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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,11 @@ | ||
| CONSOLE_LOGGING=false # set to true to enable console logging | ||
| HTTP_ENABLED=true # set to true to enable HTTP | ||
| HTTP_PORT=88 # only used if HTTP_ENABLED=true | ||
| MAX_REQUEST_BODY_SIZE=50mb # maximum size for request body (for handling base64 images) | ||
| HTTPS_ENABLED=false # set to true to enable HTTPS | ||
| HTTPS_PORT=443 # only used if HTTPS_ENABLED=true | ||
| HTTPS_KEY_PATH=./some-path/mykey.key # or privkey.pem | ||
| HTTPS_CERT_PATH=./some-path/mycert.pem # or fullchain.pem | ||
| IP_RATE_LIMIT_ENABLED=true # enable rate limiting by IP | ||
| IP_RATE_LIMIT_WINDOW_MS=60000 # window in milliseconds to limit requests | ||
| IP_RATE_LIMIT_MAX_REQUESTS=100 # limit each IP to X requests per set window |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,3 +1,2 @@ | ||
| /.vscode | ||
| /node_modules | ||
| .env |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,3 @@ | ||
| AWS_REGION=us-west-2 # AWS Region | ||
| AWS_ACCESS_KEY_ID=AKIAWSxxxxxxxxxxxxxx # AWS Access Key ID | ||
| AWS_SECRET_ACCESS_KEY=xxxxxxxxxxxxxxxx # AWS Secret Access Key |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,2 @@ | ||
| node_modules | ||
| .env |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,73 @@ | ||
| import OpenAI from 'openai'; | ||
| import fs from 'fs'; | ||
| import path from 'path'; | ||
| import dotenv from 'dotenv'; | ||
|
|
||
| dotenv.config(); | ||
| const { AWS_REGION, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY } = process.env; | ||
|
|
||
| const __dirname = path.resolve(); | ||
| const base64Image = fs.readFileSync(path.join(__dirname, 'lizard.jpg')).toString('base64'); | ||
| const messages = [ | ||
| { | ||
| role: "system", | ||
| content: "You are a helpful AI assistant that follows instructions extremely well. Answer the user questions accurately.", | ||
| }, | ||
| { | ||
| role: "user", | ||
| content: [ | ||
| { | ||
| type: "text", | ||
| text: "What's in this image? Please describe it in detail." | ||
| }, | ||
| { | ||
| type: "image_url", | ||
| image_url: { | ||
| url: `data:image/jpeg;base64,${base64Image}` | ||
| // url: "/~https://github.com/jparkerweb/ref/blob/main/equill-labs/bedrock-proxy-endpoint/bedrock-proxy-endpoint.png?raw=true" | ||
| } | ||
| } | ||
| ] | ||
| }, | ||
| { | ||
| role: "assistant", | ||
| content: "", | ||
| }, | ||
| ]; | ||
|
|
||
| const baseURL = "http://localhost:88"; // URL of the Bedrock Proxy Endpoint | ||
| const apiKey = `${AWS_REGION}.${AWS_ACCESS_KEY_ID}.${AWS_SECRET_ACCESS_KEY}` // Your AWS Creds / API Key | ||
|
|
||
| const openai = new OpenAI({ | ||
| baseURL: baseURL, | ||
| apiKey: apiKey, | ||
| }); | ||
|
|
||
| async function main() { | ||
| try { | ||
| const chatCompletion = await openai.chat.completions.create({ | ||
| messages: messages, | ||
| model: "Claude-3-7-Sonnet-Thinking", | ||
| max_tokens: 2048, | ||
| temperature: 0.4, | ||
| top_p: 0.7, | ||
| stream: true, | ||
| }); | ||
|
|
||
| if (chatCompletion) { | ||
| for await (const chunk of chatCompletion) { | ||
| const response = chunk.choices[0]?.delta?.content || ""; | ||
| process.stdout.write(response); | ||
| } | ||
| // Add a newline at the end for cleaner output | ||
| process.stdout.write('\n'); | ||
| } | ||
| } catch (error) { | ||
| console.error('Error:', error); | ||
| } finally { | ||
| // Explicitly exit the process when done | ||
| process.exit(0); | ||
| } | ||
| } | ||
|
|
||
| main(); |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,58 @@ | ||
| import OpenAI from 'openai'; | ||
| import dotenv from 'dotenv'; | ||
|
|
||
| dotenv.config(); | ||
| const { AWS_REGION, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY } = process.env; | ||
|
|
||
| const messages = [ | ||
| { | ||
| role: "system", | ||
| content: "You are a helpful AI assistant that follows instructions extremely well. Answer the user questions accurately.", | ||
| }, | ||
| { | ||
| role: "user", | ||
| content: "Describe why the OpenAI API standard is so great. Limit your response to five sentences.", | ||
| }, | ||
| { | ||
| role: "assistant", | ||
| content: "", | ||
| }, | ||
| ]; | ||
|
|
||
| const baseURL = "http://localhost:88"; // URL of the Bedrock Proxy Endpoint | ||
| const apiKey = `${AWS_REGION}.${AWS_ACCESS_KEY_ID}.${AWS_SECRET_ACCESS_KEY}` // Your AWS Creds / API Key | ||
|
|
||
| const openai = new OpenAI({ | ||
| baseURL: baseURL, | ||
| apiKey: apiKey, | ||
| }); | ||
|
|
||
| async function main() { | ||
| try { | ||
| const chatCompletion = await openai.chat.completions.create({ | ||
| messages: messages, | ||
| model: "Claude-3-7-Sonnet-Thinking", | ||
| max_tokens: 2048, | ||
| temperature: 0.4, | ||
| top_p: 0.7, | ||
| stream: true, | ||
| include_thinking_data: true, | ||
| }); | ||
|
|
||
| if (chatCompletion) { | ||
| for await (const chunk of chatCompletion) { | ||
| const response = chunk.choices[0]?.delta?.content || ""; | ||
| process.stdout.write(response); | ||
| } | ||
| // Add a newline at the end for cleaner output | ||
| process.stdout.write('\n'); | ||
| } | ||
| } catch (error) { | ||
| console.error('Error:', error); | ||
| } finally { | ||
| // Explicitly exit the process when done | ||
| process.exit(0); | ||
| } | ||
| } | ||
|
|
||
| main(); |
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