initial commit

Dockerfile

@@ -0,0 +1,11 @@
+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["chainlit", "run", "app.py", "--port", "7860"]

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::7sleLdbA",
+            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()

requirements.txt

@@ -0,0 +1,5 @@
+chainlit==0.6.3
+llama_index==0.8.9
+openai==0.27.9
+pypdf
+nltk