jbilcke-hf HF staff commited on
Commit
6463491
β€’
1 Parent(s): 9074714

the dynamic import is causing issue during build, but it's not an issue we can just put the var init inside the function

Browse files
src/app/queries/predict.ts CHANGED
@@ -1,13 +1,9 @@
1
  "use server"
2
 
3
  import { LLMEngine } from "@/types"
 
 
4
 
5
  const llmEngine = `${process.env.LLM_ENGINE || ""}` as LLMEngine
6
 
7
- export const predict = async () => {
8
- if (llmEngine === "OPENAI") {
9
- return (await import("./predictWithOpenAI")).predictWithOpenAI
10
- } else {
11
- return (await import("./predictWithHuggingFace")).predictWithHuggingFace
12
- }
13
- }
 
1
  "use server"
2
 
3
  import { LLMEngine } from "@/types"
4
+ import { predict as predictWithHuggingFace } from "./predictWithHuggingFace"
5
+ import { predict as predictWithOpenAI } from "./predictWithOpenAI"
6
 
7
  const llmEngine = `${process.env.LLM_ENGINE || ""}` as LLMEngine
8
 
9
+ export const predict = llmEngine === "OPENAI" ? predictWithOpenAI : predictWithHuggingFace
 
 
 
 
 
 
src/app/queries/predictWithHuggingFace.ts CHANGED
@@ -3,45 +3,45 @@
3
  import { HfInference, HfInferenceEndpoint } from "@huggingface/inference"
4
  import { LLMEngine } from "@/types"
5
 
6
- const hf = new HfInference(process.env.AUTH_HF_API_TOKEN)
 
7
 
8
- const llmEngine = `${process.env.LLM_ENGINE || ""}` as LLMEngine
9
- const inferenceEndpoint = `${process.env.LLM_HF_INFERENCE_ENDPOINT_URL || ""}`
10
- const inferenceModel = `${process.env.LLM_HF_INFERENCE_API_MODEL || ""}`
11
 
12
- let hfie: HfInferenceEndpoint = hf
13
 
14
- switch (llmEngine) {
15
- case "INFERENCE_ENDPOINT":
16
- if (inferenceEndpoint) {
17
- console.log("Using a custom HF Inference Endpoint")
18
- hfie = hf.endpoint(inferenceEndpoint)
19
- } else {
20
- const error = "No Inference Endpoint URL defined"
21
- console.error(error)
22
- throw new Error(error)
23
- }
24
- break;
25
-
26
- case "INFERENCE_API":
27
- if (inferenceModel) {
28
- console.log("Using an HF Inference API Model")
29
- } else {
30
- const error = "No Inference API model defined"
 
 
 
 
 
 
 
31
  console.error(error)
32
  throw new Error(error)
33
- }
34
- break;
35
-
36
- default:
37
- const error = "Please check your Hugging Face Inference API or Inference Endpoint settings"
38
- console.error(error)
39
- throw new Error(error)
40
- }
41
-
42
- const api = llmEngine === "INFERENCE_ENDPOINT" ? hfie : hf
43
 
44
- export async function predictWithHuggingFace(inputs: string) {
45
  let instructions = ""
46
  try {
47
  for await (const output of api.textGenerationStream({
 
3
  import { HfInference, HfInferenceEndpoint } from "@huggingface/inference"
4
  import { LLMEngine } from "@/types"
5
 
6
+ export async function predict(inputs: string): Promise<string> {
7
+ const hf = new HfInference(process.env.AUTH_HF_API_TOKEN)
8
 
9
+ const llmEngine = `${process.env.LLM_ENGINE || ""}` as LLMEngine
10
+ const inferenceEndpoint = `${process.env.LLM_HF_INFERENCE_ENDPOINT_URL || ""}`
11
+ const inferenceModel = `${process.env.LLM_HF_INFERENCE_API_MODEL || ""}`
12
 
13
+ let hfie: HfInferenceEndpoint = hf
14
 
15
+ switch (llmEngine) {
16
+ case "INFERENCE_ENDPOINT":
17
+ if (inferenceEndpoint) {
18
+ console.log("Using a custom HF Inference Endpoint")
19
+ hfie = hf.endpoint(inferenceEndpoint)
20
+ } else {
21
+ const error = "No Inference Endpoint URL defined"
22
+ console.error(error)
23
+ throw new Error(error)
24
+ }
25
+ break;
26
+
27
+ case "INFERENCE_API":
28
+ if (inferenceModel) {
29
+ console.log("Using an HF Inference API Model")
30
+ } else {
31
+ const error = "No Inference API model defined"
32
+ console.error(error)
33
+ throw new Error(error)
34
+ }
35
+ break;
36
+
37
+ default:
38
+ const error = "Please check your Hugging Face Inference API or Inference Endpoint settings"
39
  console.error(error)
40
  throw new Error(error)
41
+ }
42
+
43
+ const api = llmEngine === "INFERENCE_ENDPOINT" ? hfie : hf
 
 
 
 
 
 
 
44
 
 
45
  let instructions = ""
46
  try {
47
  for await (const output of api.textGenerationStream({
src/app/queries/predictWithOpenAI.ts CHANGED
@@ -3,9 +3,8 @@
3
  import type { ChatCompletionMessage } from "openai/resources/chat"
4
  import OpenAI from "openai"
5
 
6
- const openaiApiKey = `${process.env.AUTH_OPENAI_API_KEY || ""}`
7
-
8
- export async function predictWithOpenAI(inputs: string) {
9
  const openaiApiBaseUrl = `${process.env.LLM_OPENAI_API_BASE_URL || "https://api.openai.com/v1"}`
10
  const openaiApiModel = `${process.env.LLM_OPENAI_API_MODEL || "gpt-3.5-turbo"}`
11
 
@@ -26,8 +25,9 @@ export async function predictWithOpenAI(inputs: string) {
26
  temperature: 0.8
27
  })
28
 
29
- return res.choices[0].message.content
30
  } catch (err) {
31
  console.error(`error during generation: ${err}`)
 
32
  }
33
  }
 
3
  import type { ChatCompletionMessage } from "openai/resources/chat"
4
  import OpenAI from "openai"
5
 
6
+ export async function predict(inputs: string): Promise<string> {
7
+ const openaiApiKey = `${process.env.AUTH_OPENAI_API_KEY || ""}`
 
8
  const openaiApiBaseUrl = `${process.env.LLM_OPENAI_API_BASE_URL || "https://api.openai.com/v1"}`
9
  const openaiApiModel = `${process.env.LLM_OPENAI_API_MODEL || "gpt-3.5-turbo"}`
10
 
 
25
  temperature: 0.8
26
  })
27
 
28
+ return res.choices[0].message.content || ""
29
  } catch (err) {
30
  console.error(`error during generation: ${err}`)
31
+ return ""
32
  }
33
  }