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14
.editorconfig
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@ -1,14 +0,0 @@
root = true
[*]
charset = utf-8
end_of_line = lf
indent_size = 4
indent_style = space
insert_final_newline = true
trim_trailing_whitespace = true
max_line_length = 120
[*.md]
trim_trailing_whitespace = false
max_line_length = 0

2
.gitignore vendored
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@ -1,5 +1,3 @@
.env
/transcripts
/index
/.idea
/venv

13
README.md → README.MD
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@ -9,15 +9,9 @@ Well, let's ask our LLM:
## How to run
### Install dependencies
It is recommended to use a python version greater than or equal to ``3.10.0``.
Another stuff recommended, is to create a venv or use an IDE that supports venv creation, so all dependencies are installed locally to the project and not globally. If not, you can use https://virtualenv.pypa.io/en/latest/ to artificially create isolated environments.
Install the dependencies required to run the project by running the following command at the project root :
```shell
pip install -r requirements.txt
```
I have no idea what the correct way to install dependencies with python is. Somehow install these libraries and their dependencies:
- llama_index
- beautifulsoup4
### Execution
Download transcripts:
```shell
@ -37,7 +31,6 @@ python3 main.py
On the first run, it will generate the index. This can take a while, but it will be cached on disk for the next runs.
You can then ask it any questions about Darknet Diaries!
## Examples
> What is the intro of the podcast?

42
download_transcripts.py
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@ -5,30 +5,26 @@ import json
folder_path = "transcripts"
if __name__ == '__main__':
if not os.path.exists(folder_path):
os.makedirs(folder_path)
if not os.path.exists(folder_path):
os.makedirs(folder_path)
for i in range(1, 139):
try:
# fetch transcript
url = f"https://darknetdiaries.com/transcript/{i}"
r = requests.get(url)
soup = BeautifulSoup(r.text, 'html.parser')
for i in range(1, 139):
try:
url = f"https://darknetdiaries.com/transcript/{i}"
r = requests.get(url)
soup = BeautifulSoup(r.text, 'html.parser')
transcript = soup.find('pre').get_text()
transcript = soup.find('pre').get_text()
# fetch transcript metadata
url = f"https://api.darknetdiaries.com/{i}.json"
r = requests.get(url)
parsed_json = json.loads(r.text)
title = parsed_json["episode_name"]
number = parsed_json["episode_number"]
downloads = parsed_json["total_downloads"]
url = f"https://api.darknetdiaries.com/{i}.json"
r = requests.get(url)
parsed_json = json.loads(r.text)
title = parsed_json["episode_name"]
number = parsed_json["episode_number"]
downloads = parsed_json["total_downloads"]
# write transcript
with open(f"{folder_path}/episode_{number}.txt", "w", encoding='utf-8') as f:
f.write(f"{title}\n{downloads}\n{transcript}")
print(f"{number} {title}")
except Exception as err:
print(f"Failed scraping episode {i} : [{err}]")
with open(f"{folder_path}/episode_{number}.txt", "w") as f:
f.write(f"{title}\n{downloads}\n{transcript}")
print(f"{number} {title}")
except Exception:
print(f"Failed scraping episode {i}")

178
main.py
View File

@ -4,109 +4,103 @@ from llama_index.node_parser import SimpleNodeParser
from llama_index import VectorStoreIndex
from llama_index.llms import OpenAI, ChatMessage, MessageRole
from llama_index.prompts import ChatPromptTemplate
# from llama_index import set_global_handler
from llama_index import set_global_handler
from llama_index.chat_engine.types import ChatMode
from dotenv import load_dotenv
import os
import re
# set_global_handler("simple")
# load .env
load_dotenv()
OPEN_API_KEY = os.getenv('OPEN_API_KEY')
# config llm context
llm = OpenAI(model="gpt-4", temperature=0, max_tokens=256, api_key=OPEN_API_KEY)
llm = OpenAI(model="gpt-4", temperature=0, max_tokens=256)
service_context = ServiceContext.from_defaults(llm=llm)
set_global_service_context(service_context)
if __name__ == '__main__':
if not os.path.exists("./index/lock"):
documents = []
for filename in os.listdir("./transcripts"):
episode_number = re.search(r'\d+', filename).group()
with open("./transcripts/" + filename, 'r') as f:
title = f.readline().strip()
downloads = f.readline().strip()
content = f.read()
document = Document(
text=content,
doc_id=filename,
metadata={
"episode_number": episode_number,
"episode_title": title,
"episode_downloads": downloads,
"episode_url": f"https://darknetdiaries.com/episode/{episode_number}/"
}
)
documents.append(document)
parser = SimpleNodeParser.from_defaults()
nodes = parser.get_nodes_from_documents(documents)
index = VectorStoreIndex(nodes, show_progress=True)
index.storage_context.persist(persist_dir="./index")
open("./index/lock", 'a').close()
else:
print("Loading index...")
storage_context = StorageContext.from_defaults(persist_dir="./index")
index = load_index_from_storage(storage_context)
chat_text_qa_msgs = [
ChatMessage(
role=MessageRole.SYSTEM,
content=(
"You have been trained on the Darknet Diaries podcast transcripts with data from october 6 2023."
"You are an expert about it and will answer as such. You know about every episode up to number 138."
"Always answer the question, even if the context isn't helpful."
"Mention the number and title of the episodes you are referring to."
)
),
ChatMessage(
role=MessageRole.USER,
content=(
"Context information is below.\n"
"---------------------\n"
"{context_str}\n"
"---------------------\n"
"Given the context information and not prior knowledge,"
"answer the question: {query_str}\n"
)
if not os.path.exists("./index/lock"):
documents = []
for filename in os.listdir("./transcripts"):
episode_number = re.search(r'\d+', filename).group()
with open("./transcripts/" + filename, 'r') as f:
title = f.readline().strip()
downloads = f.readline().strip()
content = f.read()
document = Document(
text=content,
doc_id=filename,
metadata={
"episode_number": episode_number,
"episode_title": title,
"episode_downloads": downloads,
"episode_url": f"https://darknetdiaries.com/episode/{episode_number}/"
}
)
]
text_qa_template = ChatPromptTemplate(chat_text_qa_msgs)
documents.append(document)
chat_refine_msgs = [
ChatMessage(
role=MessageRole.SYSTEM,
content="Always answer the question, even if the context isn't helpful.",
),
ChatMessage(
role=MessageRole.USER,
content=(
"We have the opportunity to refine the original answer "
"(only if needed) with some more context below.\n"
"------------\n"
"{context_msg}\n"
"------------\n"
"Given the new context, refine the original answer to better "
"answer the question: {query_str}. "
"If the context isn't useful, output the original answer again.\n"
"Original Answer: {existing_answer}"
),
),
]
refine_template = ChatPromptTemplate(chat_refine_msgs)
parser = SimpleNodeParser.from_defaults()
nodes = parser.get_nodes_from_documents(documents)
chat_engine = index.as_chat_engine(
text_qa_template=text_qa_template,
refine_template=refine_template,
chat_mode=ChatMode.OPENAI
index = VectorStoreIndex(nodes, show_progress=True)
index.storage_context.persist(persist_dir="./index")
open("./index/lock", 'a').close()
else:
print("Loading index...")
storage_context = StorageContext.from_defaults(persist_dir="./index")
index = load_index_from_storage(storage_context)
chat_text_qa_msgs = [
ChatMessage(
role=MessageRole.SYSTEM,
content=(
"You have been trained on the Darknet Diaries podcast transcripts with data from october 6 2023."
"You are an expert about it and will answer as such. You know about every episode up to number 138."
"Always answer the question, even if the context isn't helpful."
"Mention the number and title of the episodes you are referring to."
)
),
ChatMessage(
role=MessageRole.USER,
content=(
"Context information is below.\n"
"---------------------\n"
"{context_str}\n"
"---------------------\n"
"Given the context information and not prior knowledge,"
"answer the question: {query_str}\n"
)
)
]
text_qa_template = ChatPromptTemplate(chat_text_qa_msgs)
chat_refine_msgs = [
ChatMessage(
role=MessageRole.SYSTEM,
content="Always answer the question, even if the context isn't helpful.",
),
ChatMessage(
role=MessageRole.USER,
content=(
"We have the opportunity to refine the original answer "
"(only if needed) with some more context below.\n"
"------------\n"
"{context_msg}\n"
"------------\n"
"Given the new context, refine the original answer to better "
"answer the question: {query_str}. "
"If the context isn't useful, output the original answer again.\n"
"Original Answer: {existing_answer}"
),
),
]
refine_template = ChatPromptTemplate(chat_refine_msgs)
chat_engine = index.as_chat_engine(
text_qa_template=text_qa_template,
refine_template=refine_template,
chat_mode=ChatMode.OPENAI
)
while True:
try:
chat_engine.chat_repl()
except KeyboardInterrupt:
break
while True:
try:
chat_engine.chat_repl()
except KeyboardInterrupt:
break

16
requirements.txt
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@ -1,16 +0,0 @@
# =====================
# Required dependencies
# =====================
# general deps
requests~=2.31.0
llama-index~=0.8.40
beautifulsoup4~=4.12.2
python-dotenv~=1.0.0
# llama sub deps
transformers~=4.34.0
torch~=2.1.0
# =====================
# Development dependencies
# =====================