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Update app.py
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app.py
CHANGED
@@ -3,7 +3,6 @@ import os
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import subprocess
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import random
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from huggingface_hub import InferenceClient
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import gradio as gr
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from safe_search import safe_search
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from i_search import google
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from i_search import i_search as i_s
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@@ -44,7 +43,7 @@ logger = logging.getLogger(__name__)
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# Load custom prompts
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try:
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with open('custom_prompts.yaml', 'r') as fp:
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custom_prompts = yaml.
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except FileNotFoundError:
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custom_prompts = {
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"WEB_DEV": "",
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@@ -285,7 +284,7 @@ def run_action(purpose, task, history, directory, action_name, action_input):
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print("COMPRESSING HISTORY")
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history = compress_history(purpose, task, history, directory)
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if not
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action_name = "MAIN"
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if action_name == "" or action_name is None:
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action_name = "MAIN"
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@@ -327,10 +326,10 @@ def run(purpose, history):
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action_input,
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)
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yield
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if task == "END":
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return
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################################################
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@@ -344,14 +343,14 @@ def generate(
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prompt, history, agent_name=agents[0], sys_prompt="", temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.7,
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):
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seed = random.randint(1, 1111111111111111)
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agent =
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if agent_name == "WEB_DEV":
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agent =
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elif agent_name == "AI_SYSTEM_PROMPT":
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agent =
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elif agent_name == "PYTHON_CODE_DEV":
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agent =
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system_prompt = agent
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temperature = float(temperature)
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@@ -389,15 +388,15 @@ with gr.Blocks() as iface:
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iface.load(inputs, events)
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def log_messages(inputs, outputs):
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logger(f'Input: {inputs}, Output: {outputs}')
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@gr.Interface.load(inputs, agents)
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def log_messages(inputs, outputs):
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logger(f'Input: {inputs}, Output: {outputs}')
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@gr.Interface.load(inputs, events)
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def log_messages(inputs, outputs):
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logger(f'Input: {inputs}, Output: {outputs}')
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def update_sys_prompt(agent):
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global SYSTEM_PROMPT
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@@ -514,9 +513,10 @@ with iface:
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[msg, chatbot, agent_dropdown, sys_prompt, temperature, max_new_tokens, top_p, repetition_penalty],
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[chatbot, msg])
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clear.click(lambda: None, None, chatbot, queue=False)
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gr.Examples(examples, [msg, agent_dropdown, sys_prompt, temperature, max_new_tokens, top_p, repetition_penalty]),
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iface.launch()
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import subprocess
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import random
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from huggingface_hub import InferenceClient
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from safe_search import safe_search
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from i_search import google
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from i_search import i_search as i_s
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# Load custom prompts
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try:
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with open('custom_prompts.yaml', 'r') as fp:
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custom_prompts = yaml.safe_load(fp)
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except FileNotFoundError:
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custom_prompts = {
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"WEB_DEV": "",
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print("COMPRESSING HISTORY")
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history = compress_history(purpose, task, history, directory)
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if action_name not in NAME_TO_FUNC:
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action_name = "MAIN"
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if action_name == "" or action_name is None:
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action_name = "MAIN"
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action_input,
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)
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yield history
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if task == "END":
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return history
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################################################
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prompt, history, agent_name=agents[0], sys_prompt="", temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.7,
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):
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seed = random.randint(1, 1111111111111111)
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agent = custom_prompts["WEB_DEV"]
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if agent_name == "WEB_DEV":
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agent = custom_prompts["WEB_DEV"]
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elif agent_name == "AI_SYSTEM_PROMPT":
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agent = custom_prompts["AI_SYSTEM_PROMPT"]
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elif agent_name == "PYTHON_CODE_DEV":
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agent = custom_prompts["PYTHON_CODE_DEV"]
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system_prompt = agent
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temperature = float(temperature)
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iface.load(inputs, events)
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def log_messages(inputs, outputs):
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logger.info(f'Input: {inputs}, Output: {outputs}')
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@gr.Interface.load(inputs, agents)
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def log_messages(inputs, outputs):
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logger.info(f'Input: {inputs}, Output: {outputs}')
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@gr.Interface.load(inputs, events)
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def log_messages(inputs, outputs):
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logger.info(f'Input: {inputs}, Output: {outputs}')
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def update_sys_prompt(agent):
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global SYSTEM_PROMPT
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[msg, chatbot, agent_dropdown, sys_prompt, temperature, max_new_tokens, top_p, repetition_penalty],
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[chatbot, msg])
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clear.click(lambda: None, None, chatbot, queue=False)
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gr.Examples(examples, [msg, agent_dropdown, sys_prompt, temperature, max_new_tokens, top_p, repetition_penalty])
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agent_dropdown.change(fn=get_helpful_tip, inputs=agent_dropdown, outputs=gr.components.Markdown())
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agent_dropdown.change(fn=update_sys_prompt, inputs=agent_dropdown, outputs=sys_prompt)
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iface.launch()
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