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import os | |
import subprocess | |
from huggingface_hub import InferenceClient | |
import gradio as gr | |
import random | |
import time | |
from typing import List, Dict | |
from flask import Flask, request, jsonify | |
from app.prompts import * | |
# Constants | |
AGENT_TYPES = [ | |
"Task Executor", | |
"Information Retriever", | |
"Decision Maker", | |
"Data Analyzer", | |
] | |
TOOL_TYPES = [ | |
"Web Scraper", | |
"Database Connector", | |
"API Caller", | |
"File Handler", | |
"Text Processor", | |
] | |
VERBOSE = False | |
MAX_HISTORY = 100 | |
MODEL = "mistralai/Mixtral-8x7B-Instruct-v0.1" | |
# Initialize Hugging Face client | |
client = InferenceClient(MODEL) | |
# Import necessary prompts and functions from the existing code | |
from .prompts import ( | |
ACTION_PROMPT, | |
ADD_PROMPT, | |
COMPRESS_HISTORY_PROMPT, | |
LOG_PROMPT, | |
LOG_RESPONSE, | |
MODIFY_PROMPT, | |
PREFIX, | |
READ_PROMPT, | |
TASK_PROMPT, | |
UNDERSTAND_TEST_RESULTS_PROMPT, | |
) | |
from .utils import parse_action, parse_file_content, read_python_module_structure | |
class Agent: | |
def __init__(self, name: str, agent_type: str, complexity: int): | |
self.name = name | |
self.type = agent_type | |
self.complexity = complexity | |
self.tools = [] | |
def add_tool(self, tool): | |
self.tools.append(tool) | |
def __str__(self): | |
return f"{self.name} ({self.type}) - Complexity: {self.complexity}" | |
class Tool: | |
def __init__(self, name: str, tool_type: str): | |
self.name = name | |
self.type = tool_type | |
def __str__(self): | |
return f"{self.name} ({self.type})" | |
class Pypelyne: | |
def __init__(self): | |
self.agents: List[Agent] = [] | |
self.tools: List[Tool] = [] | |
self.history = "" | |
self.task = None | |
self.purpose = None | |
self.directory = None | |
def add_agent(self, agent: Agent): | |
self.agents.append(agent) | |
def add_tool(self, tool: Tool): | |
self.tools.append(tool) | |
def generate_chat_app(self): | |
time.sleep(2) # Simulate processing time | |
return f"Chat app generated with {len(self.agents)} agents and {len(self.tools)} tools." | |
def run_gpt(self, prompt_template, stop_tokens, max_tokens, **prompt_kwargs): | |
content = PREFIX.format( | |
module_summary=read_python_module_structure(self.directory)[0], | |
purpose=self.purpose, | |
) + prompt_template.format(**prompt_kwargs) | |
if VERBOSE: | |
print(LOG_PROMPT.format(content)) | |
try: | |
stream = client.text_generation( | |
prompt=content, | |
max_new_tokens=max_tokens, | |
stop_sequences=stop_tokens if stop_tokens else None, | |
do_sample=True, | |
temperature=0.7, | |
) | |
resp = "".join(token for token in stream) | |
except Exception as e: | |
print(f"Error in run_gpt: {e}") | |
resp = f"Error: {e}" | |
if VERBOSE: | |
print(LOG_RESPONSE.format(resp)) | |
return resp | |
def compress_history(self): | |
resp = self.run_gpt( | |
COMPRESS_HISTORY_PROMPT, | |
stop_tokens=["observation:", "task:", "action:", "thought:"], | |
max_tokens=512, | |
task=self.task, | |
history=self.history, | |
) | |
self.history = f"observation: {resp}\n" | |
def run_action(self, action_name, action_input): | |
if action_name == "COMPLETE": | |
return "Task completed." | |
if len(self.history.split("\n")) > MAX_HISTORY: | |
if VERBOSE: | |
print("COMPRESSING HISTORY") | |
self.compress_history() | |
action_funcs = { | |
"MAIN": self.call_main, | |
"UPDATE-TASK": self.call_set_task, | |
"MODIFY-FILE": self.call_modify, | |
"READ-FILE": self.call_read, | |
"ADD-FILE": self.call_add, | |
"TEST": self.call_test, | |
} | |
if action_name not in action_funcs: | |
return f"Unknown action: {action_name}" | |
print(f"RUN: {action_name} {action_input}") | |
return action_funcs[action_name](action_input) | |
def call_main(self, action_input): | |
resp = self.run_gpt( | |
ACTION_PROMPT, | |
stop_tokens=["observation:", "task:"], | |
max_tokens=256, | |
task=self.task, | |
history=self.history, | |
) | |
lines = resp.strip().strip("\n").split("\n") | |
for line in lines: | |
if line == "": | |
continue | |
if line.startswith("thought: "): | |
self.history += f"{line}\n" | |
elif line.startswith("action: "): | |
action_name, action_input = parse_action(line) | |
self.history += f"{line}\n" | |
return self.run_action(action_name, action_input) | |
return "No valid action found." | |
def call_set_task(self, action_input): | |
self.task = self.run_gpt( | |
TASK_PROMPT, | |
stop_tokens=[], | |
max_tokens=64, | |
task=self.task, | |
history=self.history, | |
).strip("\n") | |
self.history += f"observation: task has been updated to: {self.task}\n" | |
return f"Task updated: {self.task}" | |
def call_modify(self, action_input): | |
if not os.path.exists(action_input): | |
self.history += "observation: file does not exist\n" | |
return "File does not exist." | |
content = read_python_module_structure(self.directory)[1] | |
f_content = ( | |
content[action_input] if content[action_input] else "< document is empty >" | |
) | |
resp = self.run_gpt( | |
MODIFY_PROMPT, | |
stop_tokens=["action:", "thought:", "observation:"], | |
max_tokens=2048, | |
task=self.task, | |
history=self.history, | |
file_path=action_input, | |
file_contents=f_content, | |
) | |
new_contents, description = parse_file_content(resp) | |
if new_contents is None: | |
self.history += "observation: failed to modify file\n" | |
return "Failed to modify file." | |
with open(action_input, "w") as f: | |
f.write(new_contents) | |
self.history += f"observation: file successfully modified\n" | |
self.history += f"observation: {description}\n" | |
return f"File modified: {action_input}" | |
def call_read(self, action_input): | |
if not os.path.exists(action_input): | |
self.history += "observation: file does not exist\n" | |
return "File does not exist." | |
content = read_python_module_structure(self.directory)[1] | |
f_content = ( | |
content[action_input] if content[action_input] else "< document is empty >" | |
) | |
resp = self.run_gpt( | |
READ_PROMPT, | |
stop_tokens=[], | |
max_tokens=256, | |
task=self.task, | |
history=self.history, | |
file_path=action_input, | |
file_contents=f_content, | |
).strip("\n") | |
self.history += f"observation: {resp}\n" | |
return f"File read: {action_input}" | |
def call_add(self, action_input): | |
d = os.path.dirname(action_input) | |
if not d.startswith(self.directory): | |
self.history += ( | |
f"observation: files must be under directory {self.directory}\n" | |
) | |
return f"Invalid directory: {d}" | |
elif not action_input.endswith(".py"): | |
self.history += "observation: can only write .py files\n" | |
return "Only .py files are allowed." | |
else: | |
if d and not os.path.exists(d): | |
os.makedirs(d) | |
if not os.path.exists(action_input): | |
resp = self.run_gpt( | |
ADD_PROMPT, | |
stop_tokens=["action:", "thought:", "observation:"], | |
max_tokens=2048, | |
task=self.task, | |
history=self.history, | |
file_path=action_input, | |
) | |
new_contents, description = parse_file_content(resp) | |
if new_contents is None: | |
self.history += "observation: failed to write file\n" | |
return "Failed to write file." | |
with open(action_input, "w") as f: | |
f.write(new_contents) | |
self.history += "observation: file successfully written\n" | |
self.history += f"observation: {description}\n" | |
return f"File added: {action_input}" | |
else: | |
self.history += "observation: file already exists\n" | |
return "File already exists." | |
def call_test(self, action_input): | |
result = subprocess.run( | |
["python", "-m", "pytest", "--collect-only", self.directory], | |
capture_output=True, | |
text=True, | |
) | |
if result.returncode != 0: | |
self.history += f"observation: there are no tests! Test should be written in a test folder under {self.directory}\n" | |
return "No tests found." | |
result = subprocess.run( | |
["python", "-m", "pytest", self.directory], capture_output=True, text=True | |
) | |
if result.returncode == 0: | |
self.history += "observation: tests pass\n" | |
return "All tests passed." | |
resp = self.run_gpt( | |
UNDERSTAND_TEST_RESULTS_PROMPT, | |
stop_tokens=[], | |
max_tokens=256, | |
task=self.task, | |
history=self.history, | |
stdout=result.stdout[:5000], | |
stderr=result.stderr[:5000], | |
) | |
self.history += f"observation: tests failed: {resp}\n" | |
return f"Tests failed: {resp}" | |
pypelyne = Pypelyne() | |
def create_agent(name: str, agent_type: str, complexity: int) -> Agent: | |
agent = Agent(name, agent_type, complexity) | |
pypelyne.add_agent(agent) | |
return agent | |
def create_tool(name: str, tool_type: str) -> Tool: | |
tool = Tool(name, tool_type) | |
pypelyne.add_tool(tool) | |
return tool | |
def main(): | |
# Create a Flask app | |
app = Flask(__name__) | |
# Define a route for the chat interface | |
def chat(): | |
if request.method == "POST": | |
# Get the user's input | |
user_input = request.form["input"] | |
# Run the input through the Pypelyne | |
response = pypelyne.run_action("MAIN", user_input) | |
# Return the response | |
return jsonify({"response": response}) | |
else: | |
# Return the chat interface | |
return """ | |
<html> | |
<body> | |
<h1>Pypelyne Chat Interface</h1> | |
<form action="/chat" method="post"> | |
<input type="text" name="input" placeholder="Enter your input"> | |
<input type="submit" value="Submit"> | |
</form> | |
<div id="response"></div> | |
<script> | |
// Update the response div with the response from the server | |
function updateResponse(response) { | |
document.getElementById("response").innerHTML = response; | |
} | |
</script> | |
</body> | |
</html> | |
""" | |
# Define a route for the agent creation interface | |
def create_agent_interface(): | |
if request.method == "POST": | |
# Get the agent's name, type, and complexity | |
name = request.form["name"] | |
agent_type = request.form["type"] | |
complexity = int(request.form["complexity"]) | |
# Create the agent | |
agent = create_agent(name, agent_type, complexity) | |
# Return a success message | |
return jsonify({"message": f"Agent {name} created successfully"}) | |
else: | |
# Return the agent creation interface | |
return """ | |
<html> | |
<body> | |
<h1>Create Agent</h1> | |
<form action="/create_agent" method="post"> | |
<label for="name">Name:</label> | |
<input type="text" id="name" name="name"><br><br> | |
<label for="type">Type:</label> | |
<select id="type" name="type"> | |
<option value="Task Executor">Task Executor</option> | |
<option value="Information Retriever">Information Retriever</option> | |
<option value="Decision Maker">Decision Maker</option> | |
<option value="Data Analyzer">Data Analyzer</option> | |
</select><br><br> | |
<label for="complexity">Complexity:</label> | |
<input type="number" id="complexity" name="complexity"><br><br> | |
<input type="submit" value="Create Agent"> | |
</form> | |
</body> | |
</html> | |
""" | |
# Define a route for the tool creation interface | |
def create_tool_interface(): | |
if request.method == "POST": | |
# Get the tool's name and type | |
name = request.form["name"] | |
tool_type = request.form["type"] | |
# Create the tool | |
tool = create_tool(name, tool_type) | |
# Return a success message | |
return jsonify({"message": f"Tool {name} created successfully"}) | |
else: | |
# Return the tool creation interface | |
return """ | |
<html> | |
<body> | |
<h1>Create Tool</h1> | |
<form action="/create_tool" method="post"> | |
<label for="name">Name:</label> | |
<input type="text" id="name" name="name"><br><br> | |
<label for="type">Type:</label> | |
<select id="type" name="type"> | |
<option value="Web Scraper">Web Scraper</option> | |
<option value="Database Connector">Database Connector</option> | |
<option value="API Caller">API Caller</option> | |
<option value="File Handler">File Handler</option> | |
<option value="Text Processor">Text Processor</option> | |
</select><br><br> | |
<input type="submit" value="Create Tool"> | |
</form> | |
</body> | |
</html> | |
""" | |
# Run the app | |
if __name__ == "__main__": | |
app.run(debug=True) | |
if __name__ == "__main__": | |
main() |