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import requests |
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import os |
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from openai import OpenAI |
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from fastapi import FastAPI, Body |
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import gradio as gr |
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CUSTOM_PATH = "/" |
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client = OpenAI(api_key=os.environ['OPEN_API_KEY']) |
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response = client.completions.create( |
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model="gpt-3.5-turbo-instruct", |
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prompt="Write a tagline for an ice cream shop." |
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) |
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app = FastAPI() |
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@app.post("/chat") |
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async def chat(body: dict = Body(...)): |
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if(body["context"] == "Grammar Checker"): |
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content = "You are a grammar expert. Grammar check and suggest with the corrected paragraph. Also calculate a confidence score for the generated content considering the punctuations, correctness, clarity, enganement and delivery" |
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elif(body["context"] == "Gift Recommender"): |
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content = "You are a Gift Recommender. Suggest Gifts based on the age and gender." |
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else: |
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content = "You are a helpful assistant." |
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response = client.chat.completions.create( |
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model="gpt-3.5-turbo", |
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messages=[ |
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{"role": "system", "content": content+" The output should be in more natural tone."}, |
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{"role": "user", "content": body['prompt']} |
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] |
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) |
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return response |
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def converse(inp, history, context): |
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response = requests.post("http://localhost:8000/chat", json={"prompt": inp, "context": context}) |
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return response.json()['choices'][0]['message']['content'] |
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title = "Welcome to the Chatbot Interface!" |
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description = "Feel free to start a conversation with the chatbot." |
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dropdown = gr.Dropdown( |
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["Assistant", "Grammar Checker", "Gift Recommender"], label="Context", value="Assistant" |
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) |
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chatapp = gr.ChatInterface( |
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fn=converse, |
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title=title, |
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description=description, |
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additional_inputs=[dropdown] |
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) |
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app = gr.mount_gradio_app(app, chatapp, path=CUSTOM_PATH) |
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