initial commit

app.py

@@ -0,0 +1,181 @@
+import os
+from typing import Optional, Tuple
+
+import gradio as gr
+from langchain.llms import OpenAIChat
+from langchain import PromptTemplate
+from langchain.chains import ConversationChain
+from langchain.chains.conversation.memory import ConversationBufferMemory
+from threading import Lock
+
+
+def load_chain():
+    prefix_messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful assistant who is very good at problem solving and thinks step by step. You are about to receive a complex set of instructions to follow for the remainder of the conversation. Good luck!"
+        }
+    ]
+
+    llm = OpenAIChat(model_name="gpt-3.5-turbo-0301", temperature=0.8, prefix_messages=prefix_messages)
+
+    prompt = PromptTemplate(
+        input_variables=['history', 'input'],
+        output_parser=None,
+        template='Current conversation:\n{history}\n\nUser: """""\n{input}"""""\n\nAssistant: ',
+        template_format='f-string'
+    )
+
+    chain = ConversationChain(
+        llm=llm,
+        prompt=prompt,
+        memory=ConversationBufferMemory(human_prefix="User", ai_prefix="Assistant")
+    )
+
+    return chain
+
+
+def load_prompt(prompt_selection: str):
+    """Load the selected initializing prompt."""
+    path = f"prompts/{prompt_selection}/prompt.txt"
+
+    with open(path, "r") as f:
+        init_prompt = f.read()
+        print(f"Loading {path.split('/')[-2]} from: {path}...") # e.g. Loading proposal-gen from: prompts/work/proposal-gen/prompt.txt
+
+    chain = load_chain()
+    chain.predict(input=init_prompt)
+    print(f"Done! Loaded {len(chain.memory.buffer)} characters.")
+    return chain
+
+def fetch_prompts():
+    """Iterates recursively through the prompts directory, returning a list of prompts.
+
+    This is used to populate the dropdown menu in the Gradio interface.
+    """
+    available_prompts = []
+    for root, dirs, files in os.walk("prompts"):
+        if "prompt.txt" in files:
+            available_prompts.append(root.replace("prompts/", "").replace("/prompt.txt", "")) # remove the "prompts/" prefix and the "/prompt.txt" suffix
+            available_prompts.sort()
+            
+    return available_prompts
+
+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:
+        os.environ["OPENAI_API_KEY"] = api_key
+        print("API key set.")
+        # chain = load_chain() # loads the chain.
+        chain = load_prompt(selected_prompt.value)
+        # os.environ["OPENAI_API_KEY"] = ""
+        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]
+    ):
+        """Execute the chat functionality."""
+        self.lock.acquire()
+        try:
+            history = history or []            
+            # If chain is None, that is because no API key was provided.
+            if chain is None:
+                history.append((inp, "Please paste your OpenAI key to use"))
+                return history, history
+            
+            # Set OpenAI key
+            import openai
+            openai.api_key = api_key
+            
+            # Run chain and append input.
+            output = chain.run(input=inp)
+            history.append((inp, output))
+        except Exception as e:
+            raise e
+        finally:
+            self.lock.release()
+        return history, history
+
+chat = ChatWrapper()
+
+block = gr.Blocks(css=".gradio-container {background-color: lightgray}")
+
+with block:
+    with gr.Row():
+        gr.Markdown("<h2><center>PromptLib</center></h2>")
+
+        with gr.Tab('Prompt'):
+
+            selected_prompt = gr.Dropdown(
+                choices=fetch_prompts(),
+                type="value",
+                value="work/proposal-gen",
+                label="Base prompt",
+                interactive=True
+            )
+
+            reload_prompt= gr.Button(
+                value="Reload",
+                variant="secondary"
+            )
+
+        with gr.Tab('API Key'):
+            openai_api_key_textbox = gr.Textbox(
+                placeholder="Paste your OpenAI API key (sk-...)",
+                show_label=False,
+                lines=1,
+                type="password",
+            )
+
+    chatbot = gr.Chatbot()
+
+    with gr.Row():
+        message = gr.Textbox(
+            label="Message",
+            placeholder="What's the answer to life, the universe, and everything?",
+            lines=1,
+        )
+        submit = gr.Button(value="Send", variant="secondary").style(full_width=False)
+
+    gr.Examples(
+        examples=[
+            "What can you do? What command(s) are available?",
+            "Please suggest some sample commands.",
+        ],
+        inputs=message,
+    )
+
+    gr.HTML(
+        "<center>Josh Pazmino | <a href='https://github.com/jmpaz'>GitHub</a> • <a href='https://twitter.com/fjpaz_'>Twitter</a> • <a href='https://linkedin.com/in/fjpazmino'>LinkedIn</a></center>"
+    )
+
+    state = gr.State()
+    agent_state = gr.State()
+
+    submit.click(chat, inputs=[openai_api_key_textbox, message, state, agent_state], outputs=[chatbot, state])
+    message.submit(chat, inputs=[openai_api_key_textbox, message, state, agent_state], outputs=[chatbot, state])
+
+
+    openai_api_key_textbox.change(
+        set_openai_api_key,
+        inputs=[openai_api_key_textbox],
+        outputs=[agent_state],
+    )
+
+    selected_prompt.change(
+        load_prompt,
+        inputs=[selected_prompt],
+        outputs=[agent_state]
+    )
+
+    reload_prompt.click(load_prompt, inputs=[selected_prompt], outputs=[agent_state])
+
+
+block.launch(debug=True)