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import gradio as gr
from huggingface_hub import InferenceClient
from langchain_community.chat_models import ChatOllama
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
# client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
model_name="llama3-8b",
api_key=None
):
client = ChatOllama(
model=model_name,
base_url="https://lintasmediadanawa-hf-llm-api.hf.space",
headers={"Authorization": f"Bearer {api_key}"},
temperature=temperature,
top_p=top_p,
max_tokens=max_tokens
)
messages = [("system", system_message)]
for val in history:
if val[0]:
# messages.append({"role": "user", "content": val[0]})
messages.append(("human", val[0]))
if val[1]:
# messages.append({"role": "assistant", "content": val[1]})
messages.append(("ai", val[1]))
# messages.append({"role": "user", "content": message})
messages.append(("user", message))
chain = ChatPromptTemplate.from_messages(messages) | ChatOllama | StrOutputParser()
return chain.invoke()
# response = ""
# for message in client.chat_completion(
# messages,
# max_tokens=max_tokens,
# stream=True,
# temperature=temperature,
# top_p=top_p,
# ):
# token = message.choices[0].delta.content
# response += token
# yield response
"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
),
gr.Textbox(value="llama3-8b", label="Available Model Name, please refer to https://lintasmediadanawa-hf-llm-api.hf.space/api/tags"),
gr.Textbox(value="hf_xxx", label="Huggingface API key")
],
)
if __name__ == "__main__":
demo.launch() |