update /api/delete to use POST method instead of DELETE

README.md

@@ -21,7 +21,9 @@ console.log(response.message.content)
 ```
 
 ### Browser Usage
+
 To use the library without node, import the browser module.
+
 ```javascript
 import ollama from 'ollama/browser'
 ```
@@ -34,7 +36,11 @@ Response streaming can be enabled by setting `stream: true`, modifying function
 import ollama from 'ollama'
 
 const message = { role: 'user', content: 'Why is the sky blue?' }
-const response = await ollama.chat({ model: 'llama3.1', messages: [message], stream: true })
+const response = await ollama.chat({
+  model: 'llama3.1',
+  messages: [message],
+  stream: true,
+})
 for await (const part of response) {
   process.stdout.write(part.message.content)
 }
@@ -207,7 +213,7 @@ ollama.abort()
 This method will abort **all** streamed generations currently running with the client instance.
 If there is a need to manage streams with timeouts, it is recommended to have one Ollama client per stream.
 
-All asynchronous threads listening to streams (typically the ```for await (const part of response)```) will throw an ```AbortError``` exception. See [examples/abort/abort-all-requests.ts](examples/abort/abort-all-requests.ts) for an example.
+All asynchronous threads listening to streams (typically the `for await (const part of response)`) will throw an `AbortError` exception. See [examples/abort/abort-all-requests.ts](examples/abort/abort-all-requests.ts) for an example.
 
 ## Custom client
 

examples/abort/abort-all-requests.ts

@@ -8,45 +8,45 @@ setTimeout(() => {
 
 // Start multiple concurrent streaming requests
 Promise.all([
-  ollama.generate({
-    model: 'llama3.2',
-    prompt: 'Write a long story about dragons',
-    stream: true,
-  }).then(
-    async (stream) => {
+  ollama
+    .generate({
+      model: 'llama3.2',
+      prompt: 'Write a long story about dragons',
+      stream: true,
+    })
+    .then(async (stream) => {
       console.log(' Starting stream for dragons story...')
       for await (const chunk of stream) {
         process.stdout.write(' 1> ' + chunk.response)
       }
-    }
-  ),
+    }),
 
-  ollama.generate({
-    model: 'llama3.2', 
-    prompt: 'Write a long story about wizards',
-    stream: true,
-  }).then(
-    async (stream) => {
+  ollama
+    .generate({
+      model: 'llama3.2',
+      prompt: 'Write a long story about wizards',
+      stream: true,
+    })
+    .then(async (stream) => {
       console.log(' Starting stream for wizards story...')
       for await (const chunk of stream) {
         process.stdout.write(' 2> ' + chunk.response)
       }
-    }
-  ),
+    }),
 
-  ollama.generate({
-    model: 'llama3.2',
-    prompt: 'Write a long story about knights',
-    stream: true,
-  }).then(
-    async (stream) => {
+  ollama
+    .generate({
+      model: 'llama3.2',
+      prompt: 'Write a long story about knights',
+      stream: true,
+    })
+    .then(async (stream) => {
       console.log(' Starting stream for knights story...')
       for await (const chunk of stream) {
         process.stdout.write(' 3>' + chunk.response)
       }
-    }
-  )
-]).catch(error => {
+    }),
+]).catch((error) => {
   if (error.name === 'AbortError') {
     console.log('All requests have been aborted')
   } else {

examples/abort/abort-single-request.ts

@@ -13,38 +13,35 @@ setTimeout(() => {
 
 // Start multiple concurrent streaming requests with different clients
 Promise.all([
-  client1.generate({
-    model: 'llama3.2',
-    prompt: 'Write a long story about dragons',
-    stream: true,
-  }).then(
-    async (stream) => {
+  client1
+    .generate({
+      model: 'llama3.2',
+      prompt: 'Write a long story about dragons',
+      stream: true,
+    })
+    .then(async (stream) => {
       console.log(' Starting stream for dragons story...')
       for await (const chunk of stream) {
         process.stdout.write(' 1> ' + chunk.response)
       }
-    }
-  ),
+    }),
 
-  client2.generate({
-    model: 'llama3.2', 
-    prompt: 'Write a short story about wizards',
-    stream: true,
-  }).then(
-    async (stream) => {
+  client2
+    .generate({
+      model: 'llama3.2',
+      prompt: 'Write a short story about wizards',
+      stream: true,
+    })
+    .then(async (stream) => {
       console.log(' Starting stream for wizards story...')
       for await (const chunk of stream) {
         process.stdout.write(' 2> ' + chunk.response)
       }
-    }
-  ),
-
-]).catch(error => {
+    }),
+]).catch((error) => {
   if (error.name === 'AbortError') {
     console.log('Dragons story request has been aborted')
   } else {
     console.error('An error occurred:', error)
   }
 })
-
-

examples/structured_outputs/structured-outputs-image.ts

@@ -1,10 +1,10 @@
-import ollama from 'ollama';
+import ollama from 'ollama'
 
-import { z } from 'zod';
-import { zodToJsonSchema } from 'zod-to-json-schema';
-import { readFileSync } from 'fs';
-import { resolve } from 'path';
-import { createInterface } from 'readline';
+import { z } from 'zod'
+import { zodToJsonSchema } from 'zod-to-json-schema'
+import { readFileSync } from 'fs'
+import { resolve } from 'path'
+import { createInterface } from 'readline'
 
 /*
     Ollama vision capabilities with structured outputs
@@ -14,70 +14,83 @@ import { createInterface } from 'readline';
 
 // Schema for individual objects detected in the image
 const ObjectSchema = z.object({
-    name: z.string().describe('The name of the object'),
-    confidence: z.number().min(0).max(1).describe('The confidence score of the object detection'),
-    attributes: z.record(z.any()).optional().describe('Additional attributes of the object')
-});
+  name: z.string().describe('The name of the object'),
+  confidence: z
+    .number()
+    .min(0)
+    .max(1)
+    .describe('The confidence score of the object detection'),
+  attributes: z
+    .record(z.any())
+    .optional()
+    .describe('Additional attributes of the object'),
+})
 
 // Schema for individual objects detected in the image
 const ImageDescriptionSchema = z.object({
-    summary: z.string().describe('A concise summary of the image'),
-    objects: z.array(ObjectSchema).describe('An array of objects detected in the image'),
-    scene: z.string().describe('The scene of the image'),
-    colors: z.array(z.string()).describe('An array of colors detected in the image'),
-    time_of_day: z.enum(['Morning', 'Afternoon', 'Evening', 'Night']).describe('The time of day the image was taken'),
-    setting: z.enum(['Indoor', 'Outdoor', 'Unknown']).describe('The setting of the image'),
-    text_content: z.string().describe('Any text detected in the image')
-});
+  summary: z.string().describe('A concise summary of the image'),
+  objects: z.array(ObjectSchema).describe('An array of objects detected in the image'),
+  scene: z.string().describe('The scene of the image'),
+  colors: z.array(z.string()).describe('An array of colors detected in the image'),
+  time_of_day: z
+    .enum(['Morning', 'Afternoon', 'Evening', 'Night'])
+    .describe('The time of day the image was taken'),
+  setting: z.enum(['Indoor', 'Outdoor', 'Unknown']).describe('The setting of the image'),
+  text_content: z.string().describe('Any text detected in the image'),
+})
 
 async function run(model: string) {
-    // Create readline interface for user input
-    const rl = createInterface({
-        input: process.stdin,
-        output: process.stdout
-    });
+  // Create readline interface for user input
+  const rl = createInterface({
+    input: process.stdin,
+    output: process.stdout,
+  })
 
-    // Get path from user input
-    const path = await new Promise<string>(resolve => {
-        rl.question('Enter the path to your image: ', resolve);
-    });
-    rl.close();
+  // Get path from user input
+  const path = await new Promise<string>((resolve) => {
+    rl.question('Enter the path to your image: ', resolve)
+  })
+  rl.close()
 
-    // Verify the file exists and read it
-    try {
-        const imagePath = resolve(path);
-        const imageBuffer = readFileSync(imagePath);
-        const base64Image = imageBuffer.toString('base64');
-
-        // Convert the Zod schema to JSON Schema format
-        const jsonSchema = zodToJsonSchema(ImageDescriptionSchema);
+  // Verify the file exists and read it
+  try {
+    const imagePath = resolve(path)
+    const imageBuffer = readFileSync(imagePath)
+    const base64Image = imageBuffer.toString('base64')
 
-        const messages = [{
-            role: 'user',
-            content: 'Analyze this image and return a detailed JSON description including objects, scene, colors and any text detected. If you cannot determine certain details, leave those fields empty.',
-            images: [base64Image]
-        }];
+    // Convert the Zod schema to JSON Schema format
+    const jsonSchema = zodToJsonSchema(ImageDescriptionSchema)
 
-        const response = await ollama.chat({
-            model: model,
-            messages: messages,
-            format: jsonSchema,
-            options: {
-                temperature: 0 // Make responses more deterministic
-            }
-        });
+    const messages = [
+      {
+        role: 'user',
+        content:
+          'Analyze this image and return a detailed JSON description including objects, scene, colors and any text detected. If you cannot determine certain details, leave those fields empty.',
+        images: [base64Image],
+      },
+    ]
 
-        // Parse and validate the response
-        try {
-            const imageAnalysis = ImageDescriptionSchema.parse(JSON.parse(response.message.content));
-            console.log('Image Analysis:', imageAnalysis);
-        } catch (error) {
-            console.error("Generated invalid response:", error);
-        }
+    const response = await ollama.chat({
+      model: model,
+      messages: messages,
+      format: jsonSchema,
+      options: {
+        temperature: 0, // Make responses more deterministic
+      },
+    })
 
+    // Parse and validate the response
+    try {
+      const imageAnalysis = ImageDescriptionSchema.parse(
+        JSON.parse(response.message.content),
+      )
+      console.log('Image Analysis:', imageAnalysis)
     } catch (error) {
-        console.error("Error reading image file:", error);
+      console.error('Generated invalid response:', error)
     }
+  } catch (error) {
+    console.error('Error reading image file:', error)
+  }
 }
 
-run('llama3.2-vision').catch(console.error);
+run('llama3.2-vision').catch(console.error)