Async models

* Tip about pytest --record-mode once

Plus mechanism for setting API key during tests with PYTEST_ANTHROPIC_API_KEY

* Async support for Claude models

Closes #25
Refs https://github.com/simonw/llm/issues/507
Refs https://github.com/simonw/llm/pull/613

* Depend on llm>=0.18a0, refs #25

README.md

@@ -54,3 +54,15 @@ To run the tests:
 ```bash
 pytest
 ```
+
+This project uses [pytest-recording](https://github.com/kiwicom/pytest-recording) to record Anthropic API responses for the tests.
+
+If you add a new test that calls the API you can capture the API response like this:
+```bash
+PYTEST_ANTHROPIC_API_KEY="$(llm keys get claude)" pytest --record-mode once
+```
+You will need to have stored a valid Anthropic API key using this command first:
+```bash
+llm keys set claude
+# Paste key here
+```

llm_claude_3.py

@@ -1,4 +1,4 @@
-from anthropic import Anthropic
+from anthropic import Anthropic, AsyncAnthropic
 import llm
 from pydantic import Field, field_validator, model_validator
 from typing import Optional, List
@@ -7,19 +7,42 @@ from typing import Optional, List
 @llm.hookimpl
 def register_models(register):
     # https://docs.anthropic.com/claude/docs/models-overview
-    register(ClaudeMessages("claude-3-opus-20240229"))
+    register(
-    register(ClaudeMessages("claude-3-opus-latest"), aliases=("claude-3-opus",))
+        ClaudeMessages("claude-3-opus-20240229"),
-    register(ClaudeMessages("claude-3-sonnet-20240229"), aliases=("claude-3-sonnet",))
+        AsyncClaudeMessages("claude-3-opus-20240229"),
-    register(ClaudeMessages("claude-3-haiku-20240307"), aliases=("claude-3-haiku",))
+    ),
+    register(
+        ClaudeMessages("claude-3-opus-latest"),
+        AsyncClaudeMessages("claude-3-opus-latest"),
+        aliases=("claude-3-opus",),
+    )
+    register(
+        ClaudeMessages("claude-3-sonnet-20240229"),
+        AsyncClaudeMessages("claude-3-sonnet-20240229"),
+        aliases=("claude-3-sonnet",),
+    )
+    register(
+        ClaudeMessages("claude-3-haiku-20240307"),
+        AsyncClaudeMessages("claude-3-haiku-20240307"),
+        aliases=("claude-3-haiku",),
+    )
     # 3.5 models
-    register(ClaudeMessagesLong("claude-3-5-sonnet-20240620"))
+    register(
-    register(ClaudeMessagesLong("claude-3-5-sonnet-20241022", supports_pdf=True)),
+        ClaudeMessagesLong("claude-3-5-sonnet-20240620"),
+        AsyncClaudeMessagesLong("claude-3-5-sonnet-20240620"),
+    )
+    register(
+        ClaudeMessagesLong("claude-3-5-sonnet-20241022", supports_pdf=True),
+        AsyncClaudeMessagesLong("claude-3-5-sonnet-20241022", supports_pdf=True),
+    )
     register(
         ClaudeMessagesLong("claude-3-5-sonnet-latest", supports_pdf=True),
+        AsyncClaudeMessagesLong("claude-3-5-sonnet-latest", supports_pdf=True),
         aliases=("claude-3.5-sonnet", "claude-3.5-sonnet-latest"),
     )
     register(
         ClaudeMessagesLong("claude-3-5-haiku-latest", supports_images=False),
+        AsyncClaudeMessagesLong("claude-3-5-haiku-latest", supports_images=False),
         aliases=("claude-3.5-haiku",),
     )
 
@@ -86,7 +109,13 @@ class ClaudeOptions(llm.Options):
         return self
 
 
-class ClaudeMessages(llm.Model):
+long_field = Field(
+    description="The maximum number of tokens to generate before stopping",
+    default=4_096 * 2,
+)
+
+
+class _Shared:
     needs_key = "claude"
     key_env_var = "ANTHROPIC_API_KEY"
     can_stream = True
@@ -178,9 +207,7 @@ class ClaudeMessages(llm.Model):
             messages.append({"role": "user", "content": prompt.prompt})
         return messages
 
-    def execute(self, prompt, stream, response, conversation):
+    def build_kwargs(self, prompt, conversation):
-        client = Anthropic(api_key=self.get_key())
-
         kwargs = {
             "model": self.claude_model_id,
             "messages": self.build_messages(prompt, conversation),
@@ -202,7 +229,17 @@ class ClaudeMessages(llm.Model):
 
         if self.extra_headers:
             kwargs["extra_headers"] = self.extra_headers
+        return kwargs
 
+    def __str__(self):
+        return "Anthropic Messages: {}".format(self.model_id)
+
+
+class ClaudeMessages(_Shared, llm.Model):
+
+    def execute(self, prompt, stream, response, conversation):
+        client = Anthropic(api_key=self.get_key())
+        kwargs = self.build_kwargs(prompt, conversation)
         if stream:
             with client.messages.stream(**kwargs) as stream:
                 for text in stream.text_stream:
@@ -214,13 +251,27 @@ class ClaudeMessages(llm.Model):
             yield completion.content[0].text
             response.response_json = completion.model_dump()
 
-    def __str__(self):
-        return "Anthropic Messages: {}".format(self.model_id)
-
 
 class ClaudeMessagesLong(ClaudeMessages):
     class Options(ClaudeOptions):
-        max_tokens: Optional[int] = Field(
+        max_tokens: Optional[int] = long_field
-            description="The maximum number of tokens to generate before stopping",
+
-            default=4_096 * 2,
+
-        )
+class AsyncClaudeMessages(_Shared, llm.AsyncModel):
+    async def execute(self, prompt, stream, response, conversation):
+        client = AsyncAnthropic(api_key=self.get_key())
+        kwargs = self.build_kwargs(prompt, conversation)
+        if stream:
+            async with client.messages.stream(**kwargs) as stream_obj:
+                async for text in stream_obj.text_stream:
+                    yield text
+            response.response_json = (await stream_obj.get_final_message()).model_dump()
+        else:
+            completion = await client.messages.create(**kwargs)
+            yield completion.content[0].text
+            response.response_json = completion.model_dump()
+
+
+class AsyncClaudeMessagesLong(AsyncClaudeMessages):
+    class Options(ClaudeOptions):
+        max_tokens: Optional[int] = long_field

pyproject.toml

@@ -9,7 +9,7 @@ classifiers = [
     "License :: OSI Approved :: Apache Software License"
 ]
 dependencies = [
-    "llm>=0.17",
+    "llm>=0.18a0",
     "anthropic>=0.39.0",
 ]
 
@@ -23,4 +23,4 @@ CI = "https://github.com/simonw/llm-claude-3/actions"
 claude_3 = "llm_claude_3"
 
 [project.optional-dependencies]
-test = ["pytest", "pytest-recording"]
+test = ["pytest", "pytest-recording", "pytest-asyncio"]

tests/cassettes/test_claude_3/test_async_prompt.yaml

@@ -0,0 +1,656 @@
+interactions:
+- request:
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+      for a pet pelican, be brief"}], "model": "claude-3-opus-latest", "temperature":
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+      - 3.10.4
+      x-stainless-stream-helper:
+      - messages
+    method: POST
+    uri: https://api.anthropic.com/v1/messages
+  response:
+    body:
+      string: 'event: message_start
+
+        data: {"type":"message_start","message":{"id":"msg_01CFHNpT4EP6DBS5Mjurxx8j","type":"message","role":"assistant","model":"claude-3-opus-20240229","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":17,"output_tokens":1}}   }
+
+
+        event: content_block_start
+
+        data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}
+        }
+
+
+        event: ping
+
+        data: {"type": "ping"}
+
+
+        event: content_block_delta
+
+        data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"1.
+        P"}             }
+
+
+        event: content_block_delta
+
+        data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"elly\n2."}     }
+
+
+        event: content_block_delta
+
+        data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"
+        G"}       }
+
+
+        event: content_block_delta
+
+        data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"ully"}
+        }
+
+
+        event: content_block_stop
+
+        data: {"type":"content_block_stop","index":0            }
+
+
+        event: message_delta
+
+        data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":15}       }
+
+
+        event: message_stop
+
+        data: {"type":"message_stop"             }
+
+
+        '
+    headers:
+      CF-Cache-Status:
+      - DYNAMIC
+      CF-RAY:
+      - 8e235667ccc0cea0-SJC
+      Cache-Control:
+      - no-cache
+      Connection:
+      - keep-alive
+      Content-Type:
+      - text/event-stream; charset=utf-8
+      Date:
+      - Thu, 14 Nov 2024 01:48:08 GMT
+      Server:
+      - cloudflare
+      Transfer-Encoding:
+      - chunked
+      X-Robots-Tag:
+      - none
+      anthropic-ratelimit-requests-limit:
+      - '4000'
+      anthropic-ratelimit-requests-remaining:
+      - '3999'
+      anthropic-ratelimit-requests-reset:
+      - '2024-11-14T01:48:08Z'
+      anthropic-ratelimit-tokens-limit:
+      - '400000'
+      anthropic-ratelimit-tokens-remaining:
+      - '396000'
+      anthropic-ratelimit-tokens-reset:
+      - '2024-11-14T01:48:08Z'
+      request-id:
+      - req_01BdZqjn7kWSfAc8dZHNwvvk
+      via:
+      - 1.1 google
+    status:
+      code: 200
+      message: OK
+version: 1

tests/conftest.py

@@ -0,0 +1,6 @@
+import pytest
+
+
+@pytest.fixture(scope="module")
+def vcr_config():
+    return {"filter_headers": ["X-API-KEY"]}

tests/test_claude_3.py

@@ -1,4 +1,5 @@
 import llm
+import os
 import pytest
 
 TINY_PNG = (
@@ -11,11 +12,13 @@ TINY_PNG = (
     b"\x82"
 )
 
+ANTHROPIC_API_KEY = os.environ.get("PYTEST_ANTHROPIC_API_KEY", None) or "sk-..."
+
 
 @pytest.mark.vcr
 def test_prompt():
     model = llm.get_model("claude-3-opus")
-    model.key = model.key or "sk-..."  # don't override existing key
+    model.key = model.key or ANTHROPIC_API_KEY
     response = model.prompt("Two names for a pet pelican, be brief")
     assert str(response) == "1. Pelly\n2. Beaky"
     response_dict = dict(response.response_json)
@@ -31,6 +34,26 @@ def test_prompt():
     }
 
 
+@pytest.mark.vcr
+@pytest.mark.asyncio
+async def test_async_prompt():
+    model = llm.get_async_model("claude-3-opus")
+    model.key = model.key or ANTHROPIC_API_KEY  # don't override existing key
+    response = await model.prompt("Two names for a pet pelican, be brief")
+    assert await response.text() == "1. Pelly\n2. Beaky"
+    response_dict = dict(response.response_json)
+    response_dict.pop("id")  # differs between requests
+    assert response_dict == {
+        "content": [{"text": "1. Pelly\n2. Beaky", "type": "text"}],
+        "model": "claude-3-opus-20240229",
+        "role": "assistant",
+        "stop_reason": "end_turn",
+        "stop_sequence": None,
+        "type": "message",
+        "usage": {"input_tokens": 17, "output_tokens": 15},
+    }
+
+
 EXPECTED_IMAGE_TEXT = (
     "This image shows two simple rectangular blocks of solid colors stacked "
     "vertically. The top rectangle is a bright, vibrant red color, while the "
@@ -43,7 +66,7 @@ EXPECTED_IMAGE_TEXT = (
 @pytest.mark.vcr
 def test_image_prompt():
     model = llm.get_model("claude-3.5-sonnet")
-    model.key = model.key or "sk-..."
+    model.key = model.key or ANTHROPIC_API_KEY
     response = model.prompt(
         "Describe image in three words",
         attachments=[llm.Attachment(content=TINY_PNG)],