Spaces:
Build error
Build error
File size: 4,336 Bytes
f51bb92 8f6647c f51bb92 f2daaee f51bb92 8f6647c f51bb92 8f6647c f51bb92 8f6647c f51bb92 8f6647c f51bb92 8f6647c f51bb92 f2daaee f51bb92 |
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 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 |
from modules.config.constants import *
import chainlit as cl
from langchain_core.prompts import PromptTemplate
def get_sources(res, answer, view_sources=False):
source_elements = []
source_dict = {} # Dictionary to store URL elements
for idx, source in enumerate(res["source_documents"]):
source_metadata = source.metadata
url = source_metadata.get("source", "N/A")
score = source_metadata.get("score", "N/A")
page = source_metadata.get("page", 1)
lecture_tldr = source_metadata.get("tldr", "N/A")
lecture_recording = source_metadata.get("lecture_recording", "N/A")
suggested_readings = source_metadata.get("suggested_readings", "N/A")
date = source_metadata.get("date", "N/A")
source_type = source_metadata.get("source_type", "N/A")
url_name = f"{url}_{page}"
if url_name not in source_dict:
source_dict[url_name] = {
"text": source.page_content,
"url": url,
"score": score,
"page": page,
"lecture_tldr": lecture_tldr,
"lecture_recording": lecture_recording,
"suggested_readings": suggested_readings,
"date": date,
"source_type": source_type,
}
else:
source_dict[url_name]["text"] += f"\n\n{source.page_content}"
# First, display the answer
full_answer = "**Answer:**\n"
full_answer += answer
if view_sources:
# Then, display the sources
full_answer += "\n\n**Sources:**\n"
for idx, (url_name, source_data) in enumerate(source_dict.items()):
full_answer += f"\nSource {idx + 1} (Score: {source_data['score']}): {source_data['url']}\n"
name = f"Source {idx + 1} Text\n"
full_answer += name
source_elements.append(
cl.Text(name=name, content=source_data["text"], display="side")
)
# Add a PDF element if the source is a PDF file
if source_data["url"].lower().endswith(".pdf"):
name = f"Source {idx + 1} PDF\n"
full_answer += name
pdf_url = f"{source_data['url']}#page={source_data['page']+1}"
source_elements.append(cl.Pdf(name=name, url=pdf_url, display="side"))
full_answer += "\n**Metadata:**\n"
for idx, (url_name, source_data) in enumerate(source_dict.items()):
full_answer += f"\nSource {idx + 1} Metadata:\n"
source_elements.append(
cl.Text(
name=f"Source {idx + 1} Metadata",
content=f"Source: {source_data['url']}\n"
f"Page: {source_data['page']}\n"
f"Type: {source_data['source_type']}\n"
f"Date: {source_data['date']}\n"
f"TL;DR: {source_data['lecture_tldr']}\n"
f"Lecture Recording: {source_data['lecture_recording']}\n"
f"Suggested Readings: {source_data['suggested_readings']}\n",
display="side",
)
)
return full_answer, source_elements, source_dict
def get_prompt(config):
if config["llm_params"]["use_history"]:
if config["llm_params"]["llm_loader"] == "local_llm":
custom_prompt_template = tinyllama_prompt_template_with_history
elif config["llm_params"]["llm_loader"] == "openai":
custom_prompt_template = openai_prompt_template_with_history
# else:
# custom_prompt_template = tinyllama_prompt_template_with_history # default
prompt = PromptTemplate(
template=custom_prompt_template,
input_variables=["context", "chat_history", "question"],
)
else:
if config["llm_params"]["llm_loader"] == "local_llm":
custom_prompt_template = tinyllama_prompt_template
elif config["llm_params"]["llm_loader"] == "openai":
custom_prompt_template = openai_prompt_template
# else:
# custom_prompt_template = tinyllama_prompt_template
prompt = PromptTemplate(
template=custom_prompt_template,
input_variables=["context", "question"],
)
return prompt
|