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- Improve annotation algorithm for Youtube (and others)

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- Patch Pytube
- improve OS deletion of files and writing of files
- Start working on Claude
- Improve template management
This commit is contained in:
Josako
2024-07-16 14:21:49 +02:00
parent db44fd3b66
commit 908a2eaf7e
39 changed files with 6427 additions and 324 deletions
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95
config/config.py
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@@ -2,6 +2,8 @@ from os import environ, path
from datetime import timedelta
import redis
from common.utils.prompt_loader import load_prompt_templates
basedir = path.abspath(path.dirname(__file__))
@@ -59,7 +61,18 @@ class Config(object):
# supported LLMs
SUPPORTED_EMBEDDINGS = ['openai.text-embedding-3-small', 'openai.text-embedding-3-large', 'mistral.mistral-embed']
SUPPORTED_LLMS = ['openai.gpt-4o', 'openai.gpt-4-turbo']
SUPPORTED_LLMS = ['openai.gpt-4o', 'anthropic.claude-3-5-sonnet']
ANTHROPIC_LLM_VERSIONS = {'claude-3-5-sonnet': 'claude-3-5-sonnet-20240620', }
# Load prompt templates dynamically
PROMPT_TEMPLATES = {model: load_prompt_templates(model) for model in SUPPORTED_LLMS}
# Annotation text chunk length
ANNOTATION_TEXT_CHUNK_LENGTH = {
'openai.gpt-4o': 10000,
'anthropic.claude-3-5-sonnet': 8000
}
# Celery settings
CELERY_TASK_SERIALIZER = 'json'
@@ -68,83 +81,6 @@ class Config(object):
CELERY_TIMEZONE = 'UTC'
CELERY_ENABLE_UTC = True
# Chunk Definition, Embedding dependent
# OAI_TE3S_MIN_CHUNK_SIZE = 2000
# OAI_TE3S_MAX_CHUNK_SIZE = 3000
# OAI_TE3L_MIN_CHUNK_SIZE = 3000
# OAI_TE3L_MAX_CHUNK_SIZE = 4000
# LLM TEMPLATES
GPT4_HTML_PARSE_TEMPLATE = """You are a top administrative assistant specialized in transforming given HTML into markdown formatted files. The generated files will be used to generate embeddings in a RAG-system.
# Best practices are:
- Respect wordings and language(s) used in the HTML.
- The following items need to be considered: headings, paragraphs, listed items (numbered or not) and tables. Images can be neglected.
- Sub-headers can be used as lists. This is true when a header is followed by a series of sub-headers without content (paragraphs or listed items). Present those sub-headers as a list.
- Be careful of encoding of the text. Everything needs to be human readable.
Process the file carefully, and take a stepped approach. The resulting markdown should be the result of the processing of the complete input html file. Answer with the pure markdown, without any other text.
HTML is between triple backquotes.
```{html}```"""
GPT4_PDF_PARSE_TEMPLATE = """You are a top administrative aid specialized in transforming given PDF-files into markdown formatted files. The generated files will be used to generate embeddings in a RAG-system.
# Best practices are:
- Respect wordings and language(s) used in the PDF.
- The following items need to be considered: headings, paragraphs, listed items (numbered or not) and tables. Images can be neglected.
- When headings are numbered, show the numbering and define the header level.
- A new item is started when a <return> is found before a full line is reached. In order to know the number of characters in a line, please check the document and the context within the document (e.g. an image could limit the number of characters temporarily).
- Paragraphs are to be stripped of newlines so they become easily readable.
- Be careful of encoding of the text. Everything needs to be human readable.
Process the file carefully, and take a stepped approach. The resulting markdown should be the result of the processing of the complete input pdf content. Answer with the pure markdown, without any other text.
PDF content is between triple backquotes.
```{pdf_content}```
"""
GPT4_SUMMARY_TEMPLATE = """Write a concise summary of the text in {language}. The text is delimited between triple backquotes.
```{text}```"""
GPT4_RAG_TEMPLATE = """Answer the question based on the following context, delimited between triple backquotes.
{tenant_context}
Use the following {language} in your communication, and cite the sources used.
If the question cannot be answered using the given context, say "I have insufficient information to answer this question."
Context:
```{context}```
Question:
{question}"""
GPT4_HISTORY_TEMPLATE = """You are a helpful assistant that details a question based on a previous context,
in such a way that the question is understandable without the previous context.
{tenant_context}
The context is a conversation history, with the HUMAN asking questions, the AI answering questions.
The history is delimited between triple backquotes.
You answer by stating the question in {language}.
History:
```{history}```
Question to be detailed:
{question}"""
GPT4_ENCYCLOPEDIA_TEMPLATE = """You have a lot of background knowledge, and as such you are some kind of
'encyclopedia' to explain general terminology. Only answer if you have a clear understanding of the question.
If not, say you do not have sufficient information to answer the question. Use the {language} in your communication.
Question:
{question}"""
GPT4_TRANSCRIPT_TEMPLATE = """You are a transcription editor that improves a given transcript on several parts
and returns markdown. Without changing what people say. The transcript is delimited between triple backquotes.
Do the following:
- divide the transcript into several logical parts. Ensure questions and their answers are in the same logical part.
- annotate the text to identify these logical parts using headings (max 2 levels) in the same language as the transcript.
- improve errors in the transcript given the context, but leave the text intact.
```{transcript}```
"""
# SocketIO settings
# SOCKETIO_ASYNC_MODE = 'threading'
SOCKETIO_ASYNC_MODE = 'gevent'
@@ -212,6 +148,9 @@ class DevConfig(Config):
# Groq API Keys
GROQ_API_KEY = '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'
# Antrhopic API Keys
ANTHROPIC_API_KEY = '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'
# Unstructured settings
UNSTRUCTURED_API_KEY = 'pDgCrXumYhM3CNvjvwV8msMldXC3uw'
UNSTRUCTURED_BASE_URL = 'https://flowitbv-16c4us0m.api.unstructuredapp.io'