removed unnecessary files
This commit is contained in:
-136
@@ -1,136 +0,0 @@
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import os
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import json
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import logging
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import anthropic
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from openai import OpenAI
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from abc import ABC, abstractmethod
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from tools.github_tool import GitHubTool
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# Initialize GitHubTool and get functions
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github_tool = GitHubTool()
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functions = github_tool.get_functions()
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class AIProvider(ABC):
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@abstractmethod
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def get_chat_response(self, messages):
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pass
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@abstractmethod
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def format_messages(self, messages):
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pass
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@abstractmethod
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def format_tool_calls(self, response):
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pass
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@abstractmethod
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def format_tool_result(self, tool_call, tool_response):
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pass
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class AnthropicProvider(AIProvider):
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def __init__(self):
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self.client = anthropic.Anthropic(
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api_key=os.environ.get("ANTHROPIC_API_KEY"),
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default_headers={"anthropic-beta": "max-tokens-3-5-sonnet-2024-07-15"}
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)
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self.model = "claude-3-5-sonnet-20240620"
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def get_chat_response(self, messages):
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try:
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response = self.client.messages.create(
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model=self.model,
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system=messages[0]['content'],
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messages=self.format_messages(messages[1:]),
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max_tokens=8192,
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tools=self.format_tools()
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)
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return response
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except Exception as e:
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logging.error(f"An error occurred: {str(e)}")
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return None
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def format_messages(self, messages):
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return messages
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def format_tool_calls(self, response):
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tool_calls = []
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for message in response.content:
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if message.type == "tool_use":
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tool_calls.append(message)
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return tool_calls
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def format_tools(self):
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return [
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{
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"name": function['name'],
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"description": function['description'],
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"input_schema": function['parameters'] if function['parameters'] not in [None, {}] else {"type": "object", "properties": {"param1": {"type": "string", "description": "Unnecessary"}}, "required": []}
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}
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for function in functions
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]
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def format_assistant_reply(self, response):
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for message in response.content:
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if message.type == "text":
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return message.text
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return ""
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def get_reply_text(self, response):
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return self.format_assistant_reply(response)
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def get_model(self):
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return self.model
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def format_tool_result(self, tool_call, tool_response):
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return {
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"role": "function",
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"name": tool_call.name,
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"content": json.dumps(tool_response)
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}
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class OpenAIProvider(AIProvider):
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def __init__(self, use_smart_model=True):
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self.client = OpenAI()
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self.use_smart_model = use_smart_model
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self.model = self.get_model()
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def get_model(self):
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return "gpt-4o" if self.use_smart_model else "gpt-4o-mini"
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def get_chat_response(self, messages):
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response = self.client.chat.completions.create(
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model=self.model,
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messages=self.format_messages(messages),
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functions=functions,
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function_call="auto",
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max_tokens=self.get_max_tokens()
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)
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return response
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def format_messages(self, messages):
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return messages
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def format_tool_calls(self, response):
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tool_calls = []
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assistant_message = response.choices[0].message
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if hasattr(assistant_message, 'function_call') and assistant_message.function_call is not None:
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tool_calls.append(assistant_message.function_call)
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return tool_calls
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def get_max_tokens(self):
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return 4096 if self.model == "gpt-4o" else 16384
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def format_tool_result(self, tool_call, tool_response):
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return {
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"role": "function",
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"name": tool_call.name,
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"content": json.dumps(tool_response)
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}
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def create_ai_provider(provider_name="anthropic", use_smart_model=True):
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if provider_name.lower() == "anthropic":
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return AnthropicProvider()
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elif provider_name.lower() == "openai":
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return OpenAIProvider(use_smart_model)
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else:
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raise ValueError(f"Unknown provider: {provider_name}")
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@@ -8,13 +8,14 @@ from telegram.ext import Application, CommandHandler, MessageHandler, filters, C
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from openai import OpenAI
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from dotenv import load_dotenv
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from tools.base_tool import BaseTool
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from anthropic import Anthropic
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# Load environment variables
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load_dotenv()
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openai_client = OpenAI()
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anthropic_client = anthropic.Anthropic(
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anthropic_client = Anthropic(
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api_key=os.environ.get("ANTHROPIC_API_KEY"),
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default_headers={"anthropic-beta": "max-tokens-3-5-sonnet-2024-07-15"}
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)
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@@ -1,31 +0,0 @@
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# tools/camera_tool.py
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from .base_tool import BaseTool
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import picamera
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import time
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import base64
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from io import BytesIO
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class CameraTool(BaseTool):
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def get_functions(self):
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return [{
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"name": "take_picture",
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"description": "Take a picture using the Raspberry Pi camera",
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"parameters": {
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"type": "object",
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"properties": {},
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"required": []
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}
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}]
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def execute(self, function_name, **kwargs):
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if function_name == "take_picture":
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with picamera.PiCamera() as camera:
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camera.resolution = (1024, 768)
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camera.start_preview()
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# Camera warm-up time
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time.sleep(2)
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image_stream = BytesIO()
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camera.capture(image_stream, 'jpeg')
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image_stream.seek(0)
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image_base64 = base64.b64encode(image_stream.getvalue()).decode('utf-8')
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return f"data:image/jpeg;base64,{image_base64}"
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@@ -1,79 +0,0 @@
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import os
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import openai
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import json
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from tools.base_tool import BaseTool
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class PersonaTool(BaseTool):
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def __init__(self):
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super().__init__()
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self.api_key = os.environ.get("OPENAI_API_KEY")
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GPT_4O = "gpt-4o"
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GPT_4O_MINI = "gpt-4o-mini"
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def generate_response(self, persona_description: str, query: str) -> str:
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"""
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Makes a call to the OpenAI API using the persona as a system prompt.
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Parameters:
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persona_description (str): Description of the persona.
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query (str): Query to be processed.
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Returns:
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str: The response generated by the OpenAI API.
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"""
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": persona_description},
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{"role": "user", "content": query}
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]
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)
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return response.choices[0].message['content']
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def get_functions(self):
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return json.dumps({
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"functions": [
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{
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"name": "generate_response",
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"description": "Generates a response based on a persona description and a user query.",
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"parameters": {
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"type": "object",
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"properties": {
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"persona_description": {
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"type": "string",
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"description": "Description of the persona."
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},
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"query": {
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"type": "string",
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"description": "User's query to be processed."
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}
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},
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"required": ["persona_description", "query"]
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}
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}
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]
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})
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def execute(self, function_name, **kwargs):
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if function_name == "generate_response":
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return self.generate_response(kwargs.get("persona_description"), kwargs.get("query"))
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else:
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raise ValueError(f"Function {function_name} not found")
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def get_chat_response(client, messages, model):
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model_max_tokens = {
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GPT_4O: 4096,
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GPT_4O_MINI: 16384
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}
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response = client.chat.completions.create(
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model=model,
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messages=messages,
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function_call="none",
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max_tokens=model_max_tokens[model]
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)
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return response
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@@ -1,49 +0,0 @@
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# tools/telegram_keyboard_tool.py
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from .base_tool import BaseTool
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class TelegramKeyboardTool(BaseTool):
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def get_functions(self):
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return [
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{
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"name": "create_keyboard",
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"description": "Create a Telegram keyboard layout.",
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"parameters": {
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"type": "object",
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"properties": {
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"buttons": {
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"type": "array",
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"items": {
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"type": "array",
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"items": {
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"type": "string",
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"description": "Text on the button."
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},
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"description": "A row of buttons."
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},
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"description": "List of rows of buttons."
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}
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},
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"required": ["buttons"]
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}
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}
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]
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def execute(self, function_name, **kwargs):
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if function_name == "create_keyboard":
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return self._create_keyboard(kwargs.get("buttons"))
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else:
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return f"Unknown function: {function_name}"
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def _create_keyboard(self, buttons):
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if not isinstance(buttons, list):
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return "Invalid input: 'buttons' must be a list of lists."
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keyboard = {
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"keyboard": buttons,
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"resize_keyboard": True,
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"one_time_keyboard": True
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}
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return keyboard
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