Merge pull request #35 from Grigorij-Dudnik/dev

Dev

docker-compose.yml

@@ -14,7 +14,7 @@ services:
       - LOG_FILE=${LOG_FILE:-}
     volumes:
       - .:/Clean_Coder
-      - ${WORK_DIR}:/work_dir
+      - ${WORK_DIR:-.}:/work_dir
     # Uncomment (linux) or adjust (other systems) the following line to use microphone
     # devices:
     #   - "/dev/snd:/dev/snd"
@@ -33,7 +33,7 @@ services:
       - LOG_FILE=${LOG_FILE:-}
     volumes:
       - .:/Clean_Coder
-      - ${WORK_DIR}:/work_dir
+      - ${WORK_DIR:-.}:/work_dir
     # Uncomment (linux) or adjust (other systems) the following line to use microphone
     # devices:
     #   - "/dev/snd:/dev/snd"

manager.py

@@ -11,13 +11,12 @@
     add_todoist_envs()
 
 from typing import TypedDict, Sequence
-from langchain_core.messages import BaseMessage, HumanMessage
+from langchain_core.messages import BaseMessage, HumanMessage, ToolMessage
 from langchain_core.load import dumps
 from langgraph.graph import StateGraph
-from dotenv import load_dotenv, find_dotenv
 from src.tools.tools_project_manager import add_task, modify_task, finish_project_planning, reorder_tasks
 from src.tools.tools_coder_pipeline import prepare_list_dir_tool, prepare_see_file_tool, ask_human_tool
-from src.utilities.manager_utils import actualize_tasks_list_and_progress_description, create_todoist_project_if_needed, get_manager_messages
+from src.utilities.manager_utils import actualize_tasks_list_and_progress_description, setup_todoist_project_if_needed, get_manager_messages
 from src.utilities.langgraph_common_functions import call_model, call_tool, multiple_tools_msg, no_tools_msg, empty_message_msg
 from src.utilities.start_project_functions import set_up_dot_clean_coder_dir
 from src.utilities.util_functions import join_paths
@@ -41,15 +40,14 @@ def __init__(self):
         self.manager = self.setup_workflow()
         self.saved_messages_path = join_paths(self.work_dir, ".clean_coder/manager_messages.json")
 
-    # node functions
     def call_model_manager(self, state):
         self.save_messages_to_disk(state)
         state = call_model(state, self.llms)
         state = self.cut_off_context(state)
         state = call_tool(state, self.tools)
         messages = [msg for msg in state["messages"] if msg.type == "ai"]
         last_ai_message = messages[-1]
-        if not last_ai_message.content:
+        if not last_ai_message.content and not last_ai_message.tool_calls:
             state["messages"].pop()
             state["messages"].append(HumanMessage(content=empty_message_msg))
         elif len(last_ai_message.tool_calls) == 0:
@@ -111,13 +109,11 @@ def setup_workflow(self):
         manager_workflow.add_node("agent", self.call_model_manager)
         manager_workflow.set_entry_point("agent")
         manager_workflow.add_edge("agent", "agent")
-        #manager_workflow.add_conditional_edges("agent", self.after_agent_condition)
         return manager_workflow.compile()
 
-
     def run(self):
         print_formatted("😀 Hello! I'm Manager agent. Let's plan your project together!", color="green")
-        create_todoist_project_if_needed()
+        setup_todoist_project_if_needed()
 
         messages = get_manager_messages(self.saved_messages_path)
         inputs = {"messages": messages}

readme.md

@@ -34,26 +34,28 @@ or (recommended) check detailed instructions [how to start in documentation](htt
 You can also [deploy with Docker](https://clean-coder.dev/quick_start/run_with_docker/).
 
 
+## 📺 Demo videos
+
+Create an entire web app ~~with~~ by Clean Coder:
+
+<div align="center">
+<a href="https://youtu.be/aNpB-Tw-YPw" title="Greg's Tech video">
+  <img src="https://img.youtube.com/vi/aNpB-Tw-YPw/maxresdefault.jpg" width="600" alt="Demo video">
+</a>
+</div>
+
+
 ## ✨ Key advantages:
 
 - Get project supervised by [Manager agent](https://clean-coder.dev/quick_start/manager/) with thoroughly-described tasks organized in Todoist, just like with a human scrum master.
 - Watch tasks executed one by one by [Programming agents](https://clean-coder.dev/quick_start/programmer_pipeline/), with a well-designed context pipeline and advanced techniques for enhanced intelligence.
-- Allow AI to see fronted it creates using [frontend feedback feature](https://clean-coder.dev/features/frontend_feedback/). At the day of writing no other AI coder has that.
+- Allow AI to see frontend it creates with [frontend feedback feature](https://clean-coder.dev/features/frontend_feedback/). At the day of writing no other AI coder has that feature.
 - Create a [frontend based on images](https://clean-coder.dev/features/working_with_images/) with designs.
 - [Speak to Clean Coder](https://clean-coder.dev/features/talk_to_cc/) instead of writing.
 - Automatic file linting prevents from introducing incorrect changes and [log check for self-debug](https://clean-coder.dev/advanced_features_installation/logs_check/).
 - File Researcher agent with (but not only) [RAG tool](https://clean-coder.dev/advanced_features_installation/similarity_search_for_researcher/) for effective searching of project files.
 - [Sensitive files protection](https://clean-coder.dev/features/sensitive_file_protection/) from being watched by AI.
 
-## 📺 Demo videos
-
-Create an entire web app ~~with~~ by Clean Coder:
-
-<div align="center">
-<a href="https://youtu.be/aNpB-Tw-YPw" title="Greg's Tech video">
-  <img src="https://img.youtube.com/vi/aNpB-Tw-YPw/maxresdefault.jpg" width="600" alt="Demo video">
-</a>
-</div>
 
 ## ⛓️‍💥 Something got broken?
 
@@ -63,7 +65,7 @@ Report bugs or propose new features for Clean Coder on our [Discord](https://dis
 <br>
 <div align="center">
   <a href="https://github.com/Grigorij-Dudnik/Clean-Coder-AI/graphs/contributors">
-    <img src="https://contrib.rocks/image?repo=Grigorij-Dudnik/Clean-Coder-AI" />
+    <img src="https://contrib.rocks/image?repo=Grigorij-Dudnik/Clean-Coder-AI&1" />
   </a>
 </div>
 <br>

requirements.txt

@@ -3,7 +3,6 @@ langchain-core==0.3.15
 langchain_community==0.3.1
 langgraph==0.2.48
 langgraph-checkpoint==2.0.4
-langgraph-checkpoint-sqlite==2.0.1
 python-dotenv==1.0.1
 langchain-anthropic==0.2.1
 langchain-openai==0.2.1
@@ -29,4 +28,5 @@ pytest==8.3.4
 pytest-cov==6.0.0
 pyright==1.1.390
 ruff==0.8.2
-httpx==0.27.2
+httpx==0.27.2
+questionary==2.1.0

single_task_coder.py

@@ -10,7 +10,7 @@
 from src.agents.planner_agent import planning
 from src.agents.executor_agent import Executor
 from src.agents.debugger_agent import Debugger
-from src.agents.frontend_feedback import write_screenshot_codes, execute_screenshot_codes
+from src.agents.frontend_feedback import write_screenshot_codes
 import os
 from src.utilities.user_input import user_input
 from src.utilities.print_formatters import print_formatted
@@ -37,25 +37,19 @@ def run_clean_coder_pipeline(task, work_dir):
             future = executor_thread.submit(write_screenshot_codes, task, plan, work_dir)
             file_paths = executor.do_task(task, plan)
             playwright_codes = future.result()
-        if playwright_codes:
-            print_formatted("Making screenshots, please wait a while...", color="light_blue")
-            first_vfeedback_screenshots_msg = execute_screenshot_codes(playwright_codes)
-        else:
-            first_vfeedback_screenshots_msg = None
     else:
         file_paths = executor.do_task(task, plan)
-        first_vfeedback_screenshots_msg = None
 
-    human_message = user_input("Please test app and provide commentary if debugging/additional refinement is needed.")
+    human_message = user_input("Please test app and provide commentary if debugging/additional refinement is needed. ")
     if human_message in ['o', 'ok']:
         return
     debugger = Debugger(
-        file_paths, work_dir, human_message,image_paths,  first_vfeedback_screenshots_msg, playwright_codes)
+        file_paths, work_dir, human_message,image_paths,  playwright_codes)
     debugger.do_task(task, plan)
 
 
 if __name__ == "__main__":
     work_dir = os.getenv("WORK_DIR")
     set_up_dot_clean_coder_dir(work_dir)
-    task = user_input("Provide task to be executed.")
+    task = user_input("Provide task to be executed. ")
     run_clean_coder_pipeline(task, work_dir)

src/agents/debugger_agent.py

@@ -47,7 +47,7 @@ class AgentState(TypedDict):
 
 
 class Debugger():
-    def __init__(self, files, work_dir, human_feedback, image_paths, vfeedback_screenshots_msg=None, playwright_code=None):
+    def __init__(self, files, work_dir, human_feedback, image_paths, playwright_code=None):
         self.work_dir = work_dir
         self.tools = prepare_tools(work_dir)
         self.llms = init_llms(self.tools, "Debugger")
@@ -57,7 +57,6 @@ def __init__(self, files, work_dir, human_feedback, image_paths, vfeedback_scree
         self.files = files
         self.images = convert_images(image_paths)
         self.human_feedback = human_feedback
-        self.visual_feedback = vfeedback_screenshots_msg
         self.playwright_code = playwright_code
 
         # workflow definition
@@ -82,11 +81,8 @@ def __init__(self, files, work_dir, human_feedback, image_paths, vfeedback_scree
     # node functions
     def call_model_debugger(self, state):
         state = call_model(state, self.llms)
-        state = self.call_tool_debugger(state)
-        return state
-
-    def call_tool_debugger(self, state):
         state = call_tool(state, self.tools)
+
         messages = [msg for msg in state["messages"] if msg.type == "ai"]
         last_ai_message = messages[-1]
         if len(last_ai_message.tool_calls) > 1:
@@ -95,6 +91,10 @@ def call_tool_debugger(self, state):
             state["messages"].append(HumanMessage(content=multiple_tools_msg))
         elif len(last_ai_message.tool_calls) == 0:
             state["messages"].append(HumanMessage(content=no_tools_msg))
+
+        for tool_call in last_ai_message.tool_calls:
+            if tool_call["name"] == "create_file_with_code":
+                self.files.add(tool_call["args"]["filename"])
         state = exchange_file_contents(state, self.files, self.work_dir)
         return state
 
@@ -154,8 +154,10 @@ def do_task(self, task, plan):
             HumanMessage(content=self.images),
             HumanMessage(content=f"Human feedback: {self.human_feedback}"),
         ]}
-        if self.visual_feedback:
-            inputs["messages"].append(self.visual_feedback)
+        if self.playwright_code:
+            print_formatted("Making screenshots, please wait a while...", color="light_blue")
+            screenshot_msg = execute_screenshot_codes(self.playwright_code)
+            inputs["messages"].append(screenshot_msg)
         self.debugger.invoke(inputs, {"recursion_limit": 150})
 
 

src/agents/executor_agent.py

@@ -26,7 +26,7 @@ def final_response_executor(test_instruction):
 tool input:
 :param test_instruction: write detailed instruction for human what actions he need to do in order to check if
 implemented changes work correctly."""
-    print_formatted(content=test_instruction, color="blue")
+    pass
 
 
 class AgentState(TypedDict):
@@ -53,13 +53,10 @@ def __init__(self, files, work_dir):
         executor_workflow = StateGraph(AgentState)
 
         executor_workflow.add_node("agent", self.call_model_executor)
-        executor_workflow.add_node("tool", self.call_tool_executor)
         executor_workflow.add_node("human_help", agent_looped_human_help)
 
         executor_workflow.set_entry_point("agent")
 
-        # executor_workflow.add_edge("agent", "checker")
-        executor_workflow.add_edge("tool", "agent")
         executor_workflow.add_edge("human_help", "agent")
         executor_workflow.add_conditional_edges("agent", self.after_agent_condition)
 
@@ -68,18 +65,15 @@ def __init__(self, files, work_dir):
     # node functions
     def call_model_executor(self, state):
         state = call_model(state, self.llms)
+        state = call_tool(state, self.tools)
         messages = [msg for msg in state["messages"] if msg.type == "ai"]
         last_ai_message = messages[-1]
         if len(last_ai_message.tool_calls) > 1:
             for tool_call in last_ai_message.tool_calls:
                 state["messages"].append(ToolMessage(content="too much tool calls", tool_call_id=tool_call["id"]))
             state["messages"].append(HumanMessage(content=multiple_tools_msg))
-        return state
-
-    def call_tool_executor(self, state):
-        state = call_tool(state, self.tools)
-        messages = [msg for msg in state["messages"] if msg.type == "ai"]
-        last_ai_message = messages[-1]
+        elif len(last_ai_message.tool_calls) == 0:
+            state["messages"].append(HumanMessage(content=no_tools_msg))
         for tool_call in last_ai_message.tool_calls:
             if tool_call["name"] == "create_file_with_code":
                 self.files.add(tool_call["args"]["filename"])
@@ -93,12 +87,10 @@ def after_agent_condition(self, state):
 
         if bad_tool_call_looped(state):
             return "human_help"
-        elif last_message.content in (multiple_tools_msg, no_tools_msg):
-            return "agent"
-        elif last_message.tool_calls[0]["name"] == "final_response_executor":
+        elif len(last_message.tool_calls) > 0 and last_message.tool_calls[0]["name"] == "final_response_executor":
             return END
         else:
-            return "tool"
+            return "agent"
 
     # just functions
     def do_task(self, task, plan):

src/agents/frontend_feedback.py

@@ -44,7 +44,7 @@ class ScreenshotCodingStructure(BaseModel):
         description="If you have missing info about some endpoint/selector/other important element name, ask about it here. If everything clear, questions are not needed."
     )
     screenshot_code: str = Field(description="""
-    Provide here your playwright code for a screenshot or write "No screenshot needed".
+    Provide here your playwright code for a screenshot. If screenshot is not needed for that task write exactly "No screenshot needed".
     """)
 
 

src/agents/planner_agent.py

@@ -91,7 +91,7 @@ def call_planer(state):
 
 
 def ask_human_planner(state):
-    human_message = user_input("Type (o)k if you accept or provide commentary.")
+    human_message = user_input("Type (o)k if you accept or provide commentary. ")
     if human_message in ['o', 'ok']:
         state["messages"].append(HumanMessage(content="Approved by human"))
     else:
@@ -135,7 +135,7 @@ def planning(task, text_files, image_paths, work_dir):
     print_formatted("📈 Planner here! Create plan of changes with me!", color="light_blue")
     file_contents = check_file_contents(text_files, work_dir, line_numbers=False)
     images = convert_images(image_paths)
-    message_content_without_imgs = f"Task: {task},\n\nFiles:\n{file_contents}"
+    message_content_without_imgs = f"Task: {task},\n\n###\n\nFiles:\n{file_contents}"
     message_without_imgs = HumanMessage(content=message_content_without_imgs)
     message_images = HumanMessage(content=images)
 

src/prompts/manager_system.prompt

@@ -8,16 +8,19 @@ Do not create/modify tasks without watching project files first. Do not add new
 Tasks you are creating are always very concrete, showing programmer how exactly and with which tools he can implement the change. If you unsure which technologies/resources to use, ask human before creating/modifying task.
 Avoid creating flaky tasks, where it's unclear how to do task and if it is needed at all.
 
-Make good file research before adding task to understand, how to implement task the best and to describe it in all details. In case if something doesn't work, make file research to undestand why it doesn't work and be able to provide exact guidelnes in the task.
+Never make up information you don't know in task description. Ask human or make file research to get info.
+
+Make good file research before adding task to understand, how to implement task the best and to describe it in all details.
 
 When you need to decide about introducing new technology into the project, consult it with human first. 
 
 Always absolutely execute orders of a human.
 
-Here is description of the project you work on:
+Here is description of changes in the project you work on:
 '''
-{project_description}
+{project_plan}
 '''
+Some of the changes may be already implemented, some not.
 
 Some important project informations and rules:
 '''

src/prompts/planer_system.prompt

@@ -6,16 +6,22 @@ Plan should not include library installation or tests or anything else unrelated
 At every your message, you providing proposition of all changes, not just some. Never imagine files you have 
 not provided in context.
 
+If advanced logic is required, plan logic algorithm before proposing code chages.
+
 Readability is a priority - write your code to be readable and minimalistic.
+Follow DRY (Don't Repeat Yourself) rule.
+Give variables names that makes sense.
 
-If you not sure how to implement given task - do not improvise, just say that you don't know. If you feel you miss some important files needed to implement plan - just say it.
+If you not sure how to implement given task - do not improvise, just say that you don't know. If you feel you miss some important files or information needed to implement plan - just say it.
 
 Do not rewrite full code, instead only write changes and point places where they need to be inserted. 
-Show with pluses (+) and minuses (-), where you want to add/remove/replace code. Like:
-```diff
-- self.id_number = str(ObjectId())
-+ self.user_id = str(ObjectId())
-+ self.email = email
+Show with pluses (+) and minuses (-), where you want to add/remove/replace code. provide code snippets in your response looking like:
+
+```filename.extension
+- self.line_to_remove = str(ObjectId())
++ self.line_to_add_on_its_place = str(ObjectId())
+self.line_to_stay_as_it_is = ObjectId(var)
++ self.more_lines_to_add = email
 ```
 
 When adjusting your plan with user feedback, always provide complete version of plan. Do not provide unnecesary elements. Do not reference to previous version of plan - write it from zero instead.

src/tools/rag/retrieval.py

@@ -24,14 +24,13 @@ def get_collection():
     return False
 
 
-collection = get_collection()
-
-
 def vdb_available():
     return True if get_collection() else False
 
 
 def retrieve(question):
+    # collection should be initialized once, in the class init
+    collection = get_collection()
     retrieval = collection.query(query_texts=[question], n_results=8)
     reranked_docs = cohere_client.rerank(
         query=question,
@@ -50,6 +49,7 @@ def retrieve(question):
 
     return response
 
+
 if __name__ == "__main__":
     question = "Common styles, used in the main page"
     results = retrieve(question)