wip: fix generate_completion params

denops/ollama/api/generate_completion.ts

@@ -2,7 +2,7 @@ import {
   is,
   type PredicateType,
 } from "https://deno.land/x/[email protected]/mod.ts";
-import { isErrorResponse, isFormat, type RequestOptions } from "./types.ts";
+import { isErrorResponse, type RequestOptions } from "./types.ts";
 import { parseJSONStream } from "./base.ts";
 import { doPost } from "./base.ts";
 
@@ -11,32 +11,6 @@ import { doPost } from "./base.ts";
 // Endpoint: /api/generate
 // Usage: https://github.com/jmorganca/ollama/blob/main/docs/api.md#generate-a-completion
 
-export const isGenerateCompletionParam = is.ObjectOf({
-  // The model name
-  model: is.String,
-  // The prompt to generate a response for
-  prompt: is.String,
-  // (optional) A list of base64-encoded images (for multimodal models such as llava)
-  images: is.OptionalOf(is.ArrayOf(is.String)),
-  // (optional) The format to return a response in. Currently the only accepted value is json
-  format: isFormat,
-  // (optional) Additional model parameters listed in the documentation for the Modelfile such as temperature
-  options: is.OptionalOf(is.Record),
-  // (optional) System message to (overrides what is defined in the Modelfile)
-  system: is.OptionalOf(is.String),
-  // (optional) The full prompt or prompt template (overrides what is defined in the Modelfile)
-  template: is.OptionalOf(is.String),
-  // (optional) The context parameter returned from a previous request to /generate, this can be used to keep a short conversational memory
-  context: is.OptionalOf(is.ArrayOf(is.Number)),
-  // (optional) If false the response will be returned as a single response object, rather than a stream of objects
-  stream: is.OptionalOf(is.Boolean),
-  // (optional) If true no formatting will be applied to the prompt. You may choose to use the raw parameter if you are specifying a full templated prompt in your request to the API.
-  raw: is.OptionalOf(is.Boolean),
-});
-export type GenerateCompletionParam = PredicateType<
-  typeof isGenerateCompletionParam
->;
-
 export const isGenerateCompletionResponse = is.OneOf([
   isErrorResponse,
   is.ObjectOf({
@@ -68,16 +42,37 @@ export type GenerateCompletionResponse = PredicateType<
   typeof isGenerateCompletionResponse
 >;
 
+export type GenerateCompletionParam = {
+  // A list of base64-encoded images (for multimodal models such as llava)
+  images?: string[] | undefined;
+  // The format to return a response in. Currently the only accepted value is json
+  format?: "json" | undefined;
+  // Additional model parameters listed in the documentation for the Modelfile such as temperature
+  options?: Record<PropertyKey, unknown> | undefined;
+  // System message to (overrides what is defined in the Modelfile)
+  system?: string | undefined;
+  // The full prompt or prompt template (overrides what is defined in the Modelfile)
+  template?: string | undefined;
+  // The context parameter returned from a previous request to /generate, this can be used to keep a short conversational memory
+  context?: number[] | undefined;
+  // If true no formatting will be applied to the prompt. You may choose to use the raw parameter if you are specifying a full templated prompt in your request to the API.
+  raw?: boolean | undefined;
+};
+
 /** Generate a response for a given prompt with a provided model.
  * This is a streaming endpoint, so there will be a series of responses.
  * The final response object will include statistics and additional data from the request.
  */
 export async function generateCompletion(
-  param: GenerateCompletionParam,
+  // The model name
+  model: string,
+  // The prompt to generate a response for
+  prompt: string,
+  param?: GenerateCompletionParam,
   options?: RequestOptions,
 ) {
   return parseJSONStream(
-    await doPost("/api/generate", param, options),
+    await doPost("/api/generate", { model, prompt, ...param }, options),
     isGenerateCompletionResponse,
   );
 }

denops/ollama/api/generate_completion_test.ts

@@ -23,10 +23,10 @@ Deno.test("generateCompletion", async (t) => {
     });
     try {
       await t.step("should call fetch with the correct arguments", async () => {
-        const result = await generateCompletion({
-          model: "model1",
-          prompt: "How to run?",
-        });
+        const result = await generateCompletion(
+          "model1",
+          "How to run?",
+        );
         assertEquals(result.response.status, 200);
         assertSpyCalls(fetchStub, 1);
         assertSpyCallArgs(fetchStub, 0, [
@@ -76,14 +76,13 @@ Deno.test("generateCompletion", async (t) => {
     try {
       await t.step("should call fetch with the correct arguments", async () => {
         const result = await generateCompletion(
+          "model1",
+          "run",
           {
-            model: "model1",
-            prompt: "run",
             context: [1, 2, 3],
             format: "json",
             images: ["foo-image-1", "foo-image-2"],
             system: "foo-system",
-            stream: true,
             raw: true,
             template: "How to %s?",
           },
@@ -97,7 +96,7 @@ Deno.test("generateCompletion", async (t) => {
           new URL("https://example.com:33562/api/generate"),
           {
             body:
-              '{"model":"model1","prompt":"run","context":[1,2,3],"format":"json","images":["foo-image-1","foo-image-2"],"system":"foo-system","stream":true,"raw":true,"template":"How to %s?"}',
+              '{"model":"model1","prompt":"run","context":[1,2,3],"format":"json","images":["foo-image-1","foo-image-2"],"system":"foo-system","raw":true,"template":"How to %s?"}',
             headers: { "Content-Type": "application/json" },
             method: "POST",
           },

denops/ollama/dispatch/start_chat.ts

@@ -96,7 +96,7 @@ async function promptCallback(
 
   const { signal, cancel } = await canceller(denops);
   try {
-    const result = await generateCompletion({ model, prompt, context }, {
+    const result = await generateCompletion(model, prompt, { context }, {
       signal,
     });
     if (!result.body) {