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Author SHA1 Message Date
NIHART, Jeremi
7774fc2698 fix: pr comments 2023-10-09 10:06:56 +02:00
6d7600e47e
feat: ups deps, add dotenv 2023-10-07 16:55:18 +02:00
0730db5727
feat: package manager 2023-10-07 15:14:18 +02:00
6 changed files with 157 additions and 108 deletions

14
.editorconfig Normal file
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@ -0,0 +1,14 @@
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

4
.gitignore vendored
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@ -1,3 +1,5 @@
.env
/transcripts
/index
/.idea
/.idea
/venv

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@ -9,9 +9,15 @@ Well, let's ask our LLM:
## How to run
### Install dependencies
I have no idea what the correct way to install dependencies with python is. Somehow install these libraries and their dependencies:
- llama_index
- beautifulsoup4
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
```
### Execution
Download transcripts:
```shell
@ -31,6 +37,7 @@ 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?
@ -69,4 +76,4 @@ You can then ask it any questions about Darknet Diaries!
>>The episode also covers a project where Jason was tasked with hacking into a large, worldwide bank. His job was to examine the bank's mobile app for any potential security vulnerabilities that could expose customer or sensitive information. The episode provides a detailed look into the world of penetration testing, highlighting the importance of robust security measures in both physical and digital spaces.
>
> How many downloads does this episode have?
>> Episode 130 of Darknet Diaries, titled "JASON'S PEN TEST", has 667,528 downloads.
>> Episode 130 of Darknet Diaries, titled "JASON'S PEN TEST", has 667,528 downloads.

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@ -5,26 +5,30 @@ import json
folder_path = "transcripts"
if not os.path.exists(folder_path):
os.makedirs(folder_path)
if __name__ == '__main__':
if not os.path.exists(folder_path):
os.makedirs(folder_path)
for i in range(1, 139):
try:
url = f"https://darknetdiaries.com/transcript/{i}"
r = requests.get(url)
soup = BeautifulSoup(r.text, 'html.parser')
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')
transcript = soup.find('pre').get_text()
transcript = soup.find('pre').get_text()
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"]
# 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"]
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}")
# 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}]")

174
main.py
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@ -4,103 +4,109 @@ 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")
llm = OpenAI(model="gpt-4", temperature=0, max_tokens=256)
# 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)
service_context = ServiceContext.from_defaults(llm=llm)
set_global_service_context(service_context)
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)
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)
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)
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}"
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."
)
),
),
]
refine_template = ChatPromptTemplate(chat_refine_msgs)
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_engine = index.as_chat_engine(
text_qa_template=text_qa_template,
refine_template=refine_template,
chat_mode=ChatMode.OPENAI
)
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)
while True:
try:
chat_engine.chat_repl()
except KeyboardInterrupt:
break
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

16
requirements.txt Normal file
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@ -0,0 +1,16 @@
# =====================
# 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
# =====================