launch app

README.md

@@ -1,7 +1,7 @@
 ---
 title: Chat Ai Safety
 emoji: 📚
-colorFrom: gray
+colorFrom: grey
 colorTo: pink
 sdk: gradio
 sdk_version: 3.28.3

app.py

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+# gradio imports
+import gradio as gr
+import os
+import time
+
+# Imports
+import os
+
+import openai
+from langchain.chains import ConversationalRetrievalChain
+
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.chat_models import ChatOpenAI
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.vectorstores import Chroma
+from langchain.document_loaders import TextLoader
+
+from langchain.memory import ConversationBufferMemory
+from langchain.chat_models import ChatOpenAI
+
+css="""
+#col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
+"""
+
+title = """
+<div style="text-align: center;max-width: 700px;">
+    <h1>Chat with Jonny's views on AI • AI Safety</h1>
+    <p style="text-align: left;">Chat is built from:<br />
+    This is a Dialogue (https://www.jonnyjohnson.com/this-is-a-dialogue)<br />
+    Game-Making articles (https://dialogues-ai.github.io/papers/docs/ai_regulation/gamemaking)<br />
+    As well as 25 blog posts contributed to BMC <br />
+</div>
+"""
+
+
+prompt_hints = """
+<div style="text-align: center;max-width: 700px;">
+    <p style="text-align: left;">Some things you can ask:<br />
+    Should I be worried about AIs?<br />
+    How do we improve the games between AIs and humans?<br />
+    What are the risks associated with AI? <br />
+    Do you agree that everything is language? <br />
+</div>
+"""
+
+# from index import PERSIST_DIRECTORY, CalendarIndex
+PERSIST_DIRECTORY = "chromadb"
+# Create embeddings
+
+# # create memory object
+from langchain.memory import ConversationBufferMemory
+memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
+
+def loading_pdf():
+    return "Loading..."
+
+def loading_database(open_ai_key):
+    if open_ai_key is not None:
+        if os.path.exists(PERSIST_DIRECTORY):
+            os.environ['OPENAI_API_KEY'] = open_ai_key
+            print("Loading from persisted dir")
+            embeddings = OpenAIEmbeddings()
+            docs_retriever = Chroma(persist_directory=PERSIST_DIRECTORY, embedding_function=embeddings)
+
+            global qa_chain
+            qa_chain = ConversationalRetrievalChain.from_llm(ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0.0),  
+                         
+                            retriever=docs_retriever.as_retriever(), 
+                            memory=memory, 
+                            return_source_documents=False
+                            )
+            return "Ready"
+    else:
+        return "You forgot OpenAI API key"
+
+def add_text(history, text):
+    history = history + [(text, None)]
+    return history, ""
+
+
+def bot(history):
+    response = infer(history[-1][0], history)
+    history[-1][1] = ""
+    for character in response:     
+        history[-1][1] += character
+        time.sleep(0.05)
+        yield history
+    
+
+def infer(question, history):
+    res = []
+    for human, ai in history[:-1]:
+        pair = (human, ai)
+        res.append(pair)
+    
+    chat_history = res
+    query = question
+    result = qa_chain({"question": query, "chat_history": chat_history})
+    return result["answer"]
+
+def update_message(question_component, chat_prompts):
+    question_component.value = chat_prompts.get_name()
+    return None
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.HTML(title)
+        with gr.Column():
+            with gr.Row():
+                openai_key = gr.Textbox(label="OpenAI API key", type="password")
+                submit_api_key = gr.Button("Submit")
+            with gr.Row():
+                langchain_status = gr.Textbox(label="Status", placeholder="", interactive=False)
+        
+        chatbot = gr.Chatbot([], elem_id="chatbot").style(height=350)
+        question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter ")
+        submit_btn = gr.Button("Send Message")
+        gr.HTML(prompt_hints)
+        
+    submit_api_key.click(loading_database, inputs=[openai_key], outputs=[langchain_status], queue=False)
+    # demo.load(loading_database, None, langchain_status)
+    question.submit(add_text, [chatbot, question], [chatbot, question]).then(
+        bot, chatbot, chatbot
+    )
+    submit_btn.click(add_text, [chatbot, question], [chatbot, question]).then(
+        bot, chatbot, chatbot)
+
+demo.queue(concurrency_count=2, max_size=20).launch()

chromadb/chroma-collections.parquet

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chromadb/chroma-embeddings.parquet

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chromadb/index/index_56718c26-0f35-40cf-b992-9f14e3ab54f1.bin

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requirements.txt

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+openai
+tiktoken
+chromadb
+langchain