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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 home.user.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() |