Created
April 23, 2024 10:06
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from core.inference.huggingface import InferWithHuggingface | |
from core.readers.github import ReadGithubIssue | |
from core.inference.llama3instruct import InferWithLlama3Instruct | |
from core.transforms.github import GithubIssueToChat | |
from core.writers.dlt import WriteFile | |
import os | |
# Get the Huggingface token | |
HF_TOKEN = os.getenv("HF_TOKEN") | |
# Create a Github reader action that will read from Github and store in memory (readitems attributes of the class) | |
# This reader will read the main issue and all comments for a specific issue number | |
read_issue = ReadGithubIssue() | |
read_issue(repo_owner="dlt-hub", repo="dlt", issue_number=933) | |
issues= read_issue.readitems['issues'] | |
comments = read_issue.readitems['comments'] | |
# Start building inputs into an LLM. Issues and comments get converted into a chat-like thread | |
# Each message in the chat are tagged with one of 3 roles: system, assistant, user | |
# The first message is by 'system' and instructs our LLM how to behave | |
messages = [] | |
messages.append({"role": "system", "content": "You are a coding assistant that answers user questions posted to GitHub!"}) | |
# Now convert all comments from Github that we read earlier | |
convert_gh_issue = GithubIssueToChat() | |
chat = convert_gh_issue(issues=issues,comments = comments) | |
messages.extend(chat) | |
# Pass this chat message list to the Llama3 model and get a response | |
infer_with_llama3 = InferWithLlama3Instruct(HF_TOKEN, device="mps") | |
response = infer_with_llama3(messages) | |
# Check that our response is safe to use at work. | |
# Generate an NSFW score using a model on Huggingface | |
filter_nsfw = InferWithHuggingface( | |
task="text-classification", model="michellejieli/NSFW_text_classifier", device="mps") | |
nsfw_score = filter_nsfw(response)[0] | |
# Start preparing outputs. | |
response_message = {"role": "assistant", "content":response} | |
response_message = {**response_message, **nsfw_score} | |
messages.append(response_message) | |
# Write the last response and the full chat to local files | |
write_last_response = WriteFile( | |
"github_bot", bucket_url="file://gh_bot_last_response") | |
write_last_response([response_message],loader_file_format="jsonl") | |
write_full_chat = WriteFile( | |
"github_bot", bucket_url="file://gh_bot_full_chat") | |
write_full_chat(messages,loader_file_format="jsonl") | |
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