Upload app.py

app.py

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+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import Chroma
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    SystemMessagePromptTemplate,
+    HumanMessagePromptTemplate,
+)
+from langchain.chains import ChatVectorDBChain
+import gradio as gr
+
+# initialize variables
+query = ""
+chat_history = []
+system_template = "You are a helpful assistant. Use the following pieces of context to \
+answer the user's question. {context}"
+temperature = 0
+qa = None
+
+# function called when user submits a question
+def chatbot(input, history=[]):
+    result = qa({"question": input, "chat_history": []})
+    history.append((input, result["answer"]))
+    return history, history
+
+
+# function to set OpenAI key and initalize LangChain chain
+def set_open_ai_key(input):
+    print("Setting OpenAI key to ", input)
+    # os.environ["OPENAI_API_KEY"] = input
+
+    # read in embedddings from vector db store
+    embeddings = OpenAIEmbeddings(openai_api_key=input)
+    vectordb = Chroma(persist_directory="vector_store", embedding_function=embeddings)
+
+    # initialize chatbot message templates
+    messages = [
+        SystemMessagePromptTemplate.from_template(system_template),
+        HumanMessagePromptTemplate.from_template("{question}\Standalone question"),
+    ]
+    prompt = ChatPromptTemplate.from_messages(messages)
+
+    # initialize chatbot chain
+    global qa
+    qa = ChatVectorDBChain.from_llm(
+        ChatOpenAI(temperature=temperature, openai_api_key=input),
+        vectordb,
+        qa_prompt=prompt,
+    )
+
+
+# example questions user can choose from in Gradio UI to test the chatbot
+examples = [
+    "What does Biggie Smalls say about learning from other people's mistakes?",
+    "What can I learn from Megan Quinn about reading?",
+    "What does Scott Belsky say about optimizing what works?",
+    "What is product market fit?",
+    "What is the best way to lower CAC?",
+    "What is the most important competitive advantage a business can have today?",
+]
+
+# initialize Gradio UI using chatbot UI
+gr_interface = gr.Interface(
+    fn=chatbot,
+    inputs=["text", "state"],
+    outputs=["chatbot", "state"],
+    title="TrenBot",
+    description="Q&A Chatbot for Tren Griffin's views on the \
+             market, tech, and everything else",
+    examples=examples,
+    thumbnail="https://i0.wp.com/25iq.com/wp-content/uploads/2012/10/tren_griffin_crop.jpg",
+)
+
+# add OpenAI key textbox to Gradio UI
+with gr_interface:
+    openai_key_textbox = gr.Textbox(
+        lines=1,
+        placeholder="Paste your OpenAI key here and hit Enter.",
+        type="password",
+        label="Your OpenAI Key",
+    )
+    openai_key_textbox.submit(set_open_ai_key, inputs=openai_key_textbox)
+
+# launch Gradio UI
+gr_interface.launch(share=True)