crawl4ai/docs/examples/tmp/chainlit_review.py
2024-06-21 17:56:54 +08:00

281 lines
7.7 KiB
Python

from openai import AsyncOpenAI
from chainlit.types import ThreadDict
import chainlit as cl
from chainlit.input_widget import Select, Switch, Slider
client = AsyncOpenAI()
# Instrument the OpenAI client
cl.instrument_openai()
settings = {
"model": "gpt-3.5-turbo",
"temperature": 0.5,
"max_tokens": 500,
"top_p": 1,
"frequency_penalty": 0,
"presence_penalty": 0,
}
@cl.action_callback("action_button")
async def on_action(action: cl.Action):
print("The user clicked on the action button!")
return "Thank you for clicking on the action button!"
@cl.set_chat_profiles
async def chat_profile():
return [
cl.ChatProfile(
name="GPT-3.5",
markdown_description="The underlying LLM model is **GPT-3.5**.",
icon="https://picsum.photos/200",
),
cl.ChatProfile(
name="GPT-4",
markdown_description="The underlying LLM model is **GPT-4**.",
icon="https://picsum.photos/250",
),
]
@cl.on_chat_start
async def on_chat_start():
settings = await cl.ChatSettings(
[
Select(
id="Model",
label="OpenAI - Model",
values=["gpt-3.5-turbo", "gpt-3.5-turbo-16k", "gpt-4", "gpt-4-32k"],
initial_index=0,
),
Switch(id="Streaming", label="OpenAI - Stream Tokens", initial=True),
Slider(
id="Temperature",
label="OpenAI - Temperature",
initial=1,
min=0,
max=2,
step=0.1,
),
Slider(
id="SAI_Steps",
label="Stability AI - Steps",
initial=30,
min=10,
max=150,
step=1,
description="Amount of inference steps performed on image generation.",
),
Slider(
id="SAI_Cfg_Scale",
label="Stability AI - Cfg_Scale",
initial=7,
min=1,
max=35,
step=0.1,
description="Influences how strongly your generation is guided to match your prompt.",
),
Slider(
id="SAI_Width",
label="Stability AI - Image Width",
initial=512,
min=256,
max=2048,
step=64,
tooltip="Measured in pixels",
),
Slider(
id="SAI_Height",
label="Stability AI - Image Height",
initial=512,
min=256,
max=2048,
step=64,
tooltip="Measured in pixels",
),
]
).send()
chat_profile = cl.user_session.get("chat_profile")
await cl.Message(
content=f"starting chat using the {chat_profile} chat profile"
).send()
print("A new chat session has started!")
cl.user_session.set("session", {
"history": [],
"context": []
})
image = cl.Image(url="https://c.tenor.com/uzWDSSLMCmkAAAAd/tenor.gif", name="cat image", display="inline")
# Attach the image to the message
await cl.Message(
content="You are such a good girl, aren't you?!",
elements=[image],
).send()
text_content = "Hello, this is a text element."
elements = [
cl.Text(name="simple_text", content=text_content, display="inline")
]
await cl.Message(
content="Check out this text element!",
elements=elements,
).send()
elements = [
cl.Audio(path="./assets/audio.mp3", display="inline"),
]
await cl.Message(
content="Here is an audio file",
elements=elements,
).send()
await cl.Avatar(
name="Tool 1",
url="https://avatars.githubusercontent.com/u/128686189?s=400&u=a1d1553023f8ea0921fba0debbe92a8c5f840dd9&v=4",
).send()
await cl.Message(
content="This message should not have an avatar!", author="Tool 0"
).send()
await cl.Message(
content="This message should have an avatar!", author="Tool 1"
).send()
elements = [
cl.File(
name="quickstart.py",
path="./quickstart.py",
display="inline",
),
]
await cl.Message(
content="This message has a file element", elements=elements
).send()
# Sending an action button within a chatbot message
actions = [
cl.Action(name="action_button", value="example_value", description="Click me!")
]
await cl.Message(content="Interact with this action button:", actions=actions).send()
# res = await cl.AskActionMessage(
# content="Pick an action!",
# actions=[
# cl.Action(name="continue", value="continue", label="✅ Continue"),
# cl.Action(name="cancel", value="cancel", label="❌ Cancel"),
# ],
# ).send()
# if res and res.get("value") == "continue":
# await cl.Message(
# content="Continue!",
# ).send()
# import plotly.graph_objects as go
# fig = go.Figure(
# data=[go.Bar(y=[2, 1, 3])],
# layout_title_text="An example figure",
# )
# elements = [cl.Plotly(name="chart", figure=fig, display="inline")]
# await cl.Message(content="This message has a chart", elements=elements).send()
# Sending a pdf with the local file path
# elements = [
# cl.Pdf(name="pdf1", display="inline", path="./pdf1.pdf")
# ]
# cl.Message(content="Look at this local pdf!", elements=elements).send()
@cl.on_settings_update
async def setup_agent(settings):
print("on_settings_update", settings)
@cl.on_stop
def on_stop():
print("The user wants to stop the task!")
@cl.on_chat_end
def on_chat_end():
print("The user disconnected!")
@cl.on_chat_resume
async def on_chat_resume(thread: ThreadDict):
print("The user resumed a previous chat session!")
# @cl.on_message
async def on_message(message: cl.Message):
cl.user_session.get("session")["history"].append({
"role": "user",
"content": message.content
})
response = await client.chat.completions.create(
messages=[
{
"content": "You are a helpful bot",
"role": "system"
},
*cl.user_session.get("session")["history"]
],
**settings
)
# Add assitanr message to the history
cl.user_session.get("session")["history"].append({
"role": "assistant",
"content": response.choices[0].message.content
})
# msg.content = response.choices[0].message.content
# await msg.update()
# await cl.Message(content=response.choices[0].message.content).send()
@cl.on_message
async def on_message(message: cl.Message):
cl.user_session.get("session")["history"].append({
"role": "user",
"content": message.content
})
msg = cl.Message(content="")
await msg.send()
stream = await client.chat.completions.create(
messages=[
{
"content": "You are a helpful bot",
"role": "system"
},
*cl.user_session.get("session")["history"]
],
stream = True,
**settings
)
async for part in stream:
if token := part.choices[0].delta.content or "":
await msg.stream_token(token)
# Add assitanr message to the history
cl.user_session.get("session")["history"].append({
"role": "assistant",
"content": msg.content
})
await msg.update()
if __name__ == "__main__":
from chainlit.cli import run_chainlit
run_chainlit(__file__)