completed

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.pdf filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,13 +1,19 @@
----
-title: Ask GalacticHitchHikers With FineTunedGPT Using LlamaIndex
-emoji: 👀
-colorFrom: red
-colorTo: red
-sdk: streamlit
-sdk_version: 1.26.0
-app_file: app.py
-pinned: false
-license: bigscience-openrail-m
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Building A Finetuning Machine Using Chainlit
+
+Today we'll take a look at how we can wrap our finetuning process into Chainlit and have our own dynamic fine-tuning machine. 
+
+We'll be leveraging [this](https://github.com/AI-Maker-Space/LLM-Ops-Cohort-1/blob/main/Week%202/Thursday/Automated%20Fine-tuning%20with%20LLamaIndex.ipynb) notebook for finetuning.
+
+Find worked-out notebook at this [repo](https://github.com/PanoEvJ/LLMOps/tree/main/Week%202/Thursday).
+
+# Build 🏗️
+There are 2 main tasks for this assignment:
+
+- Verify you can run the notebook
+- Wrap the notebook using Chainlit
+
+# Ship 🚢
+Construct a Chainlit application using the notebook that allows users to interface with the application.
+
+# Share 🚀
+Make a social media post about your final application and tag @AIMakerspace

app.py

@@ -0,0 +1,68 @@
+import os
+import openai
+
+from llama_index.query_engine.retriever_query_engine import RetrieverQueryEngine
+from llama_index.callbacks.base import CallbackManager
+from llama_index import (
+    LLMPredictor,
+    ServiceContext,
+    StorageContext,
+    load_index_from_storage,
+)
+from llama_index.llms import OpenAI
+import chainlit as cl
+
+
+openai.api_key = os.environ.get("OPENAI_API_KEY")
+
+try:
+    # rebuild storage context
+    storage_context = StorageContext.from_defaults(persist_dir="./storage")
+    # load index
+    index = load_index_from_storage(storage_context)
+except:
+    from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader
+
+    documents = SimpleDirectoryReader(input_files=["hitchhikers.pdf"]).load_data()
+    index = GPTVectorStoreIndex.from_documents(documents)
+    index.storage_context.persist()
+
+
+@cl.on_chat_start
+async def factory():
+    llm_predictor = LLMPredictor(
+        llm=OpenAI(
+            temperature=0,
+            model="ft:gpt-3.5-turbo-0613:personal::7rG4voK4",
+            streaming=True,
+            context_window=2048,
+        ),
+    )
+    service_context = ServiceContext.from_defaults(
+        llm_predictor=llm_predictor,
+        chunk_size=512,
+        callback_manager=CallbackManager([cl.LlamaIndexCallbackHandler()]),
+    )
+
+    query_engine = index.as_query_engine(
+        service_context=service_context,
+        streaming=True,
+    )
+
+    cl.user_session.set("query_engine", query_engine)
+
+
+@cl.on_message
+async def main(message):
+    query_engine = cl.user_session.get("query_engine")  # type: RetrieverQueryEngine
+    response = await cl.make_async(query_engine.query)(message)
+
+    response_message = cl.Message(content="")
+
+    for token in response.response_gen:
+        await response_message.stream_token(token=token)
+
+    if response.response_txt:
+        response_message.content = response.response_txt
+
+    await response_message.send()

chainlit.md

@@ -0,0 +1,14 @@
+# Welcome to Chainlit! 🚀🤖
+
+Hi there, Developer! 👋 We're excited to have you on board. Chainlit is a powerful tool designed to help you prototype, debug and share applications built on top of LLMs.
+
+## Useful Links 🔗
+
+- **Documentation:** Get started with our comprehensive [Chainlit Documentation](https://docs.chainlit.io) 📚
+- **Discord Community:** Join our friendly [Chainlit Discord](https://discord.gg/ZThrUxbAYw) to ask questions, share your projects, and connect with other developers! 💬
+
+We can't wait to see what you create with Chainlit! Happy coding! 💻😊
+
+## Welcome screen
+
+To modify the welcome screen, edit the `chainlit.md` file at the root of your project. If you do not want a welcome screen, just leave this file empty.

hitchhikers.pdf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fbf013abdefb5a9f2bccd3f7345467712213d4f247ce29846045056e8cf603c1
+size 3402125

requirements.txt

@@ -0,0 +1,3 @@
+chainlit==0.6.3
+llama_index==0.8.9
+openai==0.27.9