Abstract AiHandler to BaseAiHandler

pr_agent/agent/pr_agent.py

@@ -1,8 +1,11 @@
 import shlex
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
+from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler
 
 from pr_agent.algo.utils import update_settings_from_args
 from pr_agent.config_loader import get_settings
 from pr_agent.git_providers.utils import apply_repo_settings
+from pr_agent.log import get_logger
 from pr_agent.tools.pr_add_docs import PRAddDocs
 from pr_agent.tools.pr_code_suggestions import PRCodeSuggestions
 from pr_agent.tools.pr_config import PRConfig
@@ -38,8 +41,8 @@
 commands = list(command2class.keys())
 
 class PRAgent:
-    def __init__(self):
-        pass
+    def __init__(self, ai_handler: BaseAiHandler = LiteLLMAIHandler()):
+        self.ai_handler = ai_handler
 
     async def handle_request(self, pr_url, request, notify=None) -> bool:
         # First, apply repo specific settings if exists
@@ -61,13 +64,14 @@ async def handle_request(self, pr_url, request, notify=None) -> bool:
         if action == "answer":
             if notify:
                 notify()
-            await PRReviewer(pr_url, is_answer=True, args=args).run()
+            await PRReviewer(pr_url, is_answer=True, args=args, ai_handler=self.ai_handler).run()
         elif action == "auto_review":
-            await PRReviewer(pr_url, is_auto=True, args=args).run()
+            await PRReviewer(pr_url, is_auto=True, args=args, ai_handler=self.ai_handler).run()
         elif action in command2class:
             if notify:
                 notify()
-            await command2class[action](pr_url, args=args).run()
+
+            await command2class[action](pr_url, ai_handler=self.ai_handler, args=args).run()
         else:
             return False
         return True

pr_agent/algo/ai_handlers/base_ai_handler.py

@@ -0,0 +1,28 @@
+from abc import ABC, abstractmethod
+
+class BaseAiHandler(ABC):
+    """
+    This class defines the interface for an AI handler to be used by the PR Agents.  
+    """
+
+    @abstractmethod
+    def __init__(self):
+        pass
+
+    @property
+    @abstractmethod
+    def deployment_id(self):
+        pass
+
+    @abstractmethod   
+    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
+        """
+        This method should be implemented to return a chat completion from the AI model.
+        Args:
+            model (str): the name of the model to use for the chat completion
+            system (str): the system message string to use for the chat completion
+            user (str): the user message string to use for the chat completion
+            temperature (float): the temperature to use for the chat completion    
+        """
+        pass
+

pr_agent/algo/ai_handlers/langchain_ai_handler.py

@@ -0,0 +1,49 @@
+try:
+    from langchain.chat_models import ChatOpenAI
+    from langchain.schema import SystemMessage, HumanMessage
+except: # we don't enforce langchain as a dependency, so if it's not installed, just move on
+    pass
+
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
+from pr_agent.config_loader import get_settings
+from pr_agent.log import get_logger
+
+from openai.error import APIError, RateLimitError, Timeout, TryAgain
+from retry import retry    
+
+OPENAI_RETRIES = 5
+
+class LangChainOpenAIHandler(BaseAiHandler):
+    def __init__(self):
+        # Initialize OpenAIHandler specific attributes here
+        try:
+            super().__init__()            
+            self._chat = ChatOpenAI(openai_api_key=get_settings().openai.key)
+
+        except AttributeError as e:
+            raise ValueError("OpenAI key is required") from e
+
+    @property
+    def chat(self):
+        return self._chat
+
+    @property
+    def deployment_id(self):
+        """
+        Returns the deployment ID for the OpenAI API.
+        """
+        return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
+    @retry(exceptions=(APIError, Timeout, TryAgain, AttributeError, RateLimitError),
+           tries=OPENAI_RETRIES, delay=2, backoff=2, jitter=(1, 3))
+    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
+        try:
+            messages=[SystemMessage(content=system), HumanMessage(content=user)]
+
+            # get a chat completion from the formatted messages
+            resp = self.chat(messages, model=model, temperature=temperature)
+            finish_reason="completed"
+            return resp.content, finish_reason
+
+        except (Exception) as e:
+            get_logger().error("Unknown error during OpenAI inference: ", e)
+            raise e

pr_agent/algo/ai_handler.py → pr_agent/algo/ai_handlers/litellm_ai_handler.py

@@ -6,13 +6,14 @@
 from litellm import acompletion
 from openai.error import APIError, RateLimitError, Timeout, TryAgain
 from retry import retry
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
 from pr_agent.config_loader import get_settings
 from pr_agent.log import get_logger
 
 OPENAI_RETRIES = 5
 
 
-class AiHandler:
+class LiteLLMAIHandler(BaseAiHandler):
     """
     This class handles interactions with the OpenAI API for chat completions.
     It initializes the API key and other settings from a configuration file,
@@ -134,4 +135,4 @@ async def chat_completion(self, model: str, system: str, user: str, temperature:
         usage = response.get("usage")
         get_logger().info("AI response", response=resp, messages=messages, finish_reason=finish_reason,
                           model=model, usage=usage)
-        return resp, finish_reason
+        return resp, finish_reason

pr_agent/algo/ai_handlers/openai_ai_handler.py

@@ -0,0 +1,67 @@
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
+import openai
+from openai.error import APIError, RateLimitError, Timeout, TryAgain
+from retry import retry
+
+from pr_agent.config_loader import get_settings
+from pr_agent.log import get_logger
+
+OPENAI_RETRIES = 5
+
+
+class OpenAIHandler(BaseAiHandler):
+    def __init__(self):
+        # Initialize OpenAIHandler specific attributes here
+        try:
+            super().__init__()
+            openai.api_key = get_settings().openai.key
+            if get_settings().get("OPENAI.ORG", None):
+                openai.organization = get_settings().openai.org
+            if get_settings().get("OPENAI.API_TYPE", None):
+                if get_settings().openai.api_type == "azure":
+                    self.azure = True
+                    openai.azure_key = get_settings().openai.key
+            if get_settings().get("OPENAI.API_VERSION", None):
+                openai.api_version = get_settings().openai.api_version
+            if get_settings().get("OPENAI.API_BASE", None):
+                openai.api_base = get_settings().openai.api_base
+
+        except AttributeError as e:
+            raise ValueError("OpenAI key is required") from e
+    @property
+    def deployment_id(self):
+        """
+        Returns the deployment ID for the OpenAI API.
+        """
+        return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
+
+    @retry(exceptions=(APIError, Timeout, TryAgain, AttributeError, RateLimitError),
+           tries=OPENAI_RETRIES, delay=2, backoff=2, jitter=(1, 3))
+    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
+        try:
+            deployment_id = self.deployment_id
+            get_logger().info("System: ", system)
+            get_logger().info("User: ", user)
+            messages = [{"role": "system", "content": system}, {"role": "user", "content": user}]
+
+            chat_completion = await openai.ChatCompletion.acreate(
+                model=model,
+                deployment_id=deployment_id,
+                messages=messages,
+                temperature=temperature,
+            )
+            resp = chat_completion["choices"][0]['message']['content']
+            finish_reason = chat_completion["choices"][0]["finish_reason"]
+            usage = chat_completion.get("usage")
+            get_logger().info("AI response", response=resp, messages=messages, finish_reason=finish_reason,
+                            model=model, usage=usage)
+            return resp, finish_reason       
+        except (APIError, Timeout, TryAgain) as e:
+            get_logger().error("Error during OpenAI inference: ", e)
+            raise
+        except (RateLimitError) as e:
+            get_logger().error("Rate limit error during OpenAI inference: ", e)
+            raise
+        except (Exception) as e:
+            get_logger().error("Unknown error during OpenAI inference: ", e)
+            raise TryAgain from e        

pr_agent/algo/utils.py

@@ -447,4 +447,4 @@ def clip_tokens(text: str, max_tokens: int, add_three_dots=True) -> str:
         return clipped_text
     except Exception as e:
         get_logger().warning(f"Failed to clip tokens: {e}")
-        return text
+        return text

pr_agent/tools/pr_add_docs.py

@@ -4,7 +4,8 @@
 
 from jinja2 import Environment, StrictUndefined
 
-from pr_agent.algo.ai_handler import AiHandler
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
+from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler
 from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models
 from pr_agent.algo.token_handler import TokenHandler
 from pr_agent.algo.utils import load_yaml
@@ -15,14 +16,15 @@
 
 
 class PRAddDocs:
-    def __init__(self, pr_url: str, cli_mode=False, args: list = None):
+    def __init__(self, pr_url: str, cli_mode=False, args: list = None,
+                 ai_handler: BaseAiHandler = LiteLLMAIHandler()):
 
         self.git_provider = get_git_provider()(pr_url)
         self.main_language = get_main_pr_language(
             self.git_provider.get_languages(), self.git_provider.get_files()
         )
 
-        self.ai_handler = AiHandler()
+        self.ai_handler = ai_handler
         self.patches_diff = None
         self.prediction = None
         self.cli_mode = cli_mode

pr_agent/tools/pr_code_suggestions.py

@@ -3,7 +3,8 @@
 from typing import Dict, List
 from jinja2 import Environment, StrictUndefined
 
-from pr_agent.algo.ai_handler import AiHandler
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
+from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler
 from pr_agent.algo.pr_processing import get_pr_diff, get_pr_multi_diffs, retry_with_fallback_models
 from pr_agent.algo.token_handler import TokenHandler
 from pr_agent.algo.utils import load_yaml
@@ -14,7 +15,8 @@
 
 
 class PRCodeSuggestions:
-    def __init__(self, pr_url: str, cli_mode=False, args: list = None):
+    def __init__(self, pr_url: str, cli_mode=False, args: list = None,
+                 ai_handler: BaseAiHandler = LiteLLMAIHandler()):
 
         self.git_provider = get_git_provider()(pr_url)
         self.main_language = get_main_pr_language(
@@ -31,7 +33,7 @@ def __init__(self, pr_url: str, cli_mode=False, args: list = None):
         else:
             num_code_suggestions = get_settings().pr_code_suggestions.num_code_suggestions
 
-        self.ai_handler = AiHandler()
+        self.ai_handler = ai_handler
         self.patches_diff = None
         self.prediction = None
         self.cli_mode = cli_mode

pr_agent/tools/pr_description.py

@@ -4,7 +4,8 @@
 
 from jinja2 import Environment, StrictUndefined
 
-from pr_agent.algo.ai_handler import AiHandler
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
+from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler
 from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models
 from pr_agent.algo.token_handler import TokenHandler
 from pr_agent.algo.utils import load_yaml, set_custom_labels, get_user_labels
@@ -15,7 +16,8 @@
 
 
 class PRDescription:
-    def __init__(self, pr_url: str, args: list = None):
+    def __init__(self, pr_url: str, args: list = None,
+                 ai_handler: BaseAiHandler = LiteLLMAIHandler()):
         """
         Initialize the PRDescription object with the necessary attributes and objects for generating a PR description
         using an AI model.
@@ -36,7 +38,7 @@ def __init__(self, pr_url: str, args: list = None):
             get_settings().pr_description.enable_semantic_files_types = False
 
         # Initialize the AI handler
-        self.ai_handler = AiHandler()
+        self.ai_handler = ai_handler
 
         # Initialize the variables dictionary
         self.vars = {

pr_agent/tools/pr_generate_labels.py

@@ -4,7 +4,8 @@
 
 from jinja2 import Environment, StrictUndefined
 
-from pr_agent.algo.ai_handler import AiHandler
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
+from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler
 from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models
 from pr_agent.algo.token_handler import TokenHandler
 from pr_agent.algo.utils import load_yaml, set_custom_labels, get_user_labels
@@ -15,7 +16,8 @@
 
 
 class PRGenerateLabels:
-    def __init__(self, pr_url: str, args: list = None):
+    def __init__(self, pr_url: str, args: list = None,
+                 ai_handler: BaseAiHandler = LiteLLMAIHandler()):
         """
         Initialize the PRGenerateLabels object with the necessary attributes and objects for generating labels
         corresponding to the PR using an AI model.
@@ -31,7 +33,7 @@ def __init__(self, pr_url: str, args: list = None):
         self.pr_id = self.git_provider.get_pr_id()
 
         # Initialize the AI handler
-        self.ai_handler = AiHandler()
+        self.ai_handler = ai_handler
 
         # Initialize the variables dictionary
         self.vars = {

pr_agent/tools/pr_information_from_user.py

@@ -2,7 +2,8 @@
 
 from jinja2 import Environment, StrictUndefined
 
-from pr_agent.algo.ai_handler import AiHandler
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
+from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler
 from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models
 from pr_agent.algo.token_handler import TokenHandler
 from pr_agent.config_loader import get_settings
@@ -12,12 +13,13 @@
 
 
 class PRInformationFromUser:
-    def __init__(self, pr_url: str, args: list = None):
+    def __init__(self, pr_url: str, args: list = None,
+                 ai_handler: BaseAiHandler = LiteLLMAIHandler()):
         self.git_provider = get_git_provider()(pr_url)
         self.main_pr_language = get_main_pr_language(
             self.git_provider.get_languages(), self.git_provider.get_files()
         )
-        self.ai_handler = AiHandler()
+        self.ai_handler = ai_handler
         self.vars = {
             "title": self.git_provider.pr.title,
             "branch": self.git_provider.get_pr_branch(),

pr_agent/tools/pr_questions.py

@@ -2,7 +2,8 @@
 
 from jinja2 import Environment, StrictUndefined
 
-from pr_agent.algo.ai_handler import AiHandler
+from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
+from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler
 from pr_agent.algo.pr_processing import get_pr_diff, retry_with_fallback_models
 from pr_agent.algo.token_handler import TokenHandler
 from pr_agent.config_loader import get_settings
@@ -12,13 +13,13 @@
 
 
 class PRQuestions:
-    def __init__(self, pr_url: str, args=None):
+    def __init__(self, pr_url: str, args=None, ai_handler: BaseAiHandler = LiteLLMAIHandler()):
         question_str = self.parse_args(args)
         self.git_provider = get_git_provider()(pr_url)
         self.main_pr_language = get_main_pr_language(
             self.git_provider.get_languages(), self.git_provider.get_files()
         )
-        self.ai_handler = AiHandler()
+        self.ai_handler = ai_handler
         self.question_str = question_str
         self.vars = {
             "title": self.git_provider.pr.title,