Merge branch 'main' of https://github.com/bucolucas/cyclop

.gitignore

@@ -8,6 +8,7 @@ __pycache__/
 
 # Virtual environment
 .venv/
+venv/
 env/
 
 # IDE files

ai_providers.py

@@ -1,8 +1,14 @@
 import os
 import json
+import logging
 import anthropic
 from openai import OpenAI
 from abc import ABC, abstractmethod
+from tools.github_tool import GitHubTool
+
+# Initialize GitHubTool and get functions
+github_tool = GitHubTool()
+functions = github_tool.get_functions()
 
 class AIProvider(ABC):
     @abstractmethod
@@ -17,6 +23,10 @@ class AIProvider(ABC):
     def format_tool_calls(self, response):
         pass
 
+    @abstractmethod
+    def format_tool_result(self, tool_call, tool_response):
+        pass
+
 class AnthropicProvider(AIProvider):
     def __init__(self):
         self.client = anthropic.Anthropic(
@@ -56,9 +66,28 @@ class AnthropicProvider(AIProvider):
                 "description": function['description'],
                 "input_schema": function['parameters'] if function['parameters'] not in [None, {}] else {"type": "object", "properties": {"param1": {"type": "string", "description": "Unnecessary"}}, "required": []}
             }
-            for function in functions  # This assumes 'functions' is globally accessible
+            for function in functions
         ]
 
+    def format_assistant_reply(self, response):
+        for message in response.content:
+            if message.type == "text":
+                return message.text
+        return ""
+
+    def get_reply_text(self, response):
+        return self.format_assistant_reply(response)
+
+    def get_model(self):
+        return self.model
+
+    def format_tool_result(self, tool_call, tool_response):
+        return {
+            "role": "function",
+            "name": tool_call.name,
+            "content": json.dumps(tool_response)
+        }
+
 class OpenAIProvider(AIProvider):
     def __init__(self, use_smart_model=True):
         self.client = OpenAI()
@@ -72,7 +101,7 @@ class OpenAIProvider(AIProvider):
         response = self.client.chat.completions.create(
             model=self.model,
             messages=self.format_messages(messages),
-            functions=functions,  # This assumes 'functions' is globally accessible
+            functions=functions,
             function_call="auto",
             max_tokens=self.get_max_tokens()
         )
@@ -91,6 +120,13 @@ class OpenAIProvider(AIProvider):
     def get_max_tokens(self):
         return 4096 if self.model == "gpt-4o" else 16384
 
+    def format_tool_result(self, tool_call, tool_response):
+        return {
+            "role": "function",
+            "name": tool_call.name,
+            "content": json.dumps(tool_response)
+        }
+
 def create_ai_provider(provider_name="anthropic", use_smart_model=True):
     if provider_name.lower() == "anthropic":
         return AnthropicProvider()

telegram_inference_bot.py

@@ -3,8 +3,7 @@ import os
 import importlib
 import inspect
 import logging
-import anthropic
-from telegram import Update
+from telegram import Update, __version__ as telegram_version
 from telegram.ext import Application, CommandHandler, MessageHandler, filters, ContextTypes
 from openai import OpenAI
 from dotenv import load_dotenv