add async support for anthropic (#2114)

should not be merged in before
https://github.com/anthropics/anthropic-sdk-python/pull/11 gets released

docs/modules/models/llms/examples/async_llm.ipynb

@@ -9,7 +9,7 @@
     "\n",
     "LangChain provides async support for LLMs by leveraging the [asyncio](https://docs.python.org/3/library/asyncio.html) library.\n",
     "\n",
-    "Async support is particularly useful for calling multiple LLMs concurrently, as these calls are network-bound. Currently, only `OpenAI` and `PromptLayerOpenAI` are supported, but async support for other LLMs is on the roadmap.\n",
+    "Async support is particularly useful for calling multiple LLMs concurrently, as these calls are network-bound. Currently, `OpenAI`, `PromptLayerOpenAI`, `ChatOpenAI` and `Anthropic` are supported, but async support for other LLMs is on the roadmap.\n",
     "\n",
     "You can use the `agenerate` method to call an OpenAI LLM asynchronously."
    ]
@@ -151,7 +151,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.10.9"
   }
  },
  "nbformat": 4,

langchain/llms/anthropic.py

@@ -170,6 +170,38 @@ class Anthropic(LLM, BaseModel):
         )
         return response["completion"]
 
+    async def _acall(self, prompt: str, stop: Optional[List[str]] = None) -> str:
+        """Call out to Anthropic's completion endpoint asynchronously."""
+        stop = self._get_anthropic_stop(stop)
+        if self.streaming:
+            stream_resp = await self.client.acompletion_stream(
+                model=self.model,
+                prompt=self._wrap_prompt(prompt),
+                stop_sequences=stop,
+                stream=True,
+                **self._default_params,
+            )
+            current_completion = ""
+            async for data in stream_resp:
+                delta = data["completion"][len(current_completion) :]
+                current_completion = data["completion"]
+                if self.callback_manager.is_async:
+                    await self.callback_manager.on_llm_new_token(
+                        delta, verbose=self.verbose, **data
+                    )
+                else:
+                    self.callback_manager.on_llm_new_token(
+                        delta, verbose=self.verbose, **data
+                    )
+            return current_completion
+        response = await self.client.acompletion(
+            model=self.model,
+            prompt=self._wrap_prompt(prompt),
+            stop_sequences=stop,
+            **self._default_params,
+        )
+        return response["completion"]
+
     def stream(self, prompt: str, stop: Optional[List[str]] = None) -> Generator:
         r"""Call Anthropic completion_stream and return the resulting generator.
 

poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.4.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry and should not be changed by hand.
 
 [[package]]
 name = "absl-py"
@@ -287,17 +287,18 @@ types = ["mypy", "types-requests"]
 
 [[package]]
 name = "anthropic"
-version = "0.2.3"
+version = "0.2.4"
 description = "Library for accessing the anthropic API"
 category = "main"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "anthropic-0.2.3-py3-none-any.whl", hash = "sha256:51cc9e3c5c0fc39b62af64b0607fd0da1622c7815fed89d0a52d80ebe0e60f3a"},
+    {file = "anthropic-0.2.4-py3-none-any.whl", hash = "sha256:2f955435bfdecc94e5432d72492c38fd22a55647026de1518461b707dd3ae808"},
-    {file = "anthropic-0.2.3.tar.gz", hash = "sha256:3d4f8d21c54d23d476d5ef72510b50126108f9b0bdc45b9d5d2e2b34204d56ad"},
+    {file = "anthropic-0.2.4.tar.gz", hash = "sha256:2041546470a9a2e897d6317627fdd7ea585245a3ff1ed1b054a47f63b4daa893"},
 ]
 
 [package.dependencies]
+aiohttp = "*"
 httpx = "*"
 requests = "*"
 tokenizers = "*"
@@ -6868,7 +6869,7 @@ files = [
 ]
 
 [package.dependencies]
-greenlet = {version = "!=0.4.17", markers = "python_version >= \"3\" and platform_machine == \"aarch64\" or python_version >= \"3\" and platform_machine == \"ppc64le\" or python_version >= \"3\" and platform_machine == \"x86_64\" or python_version >= \"3\" and platform_machine == \"amd64\" or python_version >= \"3\" and platform_machine == \"AMD64\" or python_version >= \"3\" and platform_machine == \"win32\" or python_version >= \"3\" and platform_machine == \"WIN32\""}
+greenlet = {version = "!=0.4.17", markers = "python_version >= \"3\" and (platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\")"}
 
 [package.extras]
 aiomysql = ["aiomysql", "greenlet (!=0.4.17)"]
@@ -8528,10 +8529,10 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker
 testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
 
 [extras]
-all = ["aleph-alpha-client", "anthropic", "beautifulsoup4", "cohere", "deeplake", "elasticsearch", "faiss-cpu", "google-api-python-client", "google-search-results", "huggingface_hub", "jina", "jinja2", "manifest-ml", "networkx", "nlpcloud", "nltk", "nomic", "openai", "opensearch-py", "pgvector", "pinecone-client", "psycopg2-binary", "pypdf", "qdrant-client", "redis", "sentence-transformers", "spacy", "tensorflow-text", "tiktoken", "torch", "transformers", "weaviate-client", "wikipedia", "wolframalpha"]
+all = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "jina", "manifest-ml", "elasticsearch", "opensearch-py", "google-search-results", "faiss-cpu", "sentence-transformers", "transformers", "spacy", "nltk", "wikipedia", "beautifulsoup4", "tiktoken", "torch", "jinja2", "pinecone-client", "weaviate-client", "redis", "google-api-python-client", "wolframalpha", "qdrant-client", "tensorflow-text", "pypdf", "networkx", "nomic", "aleph-alpha-client", "deeplake", "pgvector", "psycopg2-binary"]
-llms = ["anthropic", "cohere", "huggingface_hub", "manifest-ml", "nlpcloud", "openai", "torch", "transformers"]
+llms = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "manifest-ml", "torch", "transformers"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "fec488d52fc1a46ae34a643e5951e00251232d6d38c50c844556041df6067572"
+content-hash = "b8dd776b9c9bfda2413bdc0c58eb9cc8975a0ec770a830af5568cc80e4a1925d"

pyproject.toml

@@ -34,7 +34,7 @@ pinecone-client = {version = "^2", optional = true}
 weaviate-client = {version = "^3", optional = true}
 google-api-python-client = {version = "2.70.0", optional = true}
 wolframalpha = {version = "5.0.0", optional = true}
-anthropic = {version = "^0.2.2", optional = true}
+anthropic = {version = "^0.2.4", optional = true}
 qdrant-client = {version = "^1.0.4", optional = true, python = ">=3.8.1,<3.12"}
 dataclasses-json = "^0.5.7"
 tensorflow-text = {version = "^2.11.0", optional = true, python = "^3.10, <3.12"}

tests/integration_tests/llms/test_anthropic.py

@@ -1,9 +1,11 @@
 """Test Anthropic API wrapper."""
-
 from typing import Generator
 
+import pytest
+
 from langchain.callbacks.base import CallbackManager
 from langchain.llms.anthropic import Anthropic
+from langchain.schema import LLMResult
 from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
 
 
@@ -37,3 +39,27 @@ def test_anthropic_streaming_callback() -> None:
     )
     llm("Write me a sentence with 100 words.")
     assert callback_handler.llm_streams > 1
+
+
+@pytest.mark.asyncio
+async def test_anthropic_async_generate() -> None:
+    """Test async generate."""
+    llm = Anthropic()
+    output = await llm.agenerate(["How many toes do dogs have?"])
+    assert isinstance(output, LLMResult)
+
+
+@pytest.mark.asyncio
+async def test_anthropic_async_streaming_callback() -> None:
+    """Test that streaming correctly invokes on_llm_new_token callback."""
+    callback_handler = FakeCallbackHandler()
+    callback_manager = CallbackManager([callback_handler])
+    llm = Anthropic(
+        model="claude-v1",
+        streaming=True,
+        callback_manager=callback_manager,
+        verbose=True,
+    )
+    result = await llm.agenerate(["How many toes do dogs have?"])
+    assert callback_handler.llm_streams > 1
+    assert isinstance(result, LLMResult)