File size: 1,838 Bytes
abc16ec 4919dd7 f8e0bc0 abc16ec ff41237 f8e0bc0 abc16ec |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
import os
from typing import Optional, Tuple
import gradio as gr
import pickle
from query_data import get_chain
from threading import Lock
with open("vectorstore.pkl", "rb") as f:
vectorstore = pickle.load(f)
def set_openai_api_key(api_key: str):
"""Set the api key and return chain.
If no api_key, then None is returned.
"""
if api_key:
os.environ["OPENAI_API_KEY"] = api_key
chain = get_chain(vectorstore)
os.environ["OPENAI_API_KEY"] = ""
return chain
class ChatWrapper:
def __init__(self):
self.lock = Lock()
def __call__(
self, api_key: str, inp: str, history: Optional[Tuple[str, str]], chain
):
"""Execute the chat functionality."""
self.lock.acquire()
try:
history = history or []
# If chain is None, that is because no API key was provided.
if chain is None:
history.append((inp, "Please paste your OpenAI key to use"))
return history, history
# Set OpenAI key
import openai
openai.api_key = api_key
# Run chain and append input.
output = chain({"question": inp, "chat_history": history})["answer"]
history.append((inp, output))
except Exception as e:
raise e
finally:
self.lock.release()
return history, history
def echo(name, request: gr.Request):
if request:
print("Request headers dictionary:", request.headers)
print("IP address:", request.client.host)
print("Body", request.body)
return name
def my_inference_function(name):
return "Hello " + name + "!"
gradio_interface = gr.Interface(
fn = my_inference_function,
inputs = "text",
outputs = "text"
)
gradio_interface.launch()
|