Merge pull request #11 from GregorD1A1/dev

Release 0.1.1

agents/executor_agent.py

@@ -15,7 +15,7 @@
 from langchain.prompts import PromptTemplate
 from langchain_community.chat_models import ChatOllama
 from langchain_anthropic import ChatAnthropic
-from utilities.util_functions import check_file_contents, print_formatted, check_application_logs, find_tool_json
+from utilities.util_functions import check_file_contents, print_formatted, check_application_logs
 from utilities.langgraph_common_functions import (call_model, call_tool, ask_human, after_ask_human_condition,
                                                   bad_json_format_msg, multiple_jsons_msg, no_json_msg)
 from utilities.user_input import user_input
@@ -33,19 +33,20 @@ def final_response(test_instruction):
 implemented changes work correctly."""
     print_formatted(test_instruction, color="blue")
 
-stop_sequence = "\n```\n"
-
-#llm = ChatOpenAI(model="gpt-4o", temperature=0).with_config({"run_name": "Executor"})
-llm = ChatAnthropic(model='claude-3-5-sonnet-20240620', temperature=0.2, max_tokens=2000, stop=[stop_sequence]).with_config({"run_name": "Executor"})
 #llm = ChatTogether(model="meta-llama/Llama-3-70b-chat-hf", temperature=0).with_config({"run_name": "Executor"})
 #llm = ChatOllama(model="mixtral"), temperature=0).with_config({"run_name": "Executor"})
+llms = []
+if os.getenv("ANTHROPIC_API_KEY"):
+    llms.append(ChatAnthropic(model='claude-3-5-sonnet-20240620', temperature=0.2, max_tokens=2000, timeout=120).with_config({"run_name": "Executor"}))
+if os.getenv("OPENAI_API_KEY"):
+    llms.append(ChatOpenAI(model="gpt-4o", temperature=0.2, timeout=120).with_config({"run_name": "Executor"}))
 
 
 class AgentState(TypedDict):
     messages: Sequence[BaseMessage]
 
-current_dir = os.path.dirname(os.path.realpath(__file__))
-with open(f"{current_dir}/prompts/executor_system.prompt", "r") as f:
+parent_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
+with open(f"{parent_dir}/prompts/executor_system.prompt", "r") as f:
     system_prompt_template = f.read()
 
 
@@ -82,18 +83,21 @@ def __init__(self, files, work_dir):
 
     # node functions
     def call_model_executor(self, state):
-        #stop_sequence = None
-        state = call_model(state, llm, stop_sequence_to_add=stop_sequence)
-
+        state = call_model(state, llms)
+        last_message = state["messages"][-1]
+        if last_message.type == "ai" and len(last_message.json5_tool_calls) > 1:
+            state["messages"].append(
+                HumanMessage(content=multiple_jsons_msg))
+            print("\nToo many jsons provided, asked to provide one.")
         return state
 
     def call_tool_executor(self, state):
         last_ai_message = state["messages"][-1]
         state = call_tool(state, self.tool_executor)
-        if last_ai_message.tool_call["tool"] == "create_file_with_code":
-            self.files.add(last_ai_message.tool_call["tool_input"]["filename"])
-        if last_ai_message.tool_call["tool"] in ["insert_code", "replace_code", "create_file_with_code"]:
-            state = self.exchange_file_contents(state)
+        for tool_call in last_ai_message.json5_tool_calls:
+            if tool_call["tool"] == "create_file_with_code":
+                self.files.add(tool_call["tool_input"]["filename"])
+        self.exchange_file_contents(state)
         return state
 
     def check_log(self, state):
@@ -124,7 +128,7 @@ def after_agent_condition(self, state):
 
         elif last_message.content in (bad_json_format_msg, multiple_jsons_msg, no_json_msg):
             return "agent"
-        elif last_message.tool_call["tool"] == "final_response":
+        elif last_message.json5_tool_calls[0]["tool"] == "final_response":
             return "check_log" if log_file_path else "human_end_process_confirmation"
         else:
             return "tool"

agents/planner_agent.py

@@ -5,26 +5,32 @@
 from langgraph.graph import END, StateGraph
 from dotenv import load_dotenv, find_dotenv
 from utilities.util_functions import print_formatted, check_file_contents, convert_images, get_joke
-from utilities.langgraph_common_functions import call_model, ask_human, after_ask_human_condition
+from utilities.langgraph_common_functions import ask_human, after_ask_human_condition
 import os
 from langchain_community.chat_models import ChatOllama
 from langchain_anthropic import ChatAnthropic
 
 
 load_dotenv(find_dotenv())
 
-llm = ChatOpenAI(model="gpt-4o", temperature=0.3).with_config({"run_name": "Planer"})
-llm_voter = llm.with_config({"run_name": "Voter"})
+llms_planners = []
+if os.getenv("OPENAI_API_KEY"):
+    llms_planners.append(ChatOpenAI(model="gpt-4o", temperature=0.3, timeout=120).with_config({"run_name": "Planer"}))
+if os.getenv("ANTHROPIC_API_KEY"):
+    llms_planners.append(ChatAnthropic(model='claude-3-5-sonnet-20240620', temperature=0.3, timeout=120).with_config({"run_name": "Planer"}))
 
+llm_planner = llms_planners[0].with_fallbacks(llms_planners[1:])
+# copy planers, but exchange config name
+llm_voter = llm_planner.with_config({"run_name": "Voter"})
 
 class AgentState(TypedDict):
     messages: Sequence[BaseMessage]
     voter_messages: Sequence[BaseMessage]
 
-current_dir = os.path.dirname(os.path.realpath(__file__))
-with open(f"{current_dir}/prompts/planer_system.prompt", "r") as f:
+parent_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
+with open(f"{parent_dir}/prompts/planer_system.prompt", "r") as f:
     planer_system_prompt_template = f.read()
-with open(f"{current_dir}/prompts/voter_system.prompt", "r") as f:
+with open(f"{parent_dir}/prompts/voter_system.prompt", "r") as f:
     voter_system_prompt_template = f.read()
 
 planer_system_message = SystemMessage(content=planer_system_prompt_template)
@@ -37,7 +43,7 @@ def call_planers(state):
     nr_plans = 3
     print(f"\nGenerating plan propositions. While I'm thinking...\n")
     print_formatted(get_joke(), color="red")
-    plan_propositions_messages = llm.batch([messages for _ in range(nr_plans)])
+    plan_propositions_messages = llm_planner.batch([messages for _ in range(nr_plans)])
     for i, proposition in enumerate(plan_propositions_messages):
         state["voter_messages"].append(AIMessage(content="_"))
         state["voter_messages"].append(HumanMessage(content=f"Proposition nr {i+1}:\n\n" + proposition.content))
@@ -56,7 +62,7 @@ def call_planers(state):
 
 def call_model_corrector(state):
     messages = state["messages"]
-    response = llm.invoke(messages)
+    response = llm_planner.invoke(messages)
     print_formatted(response.content)
     state["messages"].append(response)
 
@@ -99,4 +105,4 @@ def planning(task, text_files, image_paths, work_dir):
 if __name__ == "__main__":
     task = "Test task"
     work_dir = os.getenv("WORK_DIR")
-    planning(task, work_dir=work_dir)
+    planning(task, work_dir=work_dir)

agents/researcher_agent.py

@@ -14,7 +14,7 @@
     prepare_list_dir_tool, prepare_see_file_tool, retrieve_files_by_semantic_query
 )
 from rag.retrieval import vdb_available
-from utilities.util_functions import find_tool_json, print_formatted
+from utilities.util_functions import find_tools_json, print_formatted
 from utilities.langgraph_common_functions import (
     call_model, call_tool, ask_human, after_ask_human_condition, bad_json_format_msg, multiple_jsons_msg, no_json_msg
 )
@@ -23,15 +23,17 @@
 
 load_dotenv(find_dotenv())
 mistral_api_key = os.getenv("MISTRAL_API_KEY")
+anthropic_api_key = os.getenv("ANTHROPIC_API_KEY")
+openai_api_key = os.getenv("OPENAI_API_KEY")
 work_dir = os.getenv("WORK_DIR")
 
 
 @tool
 def final_response(files_to_work_on, reference_files, template_images):
-    """That tool outputs list of files executor will need to change and paths to graphical patterns if some.
-    Use that tool only when you 100% sure you found all the files Executor will need to modify.
+    """That tool outputs list of files programmer will need to change and paths to graphical patterns if some.
+    Use that tool only when you 100% sure you found all the files programmer will need to modify.
     If not, do additional research. Include only the files you convinced will be useful.
-    Provide only existing files, do not provide that you'll be implementing.
+    Provide only existing files, do not provide files to be implemented.
 
     tool input:
     :param files_to_work_on: ["List", "of", "existing files", "to potentially introduce", "changes"],
@@ -40,28 +42,27 @@ def final_response(files_to_work_on, reference_files, template_images):
     """
     pass
 
-#stop_sequence = "\n```\n"
-stop_sequence = None
-
-#llm = ChatOpenAI(model="gpt-4o", temperature=0.2)
-llm = ChatAnthropic(model='claude-3-5-sonnet-20240620', temperature=0.2).with_config({"run_name": "Researcher"})
 #llm = ChatOllama(model="gemma2:9b-instruct-fp16")
 #llm = ChatMistralAI(api_key=mistral_api_key, model="mistral-large-latest")
 #llm = Replicate(model="meta/meta-llama-3.1-405b-instruct")
-
+llms = []
+if anthropic_api_key:
+    llms.append(ChatAnthropic(model='claude-3-5-sonnet-20240620', temperature=0.2, timeout=120).with_config({"run_name": "Researcher"}))
+if openai_api_key:
+    llms.append(ChatOpenAI(model="gpt-4o", temperature=0.2, timeout=120).with_config({"run_name": "Researcher"}))
 
 class AgentState(TypedDict):
     messages: Sequence[BaseMessage]
 
 
-current_dir = os.path.dirname(os.path.realpath(__file__))
-with open(f"{current_dir}/prompts/researcher_system.prompt", "r") as f:
+parent_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
+with open(f"{parent_dir}/prompts/researcher_system.prompt", "r") as f:
     system_prompt_template = f.read()
 
 
 # node functions
 def call_model_researcher(state):
-    state = call_model(state, llm, stop_sequence_to_add=stop_sequence)
+    state = call_model(state, llms)
     return state
 
 
@@ -71,7 +72,7 @@ def after_agent_condition(state):
 
     if last_message.content in (bad_json_format_msg, multiple_jsons_msg, no_json_msg):
         return "agent"
-    elif last_message.tool_call["tool"] == "final_response":
+    elif last_message.json5_tool_calls[0]["tool"] == "final_response":
         return "human"
     else:
         return "tool"
@@ -113,7 +114,7 @@ def research_task(self, task):
         inputs = {"messages": [SystemMessage(content=system_message), HumanMessage(content=f"Go")]}
         researcher_response = self.researcher.invoke(inputs, {"recursion_limit": 100})["messages"][-2]
 
-        tool_json = find_tool_json(researcher_response.content)
+        tool_json = find_tools_json(researcher_response.content)[0]
         text_files = set(tool_json["tool_input"]["files_to_work_on"] + tool_json["tool_input"]["reference_files"])
         image_paths = tool_json["tool_input"]["template_images"]
 

clean_coder_pipeline.py

@@ -7,7 +7,8 @@
 from agents.executor_agent import Executor
 import os
 from utilities.user_input import user_input
-
+import warnings
+warnings.filterwarnings("ignore", category=DeprecationWarning)
 
 
 def run_clean_coder_pipeline(task, work_dir):

docker-compose.yml

@@ -0,0 +1,40 @@
+services:
+  project_manager:
+    build:
+      context: .
+      dockerfile: docker/Dockerfile
+    container_name: project_manager
+    environment:
+      - WORK_DIR=/work_dir
+      - OPENAI_API_KEY=${OPENAI_API_KEY}
+      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
+      - TODOIST_API_KEY=${TODOIST_API_KEY}
+      - TODOIST_PROJECT_ID=${TODOIST_PROJECT_ID}
+      - COHERE_API_KEY=${COHERE_API_KEY}
+      - LOG_FILE=${LOG_FILE:-}
+    volumes:
+      - .:/Clean_Coder
+      - ${WORK_DIR}:/work_dir
+    # Uncomment (linux) or adjust (other systems) the following line to use microphone
+    # devices:
+    #   - "/dev/snd:/dev/snd"
+    command: python project_manager.py
+
+  clean_coder_pipeline:
+    build:
+      context: .
+      dockerfile: docker/Dockerfile
+    container_name: clean_coder_pipeline
+    environment:
+      - WORK_DIR=/work_dir
+      - OPENAI_API_KEY=${OPENAI_API_KEY}
+      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
+      - COHERE_API_KEY=${COHERE_API_KEY}
+      - LOG_FILE=${LOG_FILE:-}
+    volumes:
+      - .:/Clean_Coder
+      - ${WORK_DIR}:/work_dir
+    # Uncomment (linux) or adjust (other systems) the following line to use microphone
+    # devices:
+    #   - "/dev/snd:/dev/snd"
+    command: python clean_coder_pipeline.py

docker/.dockerignore

@@ -0,0 +1,24 @@
+.env
+.idea/
+.cache/
+__pycache__/
+env/
+venv/
+*.pyc
+*.pyo
+*.pyd
+.Python
+pip-log.txt
+pip-delete-this-directory.txt
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.log
+.git
+.mypy_cache
+.pytest_cache
+.hypothesis

docker/Dockerfile

@@ -0,0 +1,30 @@
+FROM python:3.10-slim
+
+# Set working directory
+WORKDIR /Clean_Coder
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    linux-headers-generic \
+    libportaudio2 \         
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements file
+COPY requirements.txt .
+
+# Install dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the application code
+COPY . .
+
+# Create workdir
+RUN mkdir /work_dir
+
+# Set environment variables
+ENV PYTHONUNBUFFERED=1
+ENV WORK_DIR=/work_dir
+
+# Default command
+CMD ["python", "project_manager.py"]