s

pr_agent/algo/ai_handlers/base_ai_handler.py

@@ -15,7 +15,7 @@ class BaseAiHandler(ABC):
         pass
 
     @abstractmethod   
-    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
+    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2, img_path: str = None):
         """
         This method should be implemented to return a chat completion from the AI model.
         Args:

pr_agent/algo/ai_handlers/litellm_ai_handler.py

@@ -102,13 +102,23 @@ class LiteLLMAIHandler(BaseAiHandler):
         retry=retry_if_exception_type((openai.APIError, openai.APIConnectionError, openai.Timeout)), # No retry on RateLimitError
         stop=stop_after_attempt(OPENAI_RETRIES)
     )
-    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
+    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2, img_path: str = None):
         try:
             resp, finish_reason = None, None
             deployment_id = self.deployment_id
             if self.azure:
                 model = 'azure/' + model
             messages = [{"role": "system", "content": system}, {"role": "user", "content": user}]
+            if img_path:
+                import requests
+                r = requests.get(img_path, allow_redirects=True)
+                if r.status_code == 404:
+                    error_msg = "The image link is not alive. Please repost the image, get a new address, and send the question again."
+                    get_logger().error(error_msg)
+                    return f"{error_msg}", "error"
+                messages[1]["content"] = [{"type": "text", "text": messages[1]["content"]},
+                                          {"type": "image_url", "image_url": {"url": img_path}}]
+
             kwargs = {
                 "model": model,
                 "deployment_id": deployment_id,

pr_agent/servers/github_app.py

@@ -86,8 +86,13 @@ async def handle_comments_on_pr(body: Dict[str, Any],
         return {}
     comment_body = body.get("comment", {}).get("body")
     if comment_body and isinstance(comment_body, str) and not comment_body.lstrip().startswith("/"):
-        get_logger().info("Ignoring comment not starting with /")
-        return {}
+        if '/ask' in comment_body and comment_body.strip().startswith('> ![image]'):
+            comment_body_split = comment_body.split('/ask')
+            comment_body = '/ask' + comment_body_split[1] +'/n' +comment_body_split[0].strip()
+            get_logger().info(f"Reformatting comment_body so command is at the beginning: {comment_body}")
+        else:
+            get_logger().info("Ignoring comment not starting with /")
+            return {}
     disable_eyes = False
     if "issue" in body and "pull_request" in body["issue"] and "url" in body["issue"]["pull_request"]:
         api_url = body["issue"]["pull_request"]["url"]

pr_agent/settings/configuration.toml

@@ -1,7 +1,7 @@
 [config]
-model="gpt-4" # "gpt-4-0125-preview"
-model_turbo="gpt-4-0125-preview"
-fallback_models=["gpt-3.5-turbo-16k"]
+model="gpt-4-turbo" # "gpt-4-0125-preview"
+model_turbo="gpt-4-turbo"
+fallback_models=["gpt-4-0125-preview"]
 git_provider="github"
 publish_output=true
 publish_output_progress=true

pr_agent/tools/pr_questions.py

@@ -56,6 +56,12 @@ class PRQuestions:
         get_logger().debug("Relevant configs", artifacts=relevant_configs)
         if get_settings().config.publish_output:
             self.git_provider.publish_comment("Preparing answer...", is_temporary=True)
+
+        # identify image
+        img_path = self.idenfity_image_in_comment()
+        if img_path:
+            get_logger().debug(f"Image path identified", artifact=img_path)
+
         await retry_with_fallback_models(self._prepare_prediction)
 
         pr_comment = self._prepare_pr_answer()
@@ -71,6 +77,19 @@ class PRQuestions:
             self.git_provider.remove_initial_comment()
         return ""
 
+    def idenfity_image_in_comment(self):
+        img_path = ''
+        if '![image]' in self.question_str:
+            # assuming structure:
+            # /ask question ...  > ![image](img_path)
+            img_path = self.question_str.split('![image]')[1].strip().strip('()')
+            self.vars['img_path'] = img_path
+        elif 'https://' in self.question_str and '.png' in self.question_str:  # direct image link
+            # include https:// in the image path
+            img_path = 'https://' + self.question_str.split('https://')[1]
+            self.vars['img_path'] = img_path
+        return img_path
+
     async def _prepare_prediction(self, model: str):
         self.patches_diff = get_pr_diff(self.git_provider, self.token_handler, model)
         if self.patches_diff:
@@ -86,8 +105,14 @@ class PRQuestions:
         environment = Environment(undefined=StrictUndefined)
         system_prompt = environment.from_string(get_settings().pr_questions_prompt.system).render(variables)
         user_prompt = environment.from_string(get_settings().pr_questions_prompt.user).render(variables)
-        response, finish_reason = await self.ai_handler.chat_completion(model=model, temperature=0.2,
-                                                                        system=system_prompt, user=user_prompt)
+        if 'img_path' in variables:
+            img_path = self.vars['img_path']
+            response, finish_reason = await self.ai_handler.chat_completion(model=model, temperature=0.2,
+                                                                            system=system_prompt, user=user_prompt,
+                                                                            img_path=img_path)
+        else:
+            response, finish_reason = await self.ai_handler.chat_completion(model=model, temperature=0.2,
+                                                                            system=system_prompt, user=user_prompt)
         return response
 
     def _prepare_pr_answer(self) -> str: