Update app.py

app.py

@@ -6,13 +6,6 @@ from langchain.chains import ConversationChain
 from langchain.llms import OpenAI
 from threading import Lock
 
-from langchain.embeddings.openai import OpenAIEmbeddings
-from langchain.text_splitter import CharacterTextSplitter
-from langchain.vectorstores.faiss import FAISS
-from langchain.docstore.document import Document
-from langchain.chains.question_answering import load_qa_chain
-
-
 
 def load_chain():
     """Logic for loading the chain you want to use should go here."""
@@ -21,36 +14,22 @@ def load_chain():
     return chain
 
 
-def set_openai_api_key(api_key):
+def set_openai_api_key(api_key: str):
     """Set the api key and return chain.
     If no api_key, then None is returned.
     """
-    if api_key and api_key.startswith("sk-") and len(api_key) > 50:
+    if api_key:
         os.environ["OPENAI_API_KEY"] = api_key
-        print("\n\n ++++++++++++++ Setting OpenAI API key ++++++++++++++ \n\n")
-        print(str(datetime.datetime.now()) + ": Before OpenAI, OPENAI_API_KEY length: " + str(
-            len(os.environ["OPENAI_API_KEY"])))
-        llm = OpenAI(temperature=0, max_tokens=MAX_TOKENS)
-        print(str(datetime.datetime.now()) + ": After OpenAI, OPENAI_API_KEY length: " + str(
-            len(os.environ["OPENAI_API_KEY"])))
-        chain, express_chain, memory = load_chain(TOOLS_DEFAULT_LIST, llm)
-
-        # Pertains to question answering functionality
-        embeddings = OpenAIEmbeddings()
-        qa_chain = load_qa_chain(OpenAI(temperature=0), chain_type="stuff")
-
-        print(str(datetime.datetime.now()) + ": After load_chain, OPENAI_API_KEY length: " + str(
-            len(os.environ["OPENAI_API_KEY"])))
+        chain = load_chain()
         os.environ["OPENAI_API_KEY"] = ""
-        return chain, express_chain, llm, embeddings, qa_chain, memory
-    return None, None, None, None, None, None
+        return chain
 
 class ChatWrapper:
 
     def __init__(self):
         self.lock = Lock()
     def __call__(
-        self, api_key: str, inp: str, history: Optional[Tuple[str, str]], chain: Optional[ConversationChain], use_embeddings, monologue:bool
+        self, api_key: str, inp: str, history: Optional[Tuple[str, str]], chain: Optional[ConversationChain]
     ):
         """Execute the chat functionality."""
         self.lock.acquire()
@@ -63,20 +42,6 @@ class ChatWrapper:
             # Set OpenAI key
             import openai
             openai.api_key = api_key
-            if not monologue:
-                if use_embeddings:
-                    if inp and inp.strip() != "":
-                        if docsearch:
-                            docs = docsearch.similarity_search(inp)
-                            output = str(qa_chain.run(input_documents=docs, question=inp))
-                        else:
-                            output, hidden_text = "Please supply some text in the the Embeddings tab.", None
-                    else:
-                        output, hidden_text = "What's on your mind?", None
-                else:
-                    output, hidden_text = run_chain(chain, inp, capture_hidden_text=trace_chain)
-            else:
-                output, hidden_text = inp, None
             # Run chain and append input.
             output = chain.run(input=inp)
             history.append((inp, output))
@@ -86,29 +51,11 @@ class ChatWrapper:
             self.lock.release()
         return history, history
 
-# Pertains to question answering functionality
-def update_embeddings(embeddings_text, embeddings, qa_chain):
-    if embeddings_text:
-        text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
-        texts = text_splitter.split_text(embeddings_text)
-
-        docsearch = FAISS.from_texts(texts, embeddings)
-        print("Embeddings updated")
-        return docsearch
-
-
-# Pertains to question answering functionality
-def update_use_embeddings(widget, state):
-    if widget:
-        state = widget
-        return state
-
 chat = ChatWrapper()
 
 block = gr.Blocks(css=".gradio-container {background-color: lightgray}")
 
-
-with gt.Tab("Chat"):
+with block:
     with gr.Row():
         gr.Markdown("<h3><center>LangChain Demo</center></h3>")
 
@@ -138,20 +85,7 @@ with gt.Tab("Chat"):
         inputs=message,
     )
 
-
-with gr.Tab("Embeddings"):
-        embeddings_text_box = gr.Textbox(label="Enter text for embeddings and hit Create:",
-                                         lines=20)
-
-        with gr.Row():
-            use_embeddings_cb = gr.Checkbox(label="Use embeddings", value=False)
-            use_embeddings_cb.change(update_use_embeddings, inputs=[use_embeddings_cb, use_embeddings_state],
-                                     outputs=[use_embeddings_state])
-
-            embeddings_text_submit = gr.Button(value="Create", variant="secondary").style(full_width=False)
-            embeddings_text_submit.click(update_embeddings,
-                                         inputs=[embeddings_text_box, embeddings_state, qa_chain_state],
-                                         outputs=[docsearch_state])
+    
 
     state = gr.State()
     agent_state = gr.State()