forked from phito/darknet_diaries_llm
feat: ups deps, add dotenv
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1
.gitignore
vendored
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.gitignore
vendored
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@ -1,3 +1,4 @@
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.env
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/transcripts
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/index
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/.idea
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@ -5,26 +5,30 @@ import json
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folder_path = "transcripts"
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if not os.path.exists(folder_path):
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os.makedirs(folder_path)
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if __name__ == '__main__':
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if not os.path.exists(folder_path):
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os.makedirs(folder_path)
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for i in range(1, 139):
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try:
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url = f"https://darknetdiaries.com/transcript/{i}"
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r = requests.get(url)
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soup = BeautifulSoup(r.text, 'html.parser')
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for i in range(1, 139):
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try:
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# fetch transcript
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url = f"https://darknetdiaries.com/transcript/{i}"
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r = requests.get(url)
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soup = BeautifulSoup(r.text, 'html.parser')
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transcript = soup.find('pre').get_text()
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transcript = soup.find('pre').get_text()
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url = f"https://api.darknetdiaries.com/{i}.json"
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r = requests.get(url)
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parsed_json = json.loads(r.text)
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title = parsed_json["episode_name"]
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number = parsed_json["episode_number"]
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downloads = parsed_json["total_downloads"]
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# fetch transcript metadata
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url = f"https://api.darknetdiaries.com/{i}.json"
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r = requests.get(url)
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parsed_json = json.loads(r.text)
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title = parsed_json["episode_name"]
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number = parsed_json["episode_number"]
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downloads = parsed_json["total_downloads"]
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with open(f"{folder_path}/episode_{number}.txt", "w") as f:
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f.write(f"{title}\n{downloads}\n{transcript}")
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print(f"{number} {title}")
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except Exception:
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print(f"Failed scraping episode {i}")
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# write transcript
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with open(f"{folder_path}/episode_{number}.txt", "w", encoding='utf-8') as f:
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f.write(f"{title}\n{downloads}\n{transcript}")
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print(f"{number} {title}")
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except Exception as err:
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print(f"Failed scraping episode {i} : [{err}]")
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174
main.py
174
main.py
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@ -6,100 +6,108 @@ from llama_index.llms import OpenAI, ChatMessage, MessageRole
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from llama_index.prompts import ChatPromptTemplate
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# from llama_index import set_global_handler
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from llama_index.chat_engine.types import ChatMode
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from dotenv import load_dotenv
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import os
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import re
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# set_global_handler("simple")
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llm = OpenAI(model="gpt-4", temperature=0, max_tokens=256)
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# load .env
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load_dotenv()
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OPEN_API_KEY = os.getenv('OPEN_API_KEY')
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# config llm context
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llm = OpenAI(model="gpt-4", temperature=0, max_tokens=256, api_key="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")
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service_context = ServiceContext.from_defaults(llm=llm)
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set_global_service_context(service_context)
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if not os.path.exists("./index/lock"):
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documents = []
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for filename in os.listdir("./transcripts"):
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episode_number = re.search(r'\d+', filename).group()
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with open("./transcripts/" + filename, 'r') as f:
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title = f.readline().strip()
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downloads = f.readline().strip()
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content = f.read()
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document = Document(
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text=content,
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doc_id=filename,
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metadata={
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"episode_number": episode_number,
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"episode_title": title,
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"episode_downloads": downloads,
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"episode_url": f"https://darknetdiaries.com/episode/{episode_number}/"
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}
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)
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documents.append(document)
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# TODO split in small functions
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if __name__ == '__main__':
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if not os.path.exists("./index/lock"):
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documents = []
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for filename in os.listdir("./transcripts"):
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episode_number = re.search(r'\d+', filename).group()
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with open("./transcripts/" + filename, 'r') as f:
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title = f.readline().strip()
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downloads = f.readline().strip()
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content = f.read()
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document = Document(
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text=content,
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doc_id=filename,
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metadata={
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"episode_number": episode_number,
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"episode_title": title,
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"episode_downloads": downloads,
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"episode_url": f"https://darknetdiaries.com/episode/{episode_number}/"
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}
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)
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documents.append(document)
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parser = SimpleNodeParser.from_defaults()
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nodes = parser.get_nodes_from_documents(documents)
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parser = SimpleNodeParser.from_defaults()
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nodes = parser.get_nodes_from_documents(documents)
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index = VectorStoreIndex(nodes, show_progress=True)
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index.storage_context.persist(persist_dir="./index")
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open("./index/lock", 'a').close()
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else:
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print("Loading index...")
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storage_context = StorageContext.from_defaults(persist_dir="./index")
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index = load_index_from_storage(storage_context)
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index = VectorStoreIndex(nodes, show_progress=True)
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index.storage_context.persist(persist_dir="./index")
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open("./index/lock", 'a').close()
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else:
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print("Loading index...")
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storage_context = StorageContext.from_defaults(persist_dir="./index")
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index = load_index_from_storage(storage_context)
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chat_text_qa_msgs = [
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ChatMessage(
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role=MessageRole.SYSTEM,
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content=(
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"You have been trained on the Darknet Diaries podcast transcripts with data from october 6 2023."
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"You are an expert about it and will answer as such. You know about every episode up to number 138."
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"Always answer the question, even if the context isn't helpful."
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"Mention the number and title of the episodes you are referring to."
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)
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),
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ChatMessage(
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role=MessageRole.USER,
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content=(
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"Context information is below.\n"
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"---------------------\n"
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"{context_str}\n"
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"---------------------\n"
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"Given the context information and not prior knowledge,"
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"answer the question: {query_str}\n"
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)
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)
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]
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text_qa_template = ChatPromptTemplate(chat_text_qa_msgs)
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chat_refine_msgs = [
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ChatMessage(
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role=MessageRole.SYSTEM,
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content="Always answer the question, even if the context isn't helpful.",
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),
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ChatMessage(
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role=MessageRole.USER,
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content=(
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"We have the opportunity to refine the original answer "
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"(only if needed) with some more context below.\n"
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"------------\n"
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"{context_msg}\n"
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"------------\n"
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"Given the new context, refine the original answer to better "
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"answer the question: {query_str}. "
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"If the context isn't useful, output the original answer again.\n"
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"Original Answer: {existing_answer}"
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chat_text_qa_msgs = [
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ChatMessage(
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role=MessageRole.SYSTEM,
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content=(
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"You have been trained on the Darknet Diaries podcast transcripts with data from october 6 2023."
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"You are an expert about it and will answer as such. You know about every episode up to number 138."
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"Always answer the question, even if the context isn't helpful."
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"Mention the number and title of the episodes you are referring to."
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)
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),
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),
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]
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refine_template = ChatPromptTemplate(chat_refine_msgs)
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ChatMessage(
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role=MessageRole.USER,
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content=(
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"Context information is below.\n"
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"---------------------\n"
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"{context_str}\n"
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"---------------------\n"
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"Given the context information and not prior knowledge,"
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"answer the question: {query_str}\n"
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)
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)
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]
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text_qa_template = ChatPromptTemplate(chat_text_qa_msgs)
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chat_engine = index.as_chat_engine(
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text_qa_template=text_qa_template,
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refine_template=refine_template,
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chat_mode=ChatMode.OPENAI
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)
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chat_refine_msgs = [
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ChatMessage(
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role=MessageRole.SYSTEM,
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content="Always answer the question, even if the context isn't helpful.",
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),
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ChatMessage(
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role=MessageRole.USER,
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content=(
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"We have the opportunity to refine the original answer "
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"(only if needed) with some more context below.\n"
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"------------\n"
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"{context_msg}\n"
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"------------\n"
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"Given the new context, refine the original answer to better "
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"answer the question: {query_str}. "
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"If the context isn't useful, output the original answer again.\n"
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"Original Answer: {existing_answer}"
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),
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),
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]
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refine_template = ChatPromptTemplate(chat_refine_msgs)
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while True:
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try:
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chat_engine.chat_repl()
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except KeyboardInterrupt:
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break
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chat_engine = index.as_chat_engine(
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text_qa_template=text_qa_template,
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refine_template=refine_template,
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chat_mode=ChatMode.OPENAI
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)
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while True:
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try:
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chat_engine.chat_repl()
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except KeyboardInterrupt:
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break
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@ -1,8 +1,15 @@
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# =====================
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# Required dependencies
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# =====================
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llama-index==0.8.*
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beautifulsoup4==4.12.*
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# general deps
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requests~=2.31.0
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llama-index~=0.8.40
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beautifulsoup4~=4.12.2
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python-dotenv~=1.0.0
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# llama sub deps
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transformers~=4.34.0
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torch~=2.1.0
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# =====================
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# Development dependencies
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