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Create app.py
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app.py
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"""
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Chat engine.
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TODOs:
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- Better prompts.
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- Output reader / parser.
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- Agents for evaluation and task planning / splitting.
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* Haystack for orchestration
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- Tools for agents
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* Haystack for orchestration
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-
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"""
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client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
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def query_submit(user_message, history):
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return "", history + [[user_message, None]]
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def format_prompt(query, history, lookback):
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prompt = "Responses should be no more than 100 words long.\n"
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for previous_query, prevous_completion in history[-lookback:]:
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prompt += f"<s>[INST] {previous_query} [/INST] {prevous_completion}</s> "
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prompt += f"[INST] {query} [/INST]"
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return prompt
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def query_completion(
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query,
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history,
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lookback = 3,
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max_new_tokens = 256,
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):
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generateKwargs = dict(
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max_new_tokens = max_new_tokens,
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seed = 1337,
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)
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formatted_query = format_prompt(query, history, lookback)
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stream = client.text_generation(
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formatted_query,
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**generateKwargs,
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stream = True,
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details = True,
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return_full_text = False
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)
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history[-1][1] = ""
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for response in stream:
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history[-1][1] += response.token.text
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yield history
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"""
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Chat UI using Gradio Blocks.
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Blocks preferred for lower-level "atomic" layout control and state management.
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TODOs:
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- State management for dynamic components update.
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- Add scratpad readout to right of chat log.
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* Placeholder added for now.
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- Add functionality to retry button.
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* Placeholder added for now.
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- Add dropdown for model selection.
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- Add textbox for HF model selection.
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"""
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with gr.Blocks() as chatUI:
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with gr.Row():
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chatOutput = gr.Chatbot(
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bubble_full_width = False,
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scale = 2
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)
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agentWhiteBoard = gr.Markdown(scale = 1)
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with gr.Row():
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queryInput = gr.Textbox(
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placeholder = "Please enter you question or request here...",
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show_label = False,
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scale = 4
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)
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submitButton = gr.Button("Submit", scale = 1)
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with gr.Row():
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retry = gr.Button("Retry (null)")
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clear = gr.ClearButton([queryInput, chatOutput])
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# gr.State()
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queryInput.submit(
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fn = query_submit,
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inputs = [queryInput, chatOutput],
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outputs = [queryInput, chatOutput],
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queue = False,
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).then(
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fn = query_completion,
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inputs = [queryInput, chatOutput],
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outputs = [chatOutput],
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)
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submitButton.click(
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fn = query_submit,
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inputs = [queryInput, chatOutput],
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outputs = [queryInput, chatOutput],
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queue = False,
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).then(
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fn = query_completion,
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inputs = [queryInput, chatOutput],
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outputs = [chatOutput],
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)
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chatUI.queue()
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chatUI.launch(show_api = False)
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