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import gradio as gr | |
import openai | |
import json | |
from pinecone import Pinecone | |
pc = Pinecone(api_key='72f7d24d-c080-4ce6-a060-a489713284cb') | |
index_name = 'serverless-index' | |
# connect to index | |
index = pc.Index(index_name) | |
# get api key from platform.openai.com | |
openai.api_key = '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' | |
embed_model = "text-embedding-ada-002" | |
from openai import OpenAI | |
def generate_context(text): | |
body=json.dumps({"inputText": text}) | |
client = OpenAI(api_key=openai.api_key) | |
res = client.embeddings.create( | |
input=[text], | |
model=embed_model | |
).data[0].embedding | |
result = index.query(vector=res, top_k=7, include_metadata=True) | |
contexts = [] | |
contexts = contexts + [x['metadata']['text'] for x in result['matches']] | |
return contexts | |
def invoke_openai(prompt): | |
sys_prompt = "You are a helpful assistant that always answers questions." | |
# query text-davinci-003 | |
res = client.chat.completions.create( | |
model='gpt-3.5-turbo-0613', | |
messages=[ | |
{"role": "system", "content": sys_prompt}, | |
{"role": "user", "content": prompt} | |
], | |
temperature=0 | |
) | |
return res.choices[0].message.content | |
def build_prompt(message,history): | |
context=generate_context(message) | |
messages=[] | |
prompt=f'Context - {context}\nBased on the above context, answer this question - {message}' | |
print(prompt) | |
return invoke_openai(prompt) | |
iface = gr.ChatInterface(build_prompt, chatbot=gr.Chatbot(height=300), textbox=gr.Textbox(placeholder="Ask me a question", container=False, scale=7), title="Amazon Bedrock and Titan LLM", theme="soft", examples=[ "Who won the best music award?", "Which award did Avatar win?", "Who won the Best Actor award in a supporting role?", "Who is the lyricist for the song Natu Natu from RRR?", "How many awards did the film RRR win?", "Which was the Best International Feature Film?",], cache_examples=False, retry_btn=None, undo_btn="Delete Previous", clear_btn="Clear",) | |
iface.launch(share=True) |