├── .gitignore
├── .env.sample
├── requirements.txt
├── vercel.json
├── flaskGPT.py
└── README.md


/.gitignore:
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1 | .vercel
2 | .env
3 | /venv/


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/.env.sample:
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1 | OPENAI_API_KEY=sk-your-openai-api-key
2 | 


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/requirements.txt:
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1 | langchain==0.0.188
2 | openai==0.27.7
3 | google-api-python-client==2.88.0
4 | python-dotenv==1.0.0
5 | flask==2.3.2


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/vercel.json:
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1 | {
2 |     "builds": [{"src": "flaskGPT.py", "use": "@vercel/python"}],
3 |     "routes": [{"src": "/api/(.*)", "dest": "flaskGPT.py"}]
4 | }


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/flaskGPT.py:
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 1 | from dotenv import load_dotenv
 2 | load_dotenv()
 3 | 
 4 | from langchain.chat_models import ChatOpenAI
 5 | from langchain.schema import (
 6 |     AIMessage,
 7 |     HumanMessage,
 8 |     SystemMessage
 9 | )
10 | 
11 | chat = ChatOpenAI(
12 |     temperature=1.0,
13 |     max_tokens=100,
14 |     model_name="gpt-3.5-turbo",
15 |     verbose=True
16 | )
17 | 
18 | from flask import Flask, request, jsonify
19 | app = Flask(__name__)
20 | 
21 | @app.route('/api/prompt', methods=['POST'])
22 | def prompt():
23 |     data = request.get_json()
24 |     prompt = data.get('prompt', '')
25 | 
26 |     messages = [
27 |         SystemMessage(content="You are a funny chatboth only capable of answering one question at a time. Remember to have fun!"),
28 |         HumanMessage(content=prompt)
29 |     ]
30 | 
31 |     output = chat(messages)
32 |     return jsonify({'response': output.content})
33 | 
34 | if __name__ == '__main__':
35 |     app.run(port=3000)


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/README.md:
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 1 | # High Level
 2 | This project was created to be thin and enable you to build on top.  
 3 | It uses Langchain, OpenAI, Flask, and Vercel to KISS and deploy a One-Shot AI server in seconds.
 4 |   
 5 | Doesn't have what you're looking for?  
 6 | Go build it!  
 7 |   
 8 | ## Deploy on Vercel
 9 | Use this flow to yolo deploy to Vercel.  
10 |   
11 | ### Deploy directly from github
12 | 1. Fork the repostory.
13 | 2. Go to Vercel and choose this repository to deploy.
14 | 3. Go to your Vercel, this project's page & settings after it completes deployment, and configure the Environment Variables by setting.
15 | ```
16 | OPEN_API_KEY=your-api-key
17 | ```
18 | 3. Curl your endpoint and test your server!
19 | ```
20 | curl -X POST https://flaskgpt-your-account-vercel.app/api/prompt -H "Content-Type: application/json" -d "{\"prompt\": \"What is the funniest joke you've ever heard?\"}"
21 | ```
22 | 4. Have fun!
23 | 
24 | ## Deploy locally
25 | Use this flow to run the server locally and test it.
26 | 
27 | ### Terminal #1 - Setup your server
28 | 1. Clone the repository onto your local filesystem.
29 | 2. Configure your .env by setting
30 | ```
31 | OPEN_API_KEY=your-api-key
32 | ```
33 | 3. Setup your venv and activate it
34 | ```
35 | python3 -m venv venv
36 | source venv/bin/activate
37 | ```
38 | 4. Install dependencies
39 | ```
40 | pip install -r requirements.txt
41 | ```
42 | 5. Start your server
43 | ```
44 | python3 flaskGPT.py
45 | ```
46 | 
47 | ### Terminal #2 - Test your server
48 | 6. Start a new terminal
49 | 7. In your 2nd terminal, curl your server
50 | ```
51 | curl -X POST https://flaskgpt-your-account-vercel.app/api/prompt -H "Content-Type: application/json" -d "{\"prompt\": \"What is the funniest joke you've ever heard?\"}"
52 | ```
53 | 8. Have fun!
54 | 
55 | 


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