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docs/core_docs/docs/use_cases/media.mdx

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@@ -25,17 +25,17 @@ npm install @langchain/google-vertexai @langchain/core
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The first example loads an audio (MP3) file containing Mozart's Requiem in D Minor and prompts Gemini to return a single array of strings, with each string being an instrument from the song.
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import CodeBlock from "@theme/CodeBlock"
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import CodeBlock from "@theme/CodeBlock";
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import AudioExample from "@examples/use_cases/audio.ts"
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import AudioExample from "@examples/use_cases/audio.ts";
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<CodeBlock language="typescript">{AudioExample}</CodeBlock>
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From a quick Google search, we see the song was composed using the following instruments:
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```txt
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The Requiem is scored for 2 basset horns in F, 2 bassoons, 2 trumpets in D, 3 trombones (alto, tenor, and bass),
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timpani (2 drums), violins, viola, and basso continuo (cello, double bass, and organ).
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timpani (2 drums), violins, viola, and basso continuo (cello, double bass, and organ).
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```
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Gemini did pretty well here! For music not being it's primary focus, it was able to identify a few of the instruments used in the song, and didn't hallucinate any!
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This example takes a screen recording of a [LangChain YouTube video on datasets and testing in LangSmith](https://www.youtube.com/watch?v=N9hjO-Uy1Vo) sped up to 1.5x speed.
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It is then converted to `base64` format like the example above, and sent to Gemini with a prompt asking for structured output of tasks I can do to followup on the video.
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import VideoExample from "@examples/use_cases/video.ts"
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import VideoExample from "@examples/use_cases/video.ts";
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<CodeBlock language="typescript">{VideoExample}</CodeBlock>
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Here it also did well, giving me three tasks, just like I requested. It also responded with a valid JSON array, even though no function calling was used!
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Here it also did well, giving me three tasks, just like I requested. It also responded with a valid JSON array, even though no function calling was used!

examples/src/use_cases/media/audio.ts

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import { ChatPromptTemplate, MessagesPlaceholder } from "@langchain/core/prompts";
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import {
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ChatPromptTemplate,
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MessagesPlaceholder,
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} from "@langchain/core/prompts";
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import { ChatVertexAI } from "@langchain/google-vertexai";
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import { HumanMessage } from "@langchain/core/messages";
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import fs from "fs";

examples/src/use_cases/media/video.ts

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import { ChatPromptTemplate, MessagesPlaceholder } from "@langchain/core/prompts";
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import {
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ChatPromptTemplate,
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MessagesPlaceholder,
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} from "@langchain/core/prompts";
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import { ChatVertexAI } from "@langchain/google-vertexai";
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import { HumanMessage } from "@langchain/core/messages";
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import fs from "fs";
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"Learn how to use the LangSmith SDK to create, edit, and manage datasets programmatically, allowing for automation and integration with other tools.",
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"Investigate the versioning capabilities of LangSmith datasets and understand how to track changes, revert to previous versions, and collaborate effectively on dataset development."
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]
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*/
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*/

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