container_upload block
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# Code execution is GA; Files API is still beta (pass via extra_headers)
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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extra_headers={"anthropic-beta": "files-api-2025-04-14"},
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messages=[{
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@@ -364,7 +364,7 @@ for block in response.content:
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```python
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# First request: set up environment
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response1 = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{"role": "user", "content": "Install tabulate and create data.json with sample data"}],
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tools=[{"type": "code_execution_20260120", "name": "code_execution"}]
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@@ -376,7 +376,7 @@ container_id = response1.container.id
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# Second request: reuse the same container
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response2 = client.messages.create(
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container=container_id,
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{"role": "user", "content": "Read data.json and display as a formatted table"}],
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tools=[{"type": "code_execution_20260120", "name": "code_execution"}]
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@@ -416,7 +416,7 @@ import anthropic
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client = anthropic.Anthropic()
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response = client.messages.create(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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messages=[{"role": "user", "content": "Remember that my preferred language is Python."}],
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tools=[{"type": "memory_20250818", "name": "memory"}],
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@@ -442,7 +442,7 @@ memory = MyMemoryTool()
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# Use with tool runner
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runner = client.beta.messages.tool_runner(
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model="claude-opus-4-6",
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model="claude-opus-4-7",
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max_tokens=16000,
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tools=[memory],
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messages=[{"role": "user", "content": "Remember my preferences"}],
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@@ -477,7 +477,7 @@ class ContactInfo(BaseModel):
|
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client = anthropic.Anthropic()
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||||
|
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response = client.messages.parse(
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model="claude-opus-4-6",
|
||||
model="claude-opus-4-7",
|
||||
max_tokens=16000,
|
||||
messages=[{
|
||||
"role": "user",
|
||||
@@ -496,7 +496,7 @@ print(contact.interests) # ["API", "SDKs"]
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||||
|
||||
```python
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||||
response = client.messages.create(
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||||
model="claude-opus-4-6",
|
||||
model="claude-opus-4-7",
|
||||
max_tokens=16000,
|
||||
messages=[{
|
||||
"role": "user",
|
||||
@@ -530,7 +530,7 @@ data = json.loads(text)
|
||||
|
||||
```python
|
||||
response = client.messages.create(
|
||||
model="claude-opus-4-6",
|
||||
model="claude-opus-4-7",
|
||||
max_tokens=16000,
|
||||
messages=[{"role": "user", "content": "Book a flight to Tokyo for 2 passengers on March 15"}],
|
||||
tools=[{
|
||||
@@ -555,7 +555,7 @@ response = client.messages.create(
|
||||
|
||||
```python
|
||||
response = client.messages.create(
|
||||
model="claude-opus-4-6",
|
||||
model="claude-opus-4-7",
|
||||
max_tokens=16000,
|
||||
messages=[{"role": "user", "content": "Plan a trip to Paris next month"}],
|
||||
output_config={
|
||||
|
||||
Reference in New Issue
Block a user