first commit

.gitattributes

@@ -32,3 +32,4 @@ 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
+apple_amazon_intel_db/* filter=lfs diff=lfs merge=lfs -text

Dockerfile

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+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+RUN useradd -m -u 1000 user
+
+USER user
+
+ENV HOME=/home/user \
+	PATH=/home/user/.local/bin:$PATH
+
+WORKDIR $HOME/app
+
+COPY --chown=user . $HOME/app
+
+CMD ["python", "bot.py"]

apple_amazon_intel_db/chroma-collections.parquet

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apple_amazon_intel_db/chroma-embeddings.parquet

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apple_amazon_intel_db/index/id_to_uuid_8f095a90-6d97-4fdf-9d51-9b5f73967d45.pkl

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apple_amazon_intel_db/index/index_8f095a90-6d97-4fdf-9d51-9b5f73967d45.bin

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apple_amazon_intel_db/index/index_metadata_8f095a90-6d97-4fdf-9d51-9b5f73967d45.pkl

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apple_amazon_intel_db/index/uuid_to_id_8f095a90-6d97-4fdf-9d51-9b5f73967d45.pkl

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bot.py

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+import gradio as gr
+import os
+import time
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import FAISS, Chroma
+from langchain.chat_models.openai import ChatOpenAI
+from langchain.chains import ConversationalRetrievalChain
+from langchain.memory import ConversationBufferWindowMemory
+
+# RetrievalQAWithSourcesChain.from_llm()
+# ConversationalRetrievalChain()
+
+
+# os.environ["OPENAI_API_KEY"] = "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"
+print(os.environ.get("OPENAI_API_KEY"))
+persist_direcory = "apple_amazon_intel_db"
+# persist_directory = "db"
+
+embeddings = OpenAIEmbeddings()
+# db = FAISS.load_local(persist_directory, embeddings)
+chroma = Chroma(embedding_function=embeddings, persist_directory=persist_direcory)
+retriever = chroma.as_retriever(search_type="mmr", search_kwargs={"k": 10})
+
+memory = ConversationBufferWindowMemory(
+    memory_key="chat_history", return_messages=False
+)
+
+qa = ConversationalRetrievalChain.from_llm(
+    llm=ChatOpenAI(model_name="gpt-4", temperature=0, streaming=True),
+    chain_type="stuff",
+    retriever=retriever,
+    memory=memory,
+    get_chat_history=lambda h: h,
+    verbose=True,
+    # return_source_documents=True,
+)
+
+# res = qa({"question": "what is AD790?", "chat_history": []})
+# print(res["answer"])
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox()
+    clear = gr.Button("clear")
+
+    def user(user_message, history):
+        return "", history + [[user_message, None]]
+
+    def bot(history):
+        bot_message = qa.run({"question": history[-1][0], "chat_history": history[:-1]})
+        history[-1][1] = ""
+        for character in bot_message:
+            history[-1][1] += character
+            time.sleep(0.05)
+            yield history
+
+    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
+        bot, chatbot, chatbot
+    )
+    clear.click(lambda: None, None, chatbot, queue=False)
+
+demo.queue()
+demo.launch(share=False, server_name="0.0.0.0")
+"""
+Total net revenues of approximately $14.6 billion was up 6.1% on an
+operational basis
+
+what was the net revenue during the quarter?
+The net revenue during the quarter was $14.6 billion.
+how much did it increase percentage on opeational basis?
+The percentage increase in net revenue on an operational basis during the quarter was 6.1%.
+what was the 2022 adjusted earnings per share guidance ?
+"""