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pre[class*=language-]{background-color:rgba(var(--ui-12-rgb),.5);color:var(--text-01);text-shadow:none;padding:var(--spacing-00);border-radius:var(--spacing-00);font-size:smaller}",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false},"responsivegrid":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"quickstart_hero":"aem-GridColumn aem-GridColumn--default--12","flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn 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Evalanche","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers/guides/orchestrate-llm-evaluations-with-evalanche","currentPage":true},{"title":"Guides","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers/guides","currentPage":false},{"title":"Snowflake for Developers","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers","currentPage":false}],"quickstartHeroTitle":{"lines":["Orchestrate LLM Evaluations in Snowflake with Evalanche"],"type":"heading2",":type":"snowflake-site/components/title-v2"},"quickstartHeroAuthor":"Jason Summer","quickstartHeroForkRepoLink":{"id":"button-4893f5a349","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://github.com/Snowflake-Labs/sfquickstarts/tree/master/site/sfguides/src/orchestrate-llm-evaluations-with-evalanche"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"Fork Repo"}},"flexible_column_cont":{"id":"flexible-column-container-c2e62793c4","propertiesId":"quickstart-template-main-flexible-container","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"id":"container-e554c60e1c","layout":"SIMPLE",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"contentfragment":{"id":"contentfragment-22a7b392dd","paragraphs":["<!-- ------------------------ -->\n","\u003Ch2\u003EOverview\u003C/h2\u003E\n","\u003Cp\u003EBy completing this guide, you will have deployed the Evalanche application in a Snowflake account and conducted your first LLM use case evaluation.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/home.png\" alt=\"Evalanche\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EWhy Conduct Evaluations?\u003C/h3\u003E\n","\u003Cp\u003EBuilding and refining LLM use cases can be an arduous process. Differences in models, architectures, prompts, contexts, etc. can all have impactful changes in your results. Using objective, quantitative measurements to compare results is critical to achieving desired results and selecting the best implementation.\u003C/p\u003E\n","\u003Ch3\u003EWhat is Evalanche?\u003C/h3\u003E\n","\u003Cp\u003EEvalanche is a Streamlit in Snowflake (SiS) app that provides a single location to evaluate and compare LLM use case outputs in a streamlined, on demand, and automated fashion.\u003C/p\u003E\n","\u003Cp\u003EEvalanche's primary structure is based on 2 components: 1) Metrics and 2) Data Sources.\nTogether, Metrics and Data Sources can be combined to make an Evaluation.\nIn other words, an Evaluation will calculate 1 or more Metrics for every record in a Data Source.\u003C/p\u003E\n","\u003Cp\u003ELearn more about \u003Ca href=\"https://medium.com/snowflake/lookout-its-an-evalanche-cac23f983970\"\u003EEvalanche\u003C/a\u003E.\u003C/p\u003E\n","\u003Ch3\u003EMetrics\u003C/h3\u003E\n","\u003Cp\u003EMetrics rely on LLMs to Judge (or score) results.\nA Metric mostly consists of required input(s) and a prompt asking the LLM to assess a specific quality of these required input(s).\u003C/p\u003E\n","\u003Ch3\u003EData Sources\u003C/h3\u003E\n","\u003Cp\u003EData Sources provide the values to Metrics’ required inputs. Data Sources can be a Snowflake table or a SQL SELECT statement.\u003C/p\u003E\n","\u003Ch3\u003EPrerequisites\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EA \u003Ca href=\"https://signup.snowflake.com/?utm_cta=quickstarts_\"\u003ESnowflake\u003C/a\u003E account\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You’ll Learn\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to deploy Evalanche to a Snowflake account\u003C/li\u003E\u003Cli\u003EHow create and run an LLM Evaluation\u003C/li\u003E\u003Cli\u003EHow to save an LLM Evaluation\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You’ll Build\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EA Streamlit in Snowflake application\u003C/li\u003E\u003Cli\u003EAn LLM Evaluation in Evalanche\u003C/li\u003E\u003C/ul\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EDeploying Evalanche to Streamlit\u003C/h2\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ECopy the entire contents of file \u003Ca href=\"https://github.com/Snowflake-Labs/emerging-solutions-toolbox/blob/main/framework-evalanche/setup/git_setup.sql\"\u003E\u003Ccode\u003Egit_setup.sql\u003C/code\u003E\u003C/a\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ELogin to your Snowflake account. Open a new SQL Worksheet by selecting \u003Cstrong\u003EProjects\u003C/strong\u003E > \u003Cstrong\u003EWorksheets\u003C/strong\u003E > \u003Cstrong\u003E+ SQL Worksheet\u003C/strong\u003E.\nPaste the copied contents from #1 into the SQL Worksheet.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Cstrong\u003ERun All\u003C/strong\u003E in the top right of the SQL Worksheet.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EThe logic running will:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ECreate a database, schema, stage, and several tables\u003C/li\u003E\u003Cli\u003ECreate an \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/git/git-overview\"\u003EAPI Integration and Git Repository\u003C/a\u003E in Snowflake for the source code in Snowflake-Labs Github\u003C/li\u003E\u003Cli\u003ECopy the source code from the Github repo to Snowflake stage\u003C/li\u003E\u003Cli\u003ECreate the \u003Ca href=\"/en/data-cloud/overview/streamlit-in-snowflake/\"\u003EStreamlit in Snowflake application\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EOnce competed, Evalanche will be accessible in your Snowflake account under the Streamlit section.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ECreate Sample Data\u003C/h2\u003E\n","\u003Cp\u003ENext, we will create hypothetical data for our first Evaluation. Within Snowsight, select the + tab to create a new SQL Worksheet.\u003C/p\u003E\n","\u003Cp\u003ECopy and paste the below SQL into the new SQL Worksheet and select Run All. This SQL will create a new table with hypothetical user questions, reference answers, and LLM-generated responses. Later, we will evaluate various qualities of the LLM-generated responses to the corresponding question, given the ideal reference answers.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ECREATE OR REPLACE TABLE GENAI_UTILITIES.EVALUATION.SAMPLE_TABLE(\n    USER_QUESTION TEXT,\n    EXPECTED_RESPONSE TEXT,\n    GENERATED_RESPONSE TEXT\n);\n\nINSERT INTO GENAI_UTILITIES.EVALUATION.SAMPLE_TABLE (USER_QUESTION, EXPECTED_RESPONSE, GENERATED_RESPONSE) VALUES\n('What is a common use case for Docker in software engineering?','Docker is commonly used to containerize applications, allowing for consistent environments across development, testing, and production.','Docker is used for creating isolated environments for testing new code, ensuring faster deployment across platforms.'),\n('How does a load balancer improve the scalability of a web application?','A load balancer distributes incoming traffic across multiple servers, ensuring that no single server becomes overwhelmed, improving scalability and availability.','Load balancers split the network traffic between servers but might introduce delays if not configured properly.'),\n('What is the difference between REST and SOAP APIs?','REST is an architectural style that uses standard HTTP methods, while SOAP is a protocol that defines strict rules for communication between systems.','REST uses simple HTTP requests and is less secure, while SOAP provides built-in security through protocols like WS-Security.'),\n('Why would you use microservices architecture over monolithic?','Microservices offer modularity, scalability, and ease of deployment, whereas monolithic architectures can be harder to scale and maintain as the codebase grows.','Microservices are faster and more secure than monolithic architectures, which are generally used for smaller projects.'),\n('How does a version control system like Git work?','Git tracks changes to files in a repository, allowing for collaboration, branching, and rollback to previous versions.','Git allows for creating multiple versions of software, which can then be integrated together in a final release.'),\n('What is Continuous Integration (CI) in DevOps?','CI is a practice where developers frequently integrate code into a shared repository, with automated tests to catch bugs early.','CI means developers frequently push code changes and perform tests to ensure they integrate smoothly with other changes.'),\n('Can you explain the SOLID principles in object-oriented design?','SOLID principles are guidelines for writing maintainable and scalable object-oriented software, including concepts like single responsibility and open-closed principle.','SOLID principles are techniques to ensure that each object is designed correctly in the software development lifecycle.'),\n('How is a NoSQL database different from a relational database?','NoSQL databases are schema-less and can handle unstructured data, whereas relational databases use structured schemas and SQL for querying.','NoSQL is faster and more scalable than SQL, making it better suited for large data sets, while relational databases are outdated.'),\n('What are the benefits of using Kubernetes in cloud deployment?','Kubernetes automates the deployment, scaling, and management of containerized applications, simplifying the operation of complex distributed systems.','Kubernetes is the main tool for managing cloud deployments, and it can replace virtual machines entirely in many setups.'),\n('What is the purpose of unit testing in software development?','Unit testing involves testing individual components or functions of the codebase to ensure they work as expected in isolation.','Unit tests are run after the entire software is complete to check for errors in the final version of the product.'),\n('How does caching improve the performance of a web application?','Caching stores frequently accessed data in memory to reduce response time, improving performance and reducing the load on the backend.','Caching can make the website run faster by keeping a copy of files in memory to avoid fetching them each time.'),\n('What are the main types of software testing?','The main types of testing include unit testing, integration testing, system testing, and acceptance testing.','Software testing includes functional, non-functional, and regression testing, each ensuring the application meets its requirements.'),\n('What is the role of an API gateway in microservices architecture?','An API gateway acts as an entry point to a microservices architecture, handling request routing, rate limiting, and security.','An API gateway serves as a firewall, protecting microservices from outside threats by filtering and blocking malicious requests.'),\n('How do you ensure database transactions maintain ACID properties?','ACID properties ensure that database transactions are atomic, consistent, isolated, and durable, preventing data corruption or loss.','ACID properties help ensure that the database runs faster by breaking down larger transactions into smaller parts.'),\n('What is the difference between asynchronous and synchronous programming?','Asynchronous programming allows multiple tasks to be performed concurrently, whereas synchronous programming executes tasks one after another.','Asynchronous programming waits for a task to finish before starting the next, while synchronous runs tasks concurrently.'),\n('Why is refactoring important in software engineering?','Refactoring improves code readability, maintainability, and performance without changing its external behavior.','Refactoring reduces the code base size and increases performance by eliminating redundant or dead code.'),\n('What is the purpose of load testing in software applications?','Load testing measures how a system performs under heavy usage to ensure it can handle expected traffic.','Load testing is the process of testing the maximum number of users that can access a website simultaneously.'),\n('How does OAuth differ from OpenID Connect?','OAuth is used for authorization, while OpenID Connect is used for authentication, allowing users to sign in securely.','OAuth lets you log in using a third-party service, while OpenID Connect is used for authorizing access to specific APIs.'),\n('What is the difference between blue/green and canary deployment strategies?','Blue/green deployment switches traffic between two environments, while canary deployment gradually introduces changes to a subset of users.','In blue/green deployment, one environment is updated while the other handles traffic; canary deployment releases small updates first.'),\n('What is the main function of a CI/CD pipeline?','A CI/CD pipeline automates the process of integrating code changes, testing, and deploying them to production.','The CI/CD pipeline is the development process where developers write, test, and deploy code to a production server.')\n;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ERun the below to view the created table.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESELECT * FROM GENAI_UTILITIES.EVALUATION.SAMPLE_TABLE;\n\u003C/code\u003E\u003C/pre\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EOpen Evalanche and Select Metrics\u003C/h2\u003E\n","\u003Cp\u003ENavigate to the Evalanche app by selecting \u003Cstrong\u003EProjects\u003C/strong\u003E > \u003Cstrong\u003EStreamlit\u003C/strong\u003E > \u003Cstrong\u003EEvalanche: GenAI Evaluation Application\u003C/strong\u003E. For a quick overview of the application, select the Help button.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Ccode\u003ECorrectness\u003C/code\u003E in the Metric Preview box to understand the Metric's Description and Required Inputs.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect \u003Ccode\u003EAnswer Relevancy\u003C/code\u003E in the Metric Preview.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESelect the checkboxes next to \u003Ccode\u003ECorrectness\u003C/code\u003E and \u003Ccode\u003EAnswer Relevancy\u003C/code\u003E Metrics. They will display on the left-side panel upon selection.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/select-metrics.png\" alt=\"SelectMetrics\"\u003E\u003C/p\u003E\n","\u003Cp\u003EClick Continue.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ESelect and Configure Data Source\u003C/h2\u003E\n","\u003Cp\u003EA Data Source should have at least the required input(s) for the select Metric(s). A Data Source can be a single table, 2 tables (if expected and generated results are separate), and/or custom SQL if the data are not readily available as singular tables.\u003C/p\u003E\n","\u003Cp\u003ESelect the sample dataset we created and select all columns.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/data-source-selection.png\" alt=\"Data Source Selection\"\u003E\u003C/p\u003E\n","\u003Cp\u003EClick Configure. In the pop up, select the column that corresponds to each Metric's required inputs as shown below.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/data-source-configuration.png\" alt=\"Data Source Configuration\"\u003E\u003C/p\u003E\n","\u003Cp\u003EClick Run.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EView Evaluation Results\u003C/h2\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/results.png\" alt=\"Evaluation Results\"\u003E\u003C/p\u003E\n","\u003Cp\u003EThe Evaluation results are now shown with each record in the Data Source receiving Metric value(s).\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003ESelect the checkbox next to a record with a low Metric value\u003C/li\u003E\u003Cli\u003EClick Review Record.\u003C/li\u003E\u003Cli\u003EIn the dialog, toggle the Metric to the one corresponding to the low score.\u003C/li\u003E\u003Cli\u003ESelect Analyze to gain an understanding of why the low score may have been received.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/analyze.png\" alt=\"Analyze Result\"\u003E\u003C/p\u003E\n","\u003Cp\u003EBased on the analysis, can you update the GENERATED_RESPONSE to improve the score? Change the GENERATED_RESPONSE to the below content (if you've selected the record about ACID properties as shown in the screenshot).\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-text\"\u003EACID properties maintain data consistency and prevent data corruption. They ensure integrity and consistency of database transactions.\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EClick Rerun. The score should improve. Click Save.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/rerun-result.png\" alt=\"Rerun Result\"\u003E\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ESave Results and Evaluation\u003C/h2\u003E\n","\u003Cp\u003EEvaluation results can be saved to Snowflake table(s) for subsequent analysis if desired. Click Record Results and provide a Snowflake database, schema, and table name.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/record-results.png\" alt=\"Record Results\"\u003E\u003C/p\u003E\n","\u003Cp\u003ELastly, we can save the Evaluation to run in the future and/or automate the Evaluation moving forward. Saving an Evaluation will enable us to run the same Evaluation directly from the homepage. An automated Evaluation will monitor the Data Source, scoring every new record that arrives and storing the result to a table. Like saved Evaluations, automated Evaluation results are viewable directly from the homepage.\u003C/p\u003E\n","\u003Cp\u003EClick Save Evaluation. Provide an Evaluation name (omitting spaces and special characters) and a description. Click Save.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/save-evaluation.png\" alt=\"Save Evalation\"\u003E\u003C/p\u003E\n","\u003Cp\u003EReturn to the homepage by clicking home in the left-side panel. Click the saved Evaluation in the Saved Evaluation section. The collapsed sections contain metadata detailing the Data Source, Metric(s), and configuration. Click Run to re-run the same Evaluation.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/view-saved-evaluation.png\" alt=\"View Saved Evalation\"\u003E\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EConclusion And Resources\u003C/h2\u003E\n","\u003Cp\u003ECongratulations! You've successfully deployed Evalanche and created your first saved Evaluation using out of the box Metrics. For ongoing evaluations or experimentation, we encourage using Automated Evaluations.\u003C/p\u003E\n","\u003Cp\u003EHave an LLM use case that would benefit from a novel Metric? Check out \u003Ca href=\"https://github.com/Snowflake-Labs/emerging-solutions-toolbox/tree/main/framework-evalanche#custom-metrics\"\u003ECreating Custom Metrics\u003C/a\u003E or message us with information about your use case!\u003C/p\u003E\n","\u003Ch3\u003EWhat You Learned\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EDeploying Evalanche to Streamlit in Snowflake\u003C/li\u003E\u003Cli\u003ECreating an Evalanche Evaluation\u003C/li\u003E\u003Cli\u003EAnalyzing Evaluation results\u003C/li\u003E\u003Cli\u003ESaving an Evaluation configuration\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ERelated Resources\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://github.com/Snowflake-Labs/emerging-solutions-toolbox/tree/main/framework-evalanche\"\u003ESource Code on GitHub\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://medium.com/snowflake/lookout-its-an-evalanche-cac23f983970\"\u003EMedium Article\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"/content/dam/snowflake-site/developers/2024/11/evalanche-snowflake-reference-architecture.pdf\"\u003EDownload Reference Architecture\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://youtu.be/lanCEOJ-914?list=TLGGEb1eaMM_q78yNDA5MjAyNQ\"\u003EWatch the Demo\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E"],"description":"","title":"Orchestrate LLM Evaluations in Snowflake with Evalanche",":type":"snowflake-site/components/contentfragment","isDeveloperGuidesPage":false,":items":{},":itemsOrder":[],"elements":{"quickstartArticleBody":{"dataType":"string","value":"\u003C!-- ------------------------ --\u003E\r\n## Overview \r\n\r\nBy completing this guide, you will have deployed the Evalanche application in a Snowflake account and conducted your first LLM use case evaluation.\r\n\r\n![Evalanche](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/home.png)\r\n\r\n### Why Conduct Evaluations?\r\nBuilding and refining LLM use cases can be an arduous process. Differences in models, architectures, prompts, contexts, etc. can all have impactful changes in your results. Using objective, quantitative measurements to compare results is critical to achieving desired results and selecting the best implementation.\r\n\r\n### What is Evalanche?\r\nEvalanche is a Streamlit in Snowflake (SiS) app that provides a single location to evaluate and compare LLM use case outputs in a streamlined, on demand, and automated fashion. \r\n\r\nEvalanche's primary structure is based on 2 components: 1) Metrics and 2) Data Sources. \r\nTogether, Metrics and Data Sources can be combined to make an Evaluation. \r\nIn other words, an Evaluation will calculate 1 or more Metrics for every record in a Data Source.\r\n\r\nLearn more about [Evalanche](https://medium.com/snowflake/lookout-its-an-evalanche-cac23f983970).\r\n\r\n### Metrics\r\nMetrics rely on LLMs to Judge (or score) results.\r\nA Metric mostly consists of required input(s) and a prompt asking the LLM to assess a specific quality of these required input(s).\r\n\r\n### Data Sources\r\nData Sources provide the values to Metrics’ required inputs. Data Sources can be a Snowflake table or a SQL SELECT statement. \r\n\r\n### Prerequisites\r\n- A [Snowflake](https://signup.snowflake.com/?utm_cta=quickstarts_) account\r\n\r\n### What You’ll Learn \r\n- How to deploy Evalanche to a Snowflake account\r\n- How create and run an LLM Evaluation  \r\n- How to save an LLM Evaluation\r\n\r\n### What You’ll Build \r\n- A Streamlit in Snowflake application\r\n- An LLM Evaluation in Evalanche\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n## Deploying Evalanche to Streamlit\r\n\r\n1. Copy the entire contents of file [`git_setup.sql`](https://github.com/Snowflake-Labs/emerging-solutions-toolbox/blob/main/framework-evalanche/setup/git_setup.sql).\r\n\r\n2. Login to your Snowflake account. Open a new SQL Worksheet by selecting **Projects** \u003E **Worksheets** \u003E **+ SQL Worksheet**. \r\nPaste the copied contents from #1 into the SQL Worksheet.\r\n\r\n3. Select **Run All** in the top right of the SQL Worksheet.\r\n\r\nThe logic running will:\r\n- Create a database, schema, stage, and several tables\r\n- Create an [API Integration and Git Repository](https://docs.snowflake.com/en/developer-guide/git/git-overview) in Snowflake for the source code in Snowflake-Labs Github\r\n- Copy the source code from the Github repo to Snowflake stage\r\n- Create the [Streamlit in Snowflake application](/en/data-cloud/overview/streamlit-in-snowflake/)\r\n\r\nOnce competed, Evalanche will be accessible in your Snowflake account under the Streamlit section. \r\n\r\n\u003C!-- ------------------------ --\u003E\r\n## Create Sample Data\r\n\r\nNext, we will create hypothetical data for our first Evaluation. Within Snowsight, select the + tab to create a new SQL Worksheet. \r\n\r\nCopy and paste the below SQL into the new SQL Worksheet and select Run All. This SQL will create a new table with hypothetical user questions, reference answers, and LLM-generated responses. Later, we will evaluate various qualities of the LLM-generated responses to the corresponding question, given the ideal reference answers.\r\n\r\n```sql\r\nCREATE OR REPLACE TABLE GENAI_UTILITIES.EVALUATION.SAMPLE_TABLE(\r\n    USER_QUESTION TEXT,\r\n    EXPECTED_RESPONSE TEXT,\r\n    GENERATED_RESPONSE TEXT\r\n);\r\n\r\nINSERT INTO GENAI_UTILITIES.EVALUATION.SAMPLE_TABLE (USER_QUESTION, EXPECTED_RESPONSE, GENERATED_RESPONSE) VALUES\r\n('What is a common use case for Docker in software engineering?','Docker is commonly used to containerize applications, allowing for consistent environments across development, testing, and production.','Docker is used for creating isolated environments for testing new code, ensuring faster deployment across platforms.'),\r\n('How does a load balancer improve the scalability of a web application?','A load balancer distributes incoming traffic across multiple servers, ensuring that no single server becomes overwhelmed, improving scalability and availability.','Load balancers split the network traffic between servers but might introduce delays if not configured properly.'),\r\n('What is the difference between REST and SOAP APIs?','REST is an architectural style that uses standard HTTP methods, while SOAP is a protocol that defines strict rules for communication between systems.','REST uses simple HTTP requests and is less secure, while SOAP provides built-in security through protocols like WS-Security.'),\r\n('Why would you use microservices architecture over monolithic?','Microservices offer modularity, scalability, and ease of deployment, whereas monolithic architectures can be harder to scale and maintain as the codebase grows.','Microservices are faster and more secure than monolithic architectures, which are generally used for smaller projects.'),\r\n('How does a version control system like Git work?','Git tracks changes to files in a repository, allowing for collaboration, branching, and rollback to previous versions.','Git allows for creating multiple versions of software, which can then be integrated together in a final release.'),\r\n('What is Continuous Integration (CI) in DevOps?','CI is a practice where developers frequently integrate code into a shared repository, with automated tests to catch bugs early.','CI means developers frequently push code changes and perform tests to ensure they integrate smoothly with other changes.'),\r\n('Can you explain the SOLID principles in object-oriented design?','SOLID principles are guidelines for writing maintainable and scalable object-oriented software, including concepts like single responsibility and open-closed principle.','SOLID principles are techniques to ensure that each object is designed correctly in the software development lifecycle.'),\r\n('How is a NoSQL database different from a relational database?','NoSQL databases are schema-less and can handle unstructured data, whereas relational databases use structured schemas and SQL for querying.','NoSQL is faster and more scalable than SQL, making it better suited for large data sets, while relational databases are outdated.'),\r\n('What are the benefits of using Kubernetes in cloud deployment?','Kubernetes automates the deployment, scaling, and management of containerized applications, simplifying the operation of complex distributed systems.','Kubernetes is the main tool for managing cloud deployments, and it can replace virtual machines entirely in many setups.'),\r\n('What is the purpose of unit testing in software development?','Unit testing involves testing individual components or functions of the codebase to ensure they work as expected in isolation.','Unit tests are run after the entire software is complete to check for errors in the final version of the product.'),\r\n('How does caching improve the performance of a web application?','Caching stores frequently accessed data in memory to reduce response time, improving performance and reducing the load on the backend.','Caching can make the website run faster by keeping a copy of files in memory to avoid fetching them each time.'),\r\n('What are the main types of software testing?','The main types of testing include unit testing, integration testing, system testing, and acceptance testing.','Software testing includes functional, non-functional, and regression testing, each ensuring the application meets its requirements.'),\r\n('What is the role of an API gateway in microservices architecture?','An API gateway acts as an entry point to a microservices architecture, handling request routing, rate limiting, and security.','An API gateway serves as a firewall, protecting microservices from outside threats by filtering and blocking malicious requests.'),\r\n('How do you ensure database transactions maintain ACID properties?','ACID properties ensure that database transactions are atomic, consistent, isolated, and durable, preventing data corruption or loss.','ACID properties help ensure that the database runs faster by breaking down larger transactions into smaller parts.'),\r\n('What is the difference between asynchronous and synchronous programming?','Asynchronous programming allows multiple tasks to be performed concurrently, whereas synchronous programming executes tasks one after another.','Asynchronous programming waits for a task to finish before starting the next, while synchronous runs tasks concurrently.'),\r\n('Why is refactoring important in software engineering?','Refactoring improves code readability, maintainability, and performance without changing its external behavior.','Refactoring reduces the code base size and increases performance by eliminating redundant or dead code.'),\r\n('What is the purpose of load testing in software applications?','Load testing measures how a system performs under heavy usage to ensure it can handle expected traffic.','Load testing is the process of testing the maximum number of users that can access a website simultaneously.'),\r\n('How does OAuth differ from OpenID Connect?','OAuth is used for authorization, while OpenID Connect is used for authentication, allowing users to sign in securely.','OAuth lets you log in using a third-party service, while OpenID Connect is used for authorizing access to specific APIs.'),\r\n('What is the difference between blue/green and canary deployment strategies?','Blue/green deployment switches traffic between two environments, while canary deployment gradually introduces changes to a subset of users.','In blue/green deployment, one environment is updated while the other handles traffic; canary deployment releases small updates first.'),\r\n('What is the main function of a CI/CD pipeline?','A CI/CD pipeline automates the process of integrating code changes, testing, and deploying them to production.','The CI/CD pipeline is the development process where developers write, test, and deploy code to a production server.')\r\n;\r\n```\r\n\r\nRun the below to view the created table. \r\n\r\n```sql\r\nSELECT * FROM GENAI_UTILITIES.EVALUATION.SAMPLE_TABLE;\r\n```\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n## Open Evalanche and Select Metrics\r\n\r\nNavigate to the Evalanche app by selecting **Projects** \u003E **Streamlit** \u003E **Evalanche: GenAI Evaluation Application**. For a quick overview of the application, select the Help button.\r\n\r\n1. Select `Correctness` in the Metric Preview box to understand the Metric's Description and Required Inputs. \r\n\r\n2. Select `Answer Relevancy` in the Metric Preview. \r\n\r\n3. Select the checkboxes next to `Correctness` and `Answer Relevancy` Metrics. They will display on the left-side panel upon selection.\r\n\r\n![SelectMetrics](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/select-metrics.png)\r\n\r\nClick Continue.\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n## Select and Configure Data Source\r\n\r\nA Data Source should have at least the required input(s) for the select Metric(s). A Data Source can be a single table, 2 tables (if expected and generated results are separate), and/or custom SQL if the data are not readily available as singular tables.\r\n\r\nSelect the sample dataset we created and select all columns.\r\n\r\n![Data Source Selection](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/data-source-selection.png)\r\n\r\nClick Configure. In the pop up, select the column that corresponds to each Metric's required inputs as shown below.\r\n\r\n![Data Source Configuration](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/data-source-configuration.png)\r\n\r\nClick Run.\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n## View Evaluation Results\r\n\r\n![Evaluation Results](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/results.png)\r\n\r\nThe Evaluation results are now shown with each record in the Data Source receiving Metric value(s). \r\n\r\n1. Select the checkbox next to a record with a low Metric value\r\n2. Click Review Record. \r\n3. In the dialog, toggle the Metric to the one corresponding to the low score. \r\n4. Select Analyze to gain an understanding of why the low score may have been received.\r\n\r\n![Analyze Result](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/analyze.png)\r\n\r\nBased on the analysis, can you update the GENERATED_RESPONSE to improve the score? Change the GENERATED_RESPONSE to the below content (if you've selected the record about ACID properties as shown in the screenshot). \r\n\r\n```text\r\nACID properties maintain data consistency and prevent data corruption. They ensure integrity and consistency of database transactions.\r\n```\r\n\r\nClick Rerun. The score should improve. Click Save.\r\n\r\n![Rerun Result](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/rerun-result.png)\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n## Save Results and Evaluation\r\n\r\nEvaluation results can be saved to Snowflake table(s) for subsequent analysis if desired. Click Record Results and provide a Snowflake database, schema, and table name. \r\n\r\n![Record Results](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/record-results.png)\r\n\r\nLastly, we can save the Evaluation to run in the future and/or automate the Evaluation moving forward. Saving an Evaluation will enable us to run the same Evaluation directly from the homepage. An automated Evaluation will monitor the Data Source, scoring every new record that arrives and storing the result to a table. Like saved Evaluations, automated Evaluation results are viewable directly from the homepage. \r\n\r\nClick Save Evaluation. Provide an Evaluation name (omitting spaces and special characters) and a description. Click Save.\r\n\r\n![Save Evalation](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/save-evaluation.png)\r\n\r\nReturn to the homepage by clicking home in the left-side panel. Click the saved Evaluation in the Saved Evaluation section. The collapsed sections contain metadata detailing the Data Source, Metric(s), and configuration. Click Run to re-run the same Evaluation.\r\n\r\n![View Saved Evalation](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/orchestrate-llm-evaluations-with-evalanche/view-saved-evaluation.png)\r\n\r\n\u003C!-- ------------------------ --\u003E\r\n## Conclusion And Resources\r\n\r\nCongratulations! You've successfully deployed Evalanche and created your first saved Evaluation using out of the box Metrics. For ongoing evaluations or experimentation, we encourage using Automated Evaluations. \r\n\r\nHave an LLM use case that would benefit from a novel Metric? Check out [Creating Custom Metrics](https://github.com/Snowflake-Labs/emerging-solutions-toolbox/tree/main/framework-evalanche#custom-metrics) or message us with information about your use case!\r\n\r\n\r\n### What You Learned\r\n- Deploying Evalanche to Streamlit in Snowflake\r\n- Creating an Evalanche Evaluation\r\n- Analyzing Evaluation results\r\n- Saving an Evaluation configuration\r\n\r\n### Related Resources\r\n- [Source Code on GitHub](https://github.com/Snowflake-Labs/emerging-solutions-toolbox/tree/main/framework-evalanche)\r\n- [Medium Article](https://medium.com/snowflake/lookout-its-an-evalanche-cac23f983970)\r\n- [Download Reference Architecture](/content/dam/snowflake-site/developers/2024/11/evalanche-snowflake-reference-architecture.pdf)\r\n- [Watch the Demo](https://youtu.be/lanCEOJ-914?list=TLGGEb1eaMM_q78yNDA5MjAyNQ)","title":"Quickstart Article Body","multiValue":false,":type":"text/x-markdown"},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image","multiValue":false,":type":"text/plain"}},"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],"model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-055f89e6b1","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"none","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"id":"container-15a960bec8","layout":"SIMPLE",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-f8603634fe","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2024-11-20",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-1bd56bac03","additionalClasses":"qs-disclaimer-text","text":"\u003Cp\u003E\u003Cspan style=\"color: #666;\"\u003EThis content is provided as is, and is not maintained on an ongoing basis. It may be out of date with current Snowflake 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