From 11b106d6c617349fd5bbb0424cda39a6273aedbd Mon Sep 17 00:00:00 2001 From: Sitam Meur <103279526+sitamgithub-MSIT@users.noreply.github.com> Date: Sat, 19 Apr 2025 08:03:11 +0000 Subject: [PATCH 1/2] llm as judge initial code with atla and opik --- llm-as-judge/.env.example | 1 + llm-as-judge/README.md | 1 + llm-as-judge/main.py | 109 +++ llm-as-judge/pyproject.toml | 11 + llm-as-judge/uv.lock | 1270 +++++++++++++++++++++++++++++++++++ 5 files changed, 1392 insertions(+) create mode 100644 llm-as-judge/.env.example create mode 100644 llm-as-judge/README.md create mode 100644 llm-as-judge/main.py create mode 100644 llm-as-judge/pyproject.toml create mode 100644 llm-as-judge/uv.lock diff --git a/llm-as-judge/.env.example b/llm-as-judge/.env.example new file mode 100644 index 00000000..a4c20867 --- /dev/null +++ b/llm-as-judge/.env.example @@ -0,0 +1 @@ +ATLA_API_KEY=your_atla_api_key \ No newline at end of file diff --git a/llm-as-judge/README.md b/llm-as-judge/README.md new file mode 100644 index 00000000..d3b33b44 --- /dev/null +++ b/llm-as-judge/README.md @@ -0,0 +1 @@ +# LLM as a Judge \ No newline at end of file diff --git a/llm-as-judge/main.py b/llm-as-judge/main.py new file mode 100644 index 00000000..2a70ad3b --- /dev/null +++ b/llm-as-judge/main.py @@ -0,0 +1,109 @@ +import os +import json +from typing import Any +from dotenv import load_dotenv +from pydantic import BaseModel +from openai import OpenAI +from opik.evaluation.metrics import base_metric, score_result + + +# Take environment variables from .env +load_dotenv() + +# Configure Comet's Opik +import opik +opik.configure(use_local=False) + + +class LLMJudgeResult(BaseModel): + """Pydantic model representing the result of LLM judge evaluation.""" + + score: int + reason: str + + +class LLMJudgeMetric(base_metric.BaseMetric): + """ + A metric that uses an LLM to judge the quality of AI-generated responses. + + Attributes: + - name (str): The name of the metric. + - model_name (str): The name of the LLM model to use for evaluation. + - llm_client (OpenAI): The client for communicating with the LLM. + - prompt_template (str): The template for constructing prompts to send to the LLM. + + Methods: + score(input, output, **ignored_kwargs): Evaluates the AI-generated response against the + provided input using the LLM as a judge. + + Returns: + ScoreResult: Contains the numerical score (1-5) and reasoning for the evaluation. + """ + + def __init__(self, name: str = "LLM judge metric", model_name: str = "atla-selene"): + # Initialize the metric with a name and model name + self.name = name + self.model_name = model_name + + # Initialize the OpenAI client with the API key and base URL for Atla + self.llm_client = OpenAI( + api_key=os.environ.get("ATLA_API_KEY"), + base_url="https://api.atla-ai.com/v1", + ) + + # Define the prompt template for the LLM + self.prompt_template = """ + You are an expert, impartial judge tasked with evaluating an AI-generated response based on a given instruction and scoring rubric. + Provide comprehensive feedback on the response, strictly adhering to the scoring rubric. Follow this with a score between 1 and 5. + + The format of the your response should be a json with no backticks that returns: + {{ + "score": , + "reason": "" + }} + + Scoring Rubric: + Does the response effectively use humor or wit to enhance the conversation? + Score 1: The response is devoid of any humor or wit. + Score 2: The response attempts humor, but it falls flat or is inappropriate. + Score 3: The response includes humor or wit, but it could be more effectively integrated. + Score 4: The response uses humor or wit effectively in most instances, enhancing the conversation. + Score 5: The response perfectly integrates humor or wit, greatly enhancing the enjoyment of the conversation. + + Here is the data to evaluate: + Instruction: {input} + Response: {output} + """ + + @opik.track + def score(self, input: str, output: str, **ignored_kwargs: Any): + """Method to evaluate the AI-generated response using the LLM judge.""" + # Apply prompt template and prepare the messages for the LLM + prompt = self.prompt_template.format(input=input, output=output) + messages = [{"role": "user", "content": prompt}] + + # Call the LLM with the prepared messages + response = self.llm_client.chat.completions.create( + model=self.model_name, messages=messages + ) + + # Parse the response from the LLM + response_content = ( + response.choices[0].message.content + if hasattr(response, "choices") + else response.message.content + ) + result_json = json.loads(response_content) + + # Return the result as a ScoreResult object with the score and reason + return score_result.ScoreResult( + name=self.name, value=result_json["score"], reason=result_json["reason"] + ) + + +# Example usage +metric = LLMJudgeMetric() +metric.score( + input="Tell me a joke.", + output="Why did the chicken cross the road? To get to the other side", +) diff --git a/llm-as-judge/pyproject.toml b/llm-as-judge/pyproject.toml new file mode 100644 index 00000000..7168d995 --- /dev/null +++ b/llm-as-judge/pyproject.toml @@ -0,0 +1,11 @@ +[project] +name = "llm-as-judge" +version = "0.1.0" +description = "Integration of Atla LLM Judge with Comet's Opik." +readme = "README.md" +requires-python = ">=3.12" +dependencies = [ + "openai>=1.75.0", + "opik>=1.7.7", + "python-dotenv>=1.1.0", +] diff --git a/llm-as-judge/uv.lock b/llm-as-judge/uv.lock new file mode 100644 index 00000000..1322b645 --- /dev/null +++ b/llm-as-judge/uv.lock @@ -0,0 +1,1270 @@ +version = 1 +revision = 1 +requires-python = ">=3.12" + +[[package]] +name = "aiohappyeyeballs" +version = "2.6.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = 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Apr 2025 18:47:13 +0000 Subject: [PATCH 2/2] changes added according to code review --- llm-as-judge/main.py | 29 ++++++++++++++++++++--------- 1 file changed, 20 insertions(+), 9 deletions(-) diff --git a/llm-as-judge/main.py b/llm-as-judge/main.py index 2a70ad3b..347d6ec5 100644 --- a/llm-as-judge/main.py +++ b/llm-as-judge/main.py @@ -45,9 +45,16 @@ def __init__(self, name: str = "LLM judge metric", model_name: str = "atla-selen self.name = name self.model_name = model_name + # Check if API key is available + api_key = os.environ.get("ATLA_API_KEY") + if not api_key: + raise ValueError( + "ATLA_API_KEY environment variable not found. Please check your .env file." + ) + # Initialize the OpenAI client with the API key and base URL for Atla self.llm_client = OpenAI( - api_key=os.environ.get("ATLA_API_KEY"), + api_key=api_key, base_url="https://api.atla-ai.com/v1", ) @@ -83,9 +90,12 @@ def score(self, input: str, output: str, **ignored_kwargs: Any): messages = [{"role": "user", "content": prompt}] # Call the LLM with the prepared messages - response = self.llm_client.chat.completions.create( - model=self.model_name, messages=messages - ) + try: + response = self.llm_client.chat.completions.create( + model=self.model_name, messages=messages + ) + except Exception as e: + raise RuntimeError(f"Error calling LLM API: {str(e)}") from e # Parse the response from the LLM response_content = ( @@ -102,8 +112,9 @@ def score(self, input: str, output: str, **ignored_kwargs: Any): # Example usage -metric = LLMJudgeMetric() -metric.score( - input="Tell me a joke.", - output="Why did the chicken cross the road? To get to the other side", -) +if __name__ == "__main__": + metric = LLMJudgeMetric() + metric.score( + input="Tell me a joke.", + output="Why did the chicken cross the road? To get to the other side", + )