{"id":3614,"date":"2025-02-04T15:05:16","date_gmt":"2025-02-04T09:35:16","guid":{"rendered":"https:\/\/www.rangakrish.com\/?p=3614"},"modified":"2025-02-04T15:05:16","modified_gmt":"2025-02-04T09:35:16","slug":"interacting-with-openai-api-using-golang","status":"publish","type":"post","link":"https:\/\/www.rangakrish.com\/index.php\/2025\/02\/04\/interacting-with-openai-api-using-golang\/","title":{"rendered":"Interacting with OpenAI API using Golang"},"content":{"rendered":"

I normally use Python\u2019s<\/strong> LangChain<\/strong><\/em> framework to communicate with OpenAI API<\/strong><\/em>. For a change, I wanted to see if Go<\/strong><\/em> has any libraries to access OpenAI<\/strong><\/em> and other LLMs<\/strong><\/em>. Interestingly I found that LangChainGo<\/strong><\/em><\/a>\u00a0is a port of LangChain<\/strong><\/em> for Golang<\/strong><\/em>!<\/p>\n

I decided to implement a simple Completetion<\/strong><\/em> request in both streaming and non-streaming modes. Turned out to be pretty straightforward. I am not implementing any fancy GUI for this example. It just prints onto the console.<\/p>\n

Here is the code that interacts with OpenAI<\/strong><\/em> in non-streaming (sync) mode:<\/p>\n

\"Non-streaming<\/a>
Non-streaming Mode<\/strong><\/figcaption><\/figure>\n

The corresponding output is this (there is a small delay before the whole output is printed):<\/p>\n

\"The<\/a>
The Output<\/strong><\/figcaption><\/figure>\n

Here is the code that works in async (streaming) mode:<\/p>\n

\"Streaming<\/a>
Streaming Mode<\/strong><\/figcaption><\/figure>\n

When you run this function, the output is printed in chunks as expected. The final output is shown below:<\/p>\n

\"Streaming<\/a>
Streaming Mode Output<\/strong><\/figcaption><\/figure>\n

As you can see, the code abstraction is pretty clean and intuitive. The good news is that LangChainGo<\/strong><\/em> supports many other LLMs<\/strong><\/em> too.\u00a0<\/span><\/p>\n

The source code can be downloaded here<\/strong><\/em><\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

I normally use Python\u2019s LangChain framework to communicate with OpenAI API. For a change, I wanted to see if Go has any libraries to access OpenAI and other LLMs. Interestingly I found that LangChainGo\u00a0is a port of LangChain for Golang! I decided to implement a simple Completetion request in both streaming and non-streaming modes. Turned […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[141,388,17],"tags":[412,414,354,413],"class_list":["post-3614","post","type-post","status-publish","format-standard","hentry","category-golang","category-openai","category-programming","tag-golang","tag-non-streaming","tag-openai","tag-streaming"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p9OLnF-Wi","jetpack-related-posts":[{"id":3626,"url":"https:\/\/www.rangakrish.com\/index.php\/2025\/02\/21\/using-openai-from-mathematica-part-3\/","url_meta":{"origin":3614,"position":0},"title":"Using OpenAI from Mathematica: Part-3","author":"admin","date":"February 21, 2025","format":false,"excerpt":"Let us continue our discussion on using Mathematica to interact with OpenAI (you may want to go through the earlier article as well). The simplest function to interact with the LLM is LLMSynthesize[]. As you might have guessed, this is a \u201csync\u201d (non-streaming) call. What if you expect a long\u2026","rel":"","context":"In "Mathematica"","block_context":{"text":"Mathematica","link":"https:\/\/www.rangakrish.com\/index.php\/category\/mathematica\/"},"img":{"alt_text":"Basic LLMSynthesize","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2025\/02\/fig1-300x21.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2025\/02\/fig1-300x21.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2025\/02\/fig1-300x21.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":3599,"url":"https:\/\/www.rangakrish.com\/index.php\/2025\/01\/20\/using-openai-from-allegro-common-lisp\/","url_meta":{"origin":3614,"position":1},"title":"Using OpenAI from Allegro Common Lisp","author":"admin","date":"January 20, 2025","format":false,"excerpt":"Allegro Common Lisp ver 11.0\u00a0introduced support for OpenAI LLMs. In this article, let us look at some of the functions for interacting with OpenAI. First we need to specify basic parameters such as the API key, LLM to use, Temperature, etc. I have defined a convenient function configure-openai to do\u2026","rel":"","context":"In "LISP"","block_context":{"text":"LISP","link":"https:\/\/www.rangakrish.com\/index.php\/category\/lisp\/"},"img":{"alt_text":"Configuring the LLM","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2025\/01\/fig1-300x101.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":3050,"url":"https:\/\/www.rangakrish.com\/index.php\/2023\/03\/16\/building-a-xojo-app-to-interact-with-openai-api\/","url_meta":{"origin":3614,"position":2},"title":"Building a Xojo App to Interact with OpenAI API","author":"admin","date":"March 16, 2023","format":false,"excerpt":"A few weeks ago I registered with OpenAI to access its services through API and created a secret Key for my use. I then decided to build a simple application to try out the \u201cChat\u201d and \u201cCompletion\u201d models. Since I have several tools at my disposal (RAD Studio, LispWorks, Allegro\u2026","rel":"","context":"In "OpenAI"","block_context":{"text":"OpenAI","link":"https:\/\/www.rangakrish.com\/index.php\/category\/openai\/"},"img":{"alt_text":"Initial Screen","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2023\/03\/Initial-Screen-300x232.png?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":3846,"url":"https:\/\/www.rangakrish.com\/index.php\/2025\/11\/17\/implementing-zero-knowledge-proof-in-golang\/","url_meta":{"origin":3614,"position":3},"title":"Implementing Zero-Knowledge Proof in Golang","author":"admin","date":"November 17, 2025","format":false,"excerpt":"Zero-Knowledge Proofs (ZKP) are a fascinating area within Cryptography. These allow one party, called the \u201cProver\u201d, to convince another party, called the \u201cVerifier\u201d, that some statement is true without revealing the underlying information. There are two basic types of ZKPs: Interactive and non-interactive. The former requires a series of messages\u2026","rel":"","context":"In "Golang"","block_context":{"text":"Golang","link":"https:\/\/www.rangakrish.com\/index.php\/category\/golang\/"},"img":{"alt_text":"Circuit for Proving Age","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2025\/11\/circuit-300x136.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2025\/11\/circuit-300x136.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2025\/11\/circuit-300x136.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":3381,"url":"https:\/\/www.rangakrish.com\/index.php\/2024\/05\/20\/using-openai-from-mathematica\/","url_meta":{"origin":3614,"position":4},"title":"Using OpenAI from Mathematica","author":"admin","date":"May 20, 2024","format":false,"excerpt":"Mathematica was among the first to integrate with OpenAI. The functionality is nicely exposed in terms of a few pre-defined functions. Let us explore some of the functionality in today\u2019s article. The simplest way to get started is to use LLMSynthesize\u00a0function: It can take a few seconds before you get\u2026","rel":"","context":"In "Mathematica"","block_context":{"text":"Mathematica","link":"https:\/\/www.rangakrish.com\/index.php\/category\/mathematica\/"},"img":{"alt_text":"LLMSynthesize Function","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2024\/05\/Example1-300x27.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2024\/05\/Example1-300x27.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2024\/05\/Example1-300x27.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":3514,"url":"https:\/\/www.rangakrish.com\/index.php\/2024\/10\/02\/using-openai-from-mathematica-part-2\/","url_meta":{"origin":3614,"position":5},"title":"Using OpenAI from Mathematica: Part-2","author":"admin","date":"October 2, 2024","format":false,"excerpt":"I had written an earlier article\u00a0showing how to use OpenAI models from Mathematica ver 14.0.\u00a0 Wolfram Mathematica ver 14.1 was released recently, with several improvements in the area of LLMs. Of course, there are many other core additions as well, but our focus is on LLMs in this article. This\u2026","rel":"","context":"In "Mathematica"","block_context":{"text":"Mathematica","link":"https:\/\/www.rangakrish.com\/index.php\/category\/mathematica\/"},"img":{"alt_text":"LLMSynthesize Function","src":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2024\/10\/image1-300x71.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2024\/10\/image1-300x71.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/www.rangakrish.com\/wp-content\/uploads\/2024\/10\/image1-300x71.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]}],"_links":{"self":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/posts\/3614","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/comments?post=3614"}],"version-history":[{"count":0,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/posts\/3614\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/media?parent=3614"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/categories?post=3614"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.rangakrish.com\/index.php\/wp-json\/wp\/v2\/tags?post=3614"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}