From 51c2fcd4f366130b7a99abc996f650ffb82521f1 Mon Sep 17 00:00:00 2001 From: Thomas Capelle Date: Tue, 27 Aug 2024 17:52:32 +0200 Subject: [PATCH] feat: Cerebras Support (#2242) --- docs/docs/guides/integrations/cerebras.md | 107 ++++++++++++++++++ .../integrations/imgs/cerebras_calls.png | Bin 0 -> 372320 bytes .../integrations/imgs/cerebras_model.png | Bin 0 -> 332777 bytes docs/sidebars.ts | 1 + requirements.test.txt | 2 +- weave/autopatch.py | 4 + weave/integrations/cerebras/__init__.py | 0 .../cerebras_test/test_cerebras_async.yaml | 86 ++++++++++++++ .../cerebras_test/test_cerebras_sync.yaml | 86 ++++++++++++++ weave/integrations/cerebras/cerebras_sdk.py | 53 +++++++++ weave/integrations/cerebras/cerebras_test.py | 86 ++++++++++++++ weave/trace/op.py | 6 + 12 files changed, 430 insertions(+), 1 deletion(-) create mode 100644 docs/docs/guides/integrations/cerebras.md create mode 100644 docs/docs/guides/integrations/imgs/cerebras_calls.png create mode 100644 docs/docs/guides/integrations/imgs/cerebras_model.png create mode 100644 weave/integrations/cerebras/__init__.py create mode 100644 weave/integrations/cerebras/cassettes/cerebras_test/test_cerebras_async.yaml create mode 100644 weave/integrations/cerebras/cassettes/cerebras_test/test_cerebras_sync.yaml create mode 100644 weave/integrations/cerebras/cerebras_sdk.py create mode 100644 weave/integrations/cerebras/cerebras_test.py diff --git a/docs/docs/guides/integrations/cerebras.md b/docs/docs/guides/integrations/cerebras.md new file mode 100644 index 000000000000..110356a112d3 --- /dev/null +++ b/docs/docs/guides/integrations/cerebras.md @@ -0,0 +1,107 @@ +# Cerebras + +Weave automatically tracks and logs LLM calls made via the [Cerebras Cloud SDK](https://inference-docs.cerebras.ai/introduction). + +## Traces + +Tracking LLM calls is crucial for debugging and performance monitoring. Weave helps you do this by automatically capturing traces for the Cerebras Cloud SDK. + +Here's an example of how to use Weave with Cerebras: + +```python +import os +import weave +from cerebras.cloud.sdk import Cerebras + +# Initialise the weave project +weave.init("cerebras_speedster") + +# Use the Cerebras SDK as usual +api_key = os.environ["CEREBRAS_API_KEY"] +model = "llama3.1-8b" # Cerebras model + +client = Cerebras(api_key=api_key) + +response = client.chat.completions.create( + model=model, + messages=[{"role": "user", "content": "What's the fastest land animal?"}], +) + +print(response.choices[0].message.content) +``` + +Weave will now track and log all LLM calls made through the Cerebras SDK. You can view the traces in the Weave web interface, including details like token usage and response time. + +[![cerebras_calls.png](imgs/cerebras_calls.png)](https://wandb.ai/capecape/cerebras_speedster/weave/traces) + +## Wrapping with your own ops + +Weave ops offer a powerful way to enhance reproducibility and traceability in your experiments. By automatically versioning your code and capturing inputs and outputs. Here's an example of how you can leverage Weave ops with the Cerebras SDK: + +```python +import os +import weave +from cerebras.cloud.sdk import Cerebras + +# Initialise the weave project +weave.init("cerebras_speedster") + +client = Cerebras(api_key=os.environ["CEREBRAS_API_KEY"]) + +# Weave will track the inputs, outputs and code of this function +@weave.op +def animal_speedster(animal: str, model: str) -> str: + "Find out how fast an animal can run" + + response = client.chat.completions.create( + model=model, + messages=[{"role": "user", "content": f"How fast can a {animal} run?"}], + ) + return response.choices[0].message.content + +animal_speedster("cheetah", "llama3.1-8b") +animal_speedster("ostrich", "llama3.1-8b") +animal_speedster("human", "llama3.1-8b") +``` + +## Create a `Model` for easier experimentation + +The [Model](/guides/core-types/models) class in Weave helps you organize and compare different iterations of your app. This is particularly useful when experimenting with Cerebras models. Here's an example: + + +```python +import os +import weave +from cerebras.cloud.sdk import Cerebras + +# Initialise the weave project +weave.init("cerebras_speedster") + +client = Cerebras(api_key=os.environ["CEREBRAS_API_KEY"]) + +class AnimalSpeedModel(weave.Model): + model: str + temperature: float + + @weave.op + def predict(self, animal: str) -> str: + "Predict the top speed of an animal" + + response = client.chat.completions.create( + model=self.model, + messages=[{"role": "user", "content": f"What's the top speed of a {animal}?"}], + temperature=self.temperature + ) + return response.choices[0].message.content + +speed_model = AnimalSpeedModel( + model="llama3.1-8b", + temperature=0.7 +) +result = speed_model.predict(animal="cheetah") +print(result) +``` + +With this setup, you can easily experiment with different models and parameters, all while keeping track of your Cerebras-powered inferences! + 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"guides/integrations/mistral", "guides/integrations/together_ai", diff --git a/requirements.test.txt b/requirements.test.txt index 878a81e3d349..29edfdd74a7c 100644 --- a/requirements.test.txt +++ b/requirements.test.txt @@ -43,6 +43,6 @@ chromadb>=0.5.0 # LangChain pysqlite3-binary==0.5.3 # LangChain cohere>=5.5.8 # Cohere groq>=0.9.0 # Groq - +cerebras-cloud-sdk # cerebras-cloud-sdk # Used for Integration Tests semver diff --git a/weave/autopatch.py b/weave/autopatch.py index 2bd08db073bc..f9445881321c 100644 --- a/weave/autopatch.py +++ b/weave/autopatch.py @@ -7,6 +7,7 @@ def autopatch() -> None: from .integrations.anthropic.anthropic_sdk import anthropic_patcher + from .integrations.cerebras.cerebras_sdk import cerebras_patcher from .integrations.cohere.cohere_sdk import cohere_patcher from .integrations.dspy.dspy_sdk import dspy_patcher from .integrations.groq.groq_sdk import groq_patcher @@ -24,11 +25,13 @@ def autopatch() -> None: anthropic_patcher.attempt_patch() groq_patcher.attempt_patch() dspy_patcher.attempt_patch() + cerebras_patcher.attempt_patch() cohere_patcher.attempt_patch() def reset_autopatch() -> None: from .integrations.anthropic.anthropic_sdk import anthropic_patcher + from .integrations.cerebras.cerebras_sdk import cerebras_patcher from .integrations.cohere.cohere_sdk import cohere_patcher from .integrations.dspy.dspy_sdk import dspy_patcher from .integrations.groq.groq_sdk import groq_patcher @@ -46,4 +49,5 @@ def reset_autopatch() -> None: anthropic_patcher.undo_patch() groq_patcher.undo_patch() dspy_patcher.undo_patch() + cerebras_patcher.undo_patch() cohere_patcher.undo_patch() diff --git a/weave/integrations/cerebras/__init__.py b/weave/integrations/cerebras/__init__.py new file mode 100644 index 000000000000..e69de29bb2d1 diff --git a/weave/integrations/cerebras/cassettes/cerebras_test/test_cerebras_async.yaml b/weave/integrations/cerebras/cassettes/cerebras_test/test_cerebras_async.yaml new file mode 100644 index 000000000000..9aa8837630fc --- /dev/null +++ b/weave/integrations/cerebras/cassettes/cerebras_test/test_cerebras_async.yaml @@ -0,0 +1,86 @@ +interactions: +- request: + body: '{"messages": [{"role": "user", "content": "What is the capital of France?"}], + "model": "llama3.1-8b"}' + headers: + accept: + - application/json + accept-encoding: + - gzip, deflate, br + connection: + - keep-alive + content-length: + - '101' + content-type: + - application/json + host: + - api.cerebras.ai + user-agent: + - AsyncCerebras/Python 0.6.0 + x-stainless-arch: + - arm64 + x-stainless-async: + - async:asyncio + x-stainless-lang: + - python + x-stainless-os: + - MacOS + x-stainless-package-version: + - 0.6.0 + x-stainless-runtime: + - CPython + x-stainless-runtime-version: + - 3.11.9 + method: POST + uri: https://api.cerebras.ai/v1/chat/completions + response: + body: + string: '{"id":"chatcmpl-90621a67-4431-4371-8e09-93e033e8ed13","choices":[{"finish_reason":"stop","index":0,"message":{"content":"The + capital of France is Paris.","role":"assistant"}}],"created":1724146770,"model":"llama3.1-8b","system_fingerprint":"fp_70185065a4","object":"chat.completion","usage":{"prompt_tokens":17,"completion_tokens":8,"total_tokens":25},"time_info":{"queue_time":6.701e-05,"prompt_time":0.0015992357142857144,"completion_time":0.004545298285714286,"total_time":0.022367477416992188,"created":1724146770}}' + headers: + Alt-Svc: + - h3=":443"; ma=86400 + Connection: + - keep-alive + Content-Type: + - application/json + Date: + - Tue, 20 Aug 2024 09:39:30 GMT + Transfer-Encoding: + - chunked + Via: + - 1.1 e1c8225b86f394718e093d7bbdef7fa2.cloudfront.net (CloudFront) + X-Amz-Cf-Id: + - ckJufp8z4gvcTynRlh0KRHsjG0q9LL9-uLqUgADe0mwUZ5HWGCuUVQ== + X-Amz-Cf-Pop: + - CDG52-P5 + X-Amzn-Trace-Id: + - root=1-66c46452-38959c0a6d258a734a804ae5;sampled=1;lineage=822f479c:0 + X-Cache: + - Miss from cloudfront + x-amzn-Remapped-content-length: + - '519' + x-amzn-Remapped-date: + - Tue, 20 Aug 2024 09:39:03 GMT + x-amzn-Remapped-server: + - uvicorn + x-amzn-RequestId: + - cd8cad17-a3f5-40bc-b428-b769bf420996 + x-ratelimit-limit-requests-day: + - '28800' + x-ratelimit-limit-tokens-minute: + - '60000' + x-ratelimit-remaining-requests-day: + - '28800' + x-ratelimit-remaining-tokens-minute: + - '59950' + x-ratelimit-reset-requests-day: + - '51629.819103479385' + x-ratelimit-reset-tokens-minute: + - '29.819103479385376' + x-request-id: + - ckJufp8z4gvcTynRlh0KRHsjG0q9LL9-uLqUgADe0mwUZ5HWGCuUVQ== + status: + code: 200 + message: OK +version: 1 diff --git a/weave/integrations/cerebras/cassettes/cerebras_test/test_cerebras_sync.yaml b/weave/integrations/cerebras/cassettes/cerebras_test/test_cerebras_sync.yaml new file mode 100644 index 000000000000..37b8f577399f --- /dev/null +++ b/weave/integrations/cerebras/cassettes/cerebras_test/test_cerebras_sync.yaml @@ -0,0 +1,86 @@ +interactions: +- request: + body: '{"messages": [{"role": "user", "content": "What is the capital of France?"}], + "model": "llama3.1-8b"}' + headers: + accept: + - application/json + accept-encoding: + - gzip, deflate, br + connection: + - keep-alive + content-length: + - '101' + content-type: + - application/json + host: + - api.cerebras.ai + user-agent: + - Cerebras/Python 0.6.0 + x-stainless-arch: + - arm64 + x-stainless-async: + - 'false' + x-stainless-lang: + - python + x-stainless-os: + - MacOS + x-stainless-package-version: + - 0.6.0 + x-stainless-runtime: + - CPython + x-stainless-runtime-version: + - 3.11.9 + method: POST + uri: https://api.cerebras.ai/v1/chat/completions + response: + body: + string: '{"id":"chatcmpl-48b9a448-c1cc-4a11-9686-76dd8e744e02","choices":[{"finish_reason":"stop","index":0,"message":{"content":"The + capital of France is Paris.","role":"assistant"}}],"created":1724146768,"model":"llama3.1-8b","system_fingerprint":"fp_70185065a4","object":"chat.completion","usage":{"prompt_tokens":17,"completion_tokens":8,"total_tokens":25},"time_info":{"queue_time":6.615e-05,"prompt_time":0.0015992892857142858,"completion_time":0.004536781714285715,"total_time":0.02078700065612793,"created":1724146768}}' + headers: + Alt-Svc: + - h3=":443"; ma=86400 + Connection: + - keep-alive + Content-Type: + - application/json + Date: + - Tue, 20 Aug 2024 09:39:28 GMT + Transfer-Encoding: + - chunked + Via: + - 1.1 e90132d2777b51acfb2fd86213866952.cloudfront.net (CloudFront) + X-Amz-Cf-Id: + - 5UD2_0bkNmZIqCzFZQJ51eWJpqqn_3TUueEW8n82e3VCib6M6Lf-Cg== + X-Amz-Cf-Pop: + - CDG52-P5 + X-Amzn-Trace-Id: + - root=1-66c46450-1702385454adf3b15962ddd9;sampled=1;lineage=822f479c:0 + X-Cache: + - Miss from cloudfront + x-amzn-Remapped-content-length: + - '518' + x-amzn-Remapped-date: + - Tue, 20 Aug 2024 09:39:03 GMT + x-amzn-Remapped-server: + - uvicorn + x-amzn-RequestId: + - 86a3b877-20d0-44cf-85ec-6a29da1bdc94 + x-ratelimit-limit-requests-day: + - '28800' + x-ratelimit-limit-tokens-minute: + - '60000' + x-ratelimit-remaining-requests-day: + - '28800' + x-ratelimit-remaining-tokens-minute: + - '59975' + x-ratelimit-reset-requests-day: + - '51631.72441959381' + x-ratelimit-reset-tokens-minute: + - '31.724419593811035' + x-request-id: + - 5UD2_0bkNmZIqCzFZQJ51eWJpqqn_3TUueEW8n82e3VCib6M6Lf-Cg== + status: + code: 200 + message: OK +version: 1 diff --git a/weave/integrations/cerebras/cerebras_sdk.py b/weave/integrations/cerebras/cerebras_sdk.py new file mode 100644 index 000000000000..6c1ae9d46b53 --- /dev/null +++ b/weave/integrations/cerebras/cerebras_sdk.py @@ -0,0 +1,53 @@ +import importlib +import typing +from functools import wraps + +import weave +from weave.trace.patcher import MultiPatcher, SymbolPatcher + + +def create_wrapper_sync( + name: str, +) -> typing.Callable[[typing.Callable], typing.Callable]: + def wrapper(fn: typing.Callable) -> typing.Callable: + op = weave.op()(fn) + op.name = name # type: ignore + return op + + return wrapper + + +def create_wrapper_async( + name: str, +) -> typing.Callable[[typing.Callable], typing.Callable]: + def wrapper(fn: typing.Callable) -> typing.Callable: + def _fn_wrapper(fn: typing.Callable) -> typing.Callable: + @wraps(fn) + async def _async_wrapper( + *args: typing.Any, **kwargs: typing.Any + ) -> typing.Any: + return await fn(*args, **kwargs) + + return _async_wrapper + + op = weave.op()(_fn_wrapper(fn)) + op.name = name # type: ignore + return op + + return wrapper + + +cerebras_patcher = MultiPatcher( + [ + SymbolPatcher( + lambda: importlib.import_module("cerebras.cloud.sdk.resources.chat"), + "CompletionsResource.create", + create_wrapper_sync(name="cerebras.chat.completions.create"), + ), + SymbolPatcher( + lambda: importlib.import_module("cerebras.cloud.sdk.resources.chat"), + "AsyncCompletionsResource.create", + create_wrapper_async(name="cerebras.chat.completions.create"), + ), + ] +) diff --git a/weave/integrations/cerebras/cerebras_test.py b/weave/integrations/cerebras/cerebras_test.py new file mode 100644 index 000000000000..d75c02ca0ba0 --- /dev/null +++ b/weave/integrations/cerebras/cerebras_test.py @@ -0,0 +1,86 @@ +import os +from typing import Any + +import pytest +from cerebras.cloud.sdk import AsyncCerebras, Cerebras + +import weave +from weave.trace_server import trace_server_interface as tsi + +model = "llama3.1-8b" # Cerebras model + + +def _get_call_output(call: tsi.CallSchema) -> Any: + call_output = call.output + if isinstance(call_output, str) and call_output.startswith("weave://"): + return weave.ref(call_output).get() + return call_output + + +@pytest.mark.skip_clickhouse_client +@pytest.mark.vcr( + filter_headers=["authorization"], allowed_hosts=["api.wandb.ai", "localhost"] +) +def test_cerebras_sync(client: weave.weave_client.WeaveClient) -> None: + api_key = os.environ.get("CEREBRAS_API_KEY", "DUMMY_API_KEY") + cerebras_client = Cerebras(api_key=api_key) + + response = cerebras_client.chat.completions.create( + model=model, + messages=[{"role": "user", "content": "What is the capital of France?"}], + ) + + exp = "The capital of France is Paris." + assert response.choices[0].message.content.strip() == exp + + res = client.server.calls_query(tsi.CallsQueryReq(project_id=client._project_id())) + assert len(res.calls) == 1 + call = res.calls[0] + assert call.exception is None and call.ended_at is not None + output = _get_call_output(call) + assert output.choices[0].message.content.strip() == exp + assert output.choices[0].finish_reason == "stop" + assert output.id == response.id + assert output.model == response.model + summary = call.summary + assert summary is not None + model_usage = summary["usage"][output.model] + assert model_usage["requests"] == 1 + assert output.usage.completion_tokens == model_usage["completion_tokens"] + assert output.usage.prompt_tokens == model_usage["prompt_tokens"] + assert output.usage.total_tokens == model_usage["total_tokens"] + + +@pytest.mark.skip_clickhouse_client +@pytest.mark.vcr( + filter_headers=["authorization"], allowed_hosts=["api.wandb.ai", "localhost"] +) +@pytest.mark.asyncio +async def test_cerebras_async(client: weave.weave_client.WeaveClient) -> None: + api_key = os.environ.get("CEREBRAS_API_KEY", "DUMMY_API_KEY") + cerebras_client = AsyncCerebras(api_key=api_key) + + response = await cerebras_client.chat.completions.create( + model=model, + messages=[{"role": "user", "content": "What is the capital of France?"}], + ) + + exp = "The capital of France is Paris." + assert response.choices[0].message.content.strip() == exp + + res = client.server.calls_query(tsi.CallsQueryReq(project_id=client._project_id())) + assert len(res.calls) == 1 + call = res.calls[0] + assert call.exception is None and call.ended_at is not None + output = _get_call_output(call) + assert output.choices[0].message.content.strip() == exp + assert output.choices[0].finish_reason == "stop" + assert output.id == response.id + assert output.model == response.model + summary = call.summary + assert summary is not None + model_usage = summary["usage"][output.model] + assert model_usage["requests"] == 1 + assert output.usage.completion_tokens == model_usage["completion_tokens"] + assert output.usage.prompt_tokens == model_usage["prompt_tokens"] + assert output.usage.total_tokens == model_usage["total_tokens"] diff --git a/weave/trace/op.py b/weave/trace/op.py index 8c81869f5a7a..37494d80ebe2 100644 --- a/weave/trace/op.py +++ b/weave/trace/op.py @@ -45,6 +45,11 @@ except ImportError: ANTHROPIC_NOT_GIVEN = None +try: + from cerebras.cloud.sdk._types import NOT_GIVEN as CEREBRAS_NOT_GIVEN +except ImportError: + CEREBRAS_NOT_GIVEN = None + def print_call_link(call: "Call") -> None: if settings.should_print_call_link(): @@ -61,6 +66,7 @@ def value_is_sentinel(param: Any) -> bool: or param.default is OPENAI_NOT_GIVEN or param.default is COHERE_NOT_GIVEN or param.default is ANTHROPIC_NOT_GIVEN + or param.default is CEREBRAS_NOT_GIVEN )

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