Spaces:
Sleeping
Sleeping
import sys | |
sys.path.append(".") | |
import chainlit as cl | |
from langchain.prompts.chat import ( | |
ChatPromptTemplate, | |
SystemMessagePromptTemplate, | |
HumanMessagePromptTemplate, | |
) | |
from roaringkitty import roaringkiity_chain | |
system_template = """ | |
Use the following pieces of context to answer the user's question. | |
Please respond as if you are "RoaringKitty" a Youtuber known for detailed posts and videos on social media platforms like Reddit (particularly the WallStreetBets subreddit) and YouTube, where he shared his investment strategies and analysis . | |
If you don't know the answer, just say that you don't know, don't try to make up an answer. | |
You can make inferences based on the context as long as it still faithfully represents the feedback. | |
Example of your response should be: | |
``` | |
The answer is foo | |
``` | |
Begin! | |
---------------- | |
{context}""" | |
messages = [ | |
SystemMessagePromptTemplate.from_template(system_template), | |
HumanMessagePromptTemplate.from_template("{question}"), | |
] | |
prompt = ChatPromptTemplate(messages=messages) | |
chain_type_kwargs = {"prompt": prompt} | |
def rename(orig_author: str): | |
diamond_char = u'\U0001F537' | |
phrase = diamond_char + " Diamond Hands " + diamond_char | |
rename_dict = {"RetrievalQA": phrase} | |
return rename_dict.get(orig_author, orig_author) | |
async def init(): | |
msg = cl.Message(content=f"Building Index...") | |
await msg.send() | |
chain = await roaringkiity_chain(prompt) | |
msg.content = f"Index built!" | |
await msg.send() | |
cl.user_session.set("chain", chain) | |
async def main(message): | |
chain = cl.user_session.get("chain") | |
cb = cl.AsyncLangchainCallbackHandler( | |
stream_final_answer=False, answer_prefix_tokens=["FINAL", "ANSWER"] | |
) | |
cb.answer_reached = True | |
res = await chain.acall(message.content, callbacks=[cb], ) | |
answer = res["result"] | |
source_elements = [] | |
visited_sources = set() | |
# Get the documents from the user session | |
docs = res["source_documents"] | |
metadatas = [doc.metadata for doc in docs] | |
all_sources = [m["source"] for m in metadatas] | |
for source in all_sources: | |
if source in visited_sources: | |
continue | |
visited_sources.add(source) | |
# Create the text element referenced in the message | |
source_elements.append( | |
cl.Text(content="https://www.youtube.com/watch?" + source, name="Link to Video") | |
) | |
if source_elements: | |
answer += f"\nSources: {', '.join([e.content.decode('utf-8') for e in source_elements])}" | |
else: | |
answer += "\nNo sources found" | |
await cl.Message(content=answer, elements=source_elements).send() | |