initial commit

Dockerfile

@@ -0,0 +1,30 @@
+# Use the official Python 3.9 image
+FROM python:3.9
+ 
+# Set the working directory to /code
+WORKDIR /code
+ 
+# Copy the current directory contents into the container at /code
+COPY ./requirements.txt /code/requirements.txt
+ 
+# Install requirements.txt 
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+ 
+# Set up a new user named "user" with user ID 1000
+RUN useradd -m -u 1000 user
+# Switch to the "user" user
+USER user
+# Set home to the user's home directory
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+ 
+# Set the working directory to the user's home directory
+WORKDIR $HOME/app
+ 
+# Copy the current directory contents into the container at $HOME/app setting the owner to the user
+COPY --chown=user . $HOME/app
+ 
+# Start the FastAPI app on port 7860, the default port expected by Spaces
+# CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
+
+CMD gunicorn -k uvicorn.workers.UvicornWorker --workers 2 --threads=2 --max-requests 512 --bind 0.0.0.0:7860 app:app

README.md

@@ -8,4 +8,43 @@ pinned: false
 license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+## How to Use the API using python
+
+### Create a Token
+```
+import requests
+
+headers = {
+    'accept': 'application/json',
+    'Content-Type': 'application/json',
+}
+
+json_data = {
+    "ref_key": "F0eeQ419wvoCSPH7KBmsd9OiVkF0W0DxK1XE9T3BlbkFJ0",
+    "expiry_date": "2023-06-15"
+}
+
+response = requests.post('http://0.0.0.0:8000/create', headers=headers, json=json_data)
+token = response.json()
+```
+### calling open API (text-davinci-002/gpt-3.5-turbo)
+```
+import requests
+
+headers = {
+    'accept': 'application/json',
+    'Content-Type': 'application/json',
+    'Authorization': 'Bearer TOKEN',
+}
+
+json_data = {
+    'message': 'write a joke for me',
+    "openAI_token": OPENAI_KEY,
+    "model_name" : "gpt-3.5-turbo"
+}
+
+response = requests.post('http://0.0.0.0:8000/chat', headers=headers, json=json_data)
+if response.status_code == 200:
+    print(response.json())
+```
+

app.py

@@ -0,0 +1,101 @@
+import openai
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from fastapi import FastAPI, HTTPException, Depends, Request, Response
+from fastapi.security import OAuth2PasswordBearer
+from tinydb import TinyDB
+from tinydb import Query
+from datetime import datetime
+from utils import generate_token
+
+query = Query()
+db = TinyDB(".token.json")
+
+app = FastAPI()
+
+oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")
+
+REF_KEY = "F0eeQ419wvoCSPH7KBmsd9OiVkF0W0DxK1XE9T3BlbkFJ0"
+model_name = ""
+
+def verify_token(token: str = Depends(oauth2_scheme)):
+    expiry = -1
+    res = db.get(query.token == token)
+
+    if res:
+        expiry = (datetime.strptime(res["expiry_date"], '%Y-%m-%d') - datetime.strptime(res["created_at"], '%Y-%m-%d')).days
+    
+    if expiry < 0:
+        return {"message": "Token is not Valid"}
+    
+    return token
+
+
+class ChatInput(BaseModel):
+    message: str
+    openAI_token: str
+    model_name: str
+
+
+class RefToken(BaseModel):
+    expiry_date: str
+    ref_key: str
+
+
+@app.post("/create")
+async def create(data: RefToken):
+    token = "Reference Key is incorrect"
+    try:
+        if data.ref_key == REF_KEY:
+            token = generate_token(data.expiry_date, db) 
+            return {"TOKEN": token}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail="An error occurred while processing the request." + str(e))
+
+@app.get("/list")
+async def create(token: str = Depends(verify_token)):
+    token = "Reference Key is incorrect"
+    try:
+        data = db.all()
+        return {"data": data}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail="An error occurred while processing the request." + str(e))
+
+@app.post("/chat")
+async def chat_with_gpt(chat_input: ChatInput, token: str = Depends(verify_token)):
+    openai.api_key = chat_input.openAI_token
+    prompt = f"User: {chat_input.message}\nAI:"
+    model_name = chat_input.model_name
+    try:
+        if model_name == "text-davinci-002":
+            response = openai.Completion.create(
+                engine="text-davinci-002",
+                prompt=prompt,
+                max_tokens=50,
+                n=1,
+                stop=None,
+                temperature=0.7,
+            )
+            message = response.choices[0].text.strip()
+            usages = response["usage"]
+        
+        if model_name == "gpt-3.5-turbo":
+            response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",   
+            messages=[         
+                {"role": "system", "content": prompt}   
+            ])
+
+            message = response.choices[0]["message"]["content"]
+            usages = response["usage"]
+
+        if model_name == "":
+            message = "Plase select the model"
+            usages = ""
+
+        return {
+            "message": message,
+            "usages" : usages
+            }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail="An error occurred while processing the request." + str(e))

requirements.txt

@@ -0,0 +1,4 @@
+fastapi==0.95.1
+uvicorn==0.22.0
+openai==0.27.6
+tinydb==4.7.1

utils.py

@@ -0,0 +1,22 @@
+from datetime import datetime, timedelta, date
+import secrets
+import random
+import string
+
+
+def generate_token(expiry_date, db):
+    alphabet = string.ascii_letters  # Get a string containing all the alphabets (both upper and lower case)
+    first_char = random.choice(alphabet)  # Randomly choose an alphabet as the first character
+    token = "md-" + first_char + secrets.token_hex(60)
+
+    creation_date = date.today().strftime("%Y-%m-%d")
+
+    token_details = {
+        "created_at": creation_date,
+        "expiry_date" : expiry_date,
+        "token" : token 
+    }
+
+    db.insert(token_details)
+
+    return token