[Bug]: KeyError: 'user_feedback_qa'

[cranyy]

Version

VisualStudio Code extension

Operating System

Windows 10

What happened?

[Pythagora] Stopping Pythagora due to error:

File `core/cli/main.py`, line 37, in run_project
    success = await orca.run()
File `core/agents/orchestrator.py`, line 67, in run
    response = await agent.run()
File `core/agents/code_monkey.py`, line 32, in run
    return await self.implement_changes()
File `core/agents/code_monkey.py`, line 63, in implement_changes
    user_feedback_qa = iterations[-1]["user_feedback_qa"]
KeyError: 'user_feedback_qa'
 
(env) E:\Project\gpt-pilot>
```    ----------happens when i answer no no no no multiple times on some stupid suggestions, cant undo cant go back any steps always leads to the above

[DaddyWozBucks]

Same issue using repository except it happened without any inputs during code review. Restarting immediately fails again with the same message

[Badlee2020]

same here

[DaveTacker]

Seems to be working again after making this change to core/agents/code_monkey.py L60:

if len(iterations) > 0:
    if "description" in iterations[-1]:
        instructions = iterations[-1]["description"]
    if "user_feedback" in iterations[-1]:
        user_feedback = iterations[-1]["user_feedback"]
    if "user_feedback_qa" in iterations[-1]:
        user_feedback_qa = iterations[-1]["user_feedback_qa"]

[DrivenIdeaLab]

Resolved., Similar resolution to @DaveTacker

`from os.path import basename

from pydantic import BaseModel, Field

from core.agents.base import BaseAgent
from core.agents.convo import AgentConvo
from core.agents.response import AgentResponse, ResponseType
from core.config import DESCRIBE_FILES_AGENT_NAME
from core.llm.parser import JSONParser, OptionalCodeBlockParser
from core.log import get_logger

log = get_logger(name)

class FileDescription(BaseModel):
summary: str = Field(
description="Detailed description summarized what the file is about, and what the major classes, functions, elements or other functionality is implemented."
)
references: list[str] = Field(
description="List of references the file imports or includes (only files local to the project), where each element specifies the project-relative path of the referenced file, including the file extension."
)

class CodeMonkey(BaseAgent):
agent_type = "code-monkey"
display_name = "Code Monkey"

async def run(self) -> AgentResponse:
    if self.prev_response and self.prev_response.type == ResponseType.DESCRIBE_FILES:
        return await self.describe_files()
    else:
        return await self.implement_changes()

async def implement_changes(self) -> AgentResponse:
    file_name = self.step["save_file"]["path"]

    current_file = await self.state_manager.get_file_by_path(file_name)
    file_content = current_file.content.content if current_file else ""

    task = self.current_state.current_task

    if self.prev_response and self.prev_response.type == ResponseType.CODE_REVIEW_FEEDBACK:
        attempt = self.prev_response.data["attempt"] + 1
        feedback = self.prev_response.data["feedback"]
        log.debug(f"Fixing file {file_name} after review feedback: {feedback} ({attempt}. attempt)")
        await self.send_message(f"Reworking changes I made to {file_name} ...")
    else:
        log.debug(f"Implementing file {file_name}")
        await self.send_message(f"{'Updating existing' if file_content else 'Creating new'} file {file_name} ...")
        self.next_state.action = (
            f'Update file "{basename(file_name)}"' if file_content else f'Create file "{basename(file_name)}"'
        )
        attempt = 1
        feedback = None

    iterations = self.current_state.iterations
    user_feedback = None
    user_feedback_qa = None
    llm = self.get_llm()
    if iterations:
        instructions = iterations[-1].get("description")
        user_feedback = iterations[-1].get("user_feedback")
        user_feedback_qa = iterations[-1].get("user_feedback_qa")
    else:
        instructions = self.current_state.current_task["instructions"]

    convo = AgentConvo(self).template(
        "implement_changes",
        file_name=file_name,
        file_content=file_content,
        instructions=instructions,
        user_feedback=user_feedback,
        user_feedback_qa=user_feedback_qa,
    )
    if feedback:
        convo.assistant(f"```\n{self.prev_response.data['new_content']}\n```\n").template(
            "review_feedback",
            content=self.prev_response.data["approved_content"],
            original_content=file_content,
            rework_feedback=feedback,
        )

    response: str = await llm(convo, temperature=0, parser=OptionalCodeBlockParser())
    # FIXME: provide a counter here so that we don't have an endless loop here
    return AgentResponse.code_review(self, file_name, task["instructions"], file_content, response, attempt)

async def describe_files(self) -> AgentResponse:
    llm = self.get_llm(DESCRIBE_FILES_AGENT_NAME)
    to_describe = {
        file.path: file.content.content for file in self.current_state.files if not file.meta.get("description")
    }

    for file in self.next_state.files:
        content = to_describe.get(file.path)
        if content is None:
            continue

        if content == "":
            file.meta = {
                **file.meta,
                "description": "Empty file",
                "references": [],
            }
            continue

        log.debug(f"Describing file {file.path}")
        await self.send_message(f"Describing file {file.path} ...")

        convo = (
            AgentConvo(self)
            .template(
                "describe_file",
                path=file.path,
                content=content,
            )
            .require_schema(FileDescription)
        )
        llm_response: FileDescription = await llm(convo, parser=JSONParser(spec=FileDescription))

        file.meta = {
            **file.meta,
            "description": llm_response.summary,
            "references": llm_response.references,
        }
    return AgentResponse.done(self)

`

[RoseSamaras]

Here is the whole corrected code_monkey.py in gpt-pilot/core/agents

from os.path import basename

from pydantic import BaseModel, Field

from core.agents.base import BaseAgent
from core.agents.convo import AgentConvo
from core.agents.response import AgentResponse, ResponseType
from core.config import DESCRIBE_FILES_AGENT_NAME
from core.llm.parser import JSONParser, OptionalCodeBlockParser
from core.log import get_logger

log = get_logger(name)

class FileDescription(BaseModel):
summary: str = Field(
description="Detailed description summarized what the file is about, and what the major classes, functions, elements or other functionality is implemented."
)
references: list[str] = Field(
description="List of references the file imports or includes (only files local to the project), where each element specifies the project-relative path of the referenced file, including the file extension."
)

class CodeMonkey(BaseAgent):
agent_type = "code-monkey"
display_name = "Code Monkey"

async def run(self) -> AgentResponse:
    if self.prev_response and self.prev_response.type == ResponseType.DESCRIBE_FILES:
        return await self.describe_files()
    else:
        return await self.implement_changes()

async def implement_changes(self) -> AgentResponse:
    file_name = self.step["save_file"]["path"]

    current_file = await self.state_manager.get_file_by_path(file_name)
    file_content = current_file.content.content if current_file else ""

    task = self.current_state.current_task

    if self.prev_response and self.prev_response.type == ResponseType.CODE_REVIEW_FEEDBACK:
        attempt = self.prev_response.data["attempt"] + 1
        feedback = self.prev_response.data["feedback"]
        log.debug(f"Fixing file {file_name} after review feedback: {feedback} ({attempt}. attempt)")
        await self.send_message(f"Reworking changes I made to {file_name} ...")
    else:
        log.debug(f"Implementing file {file_name}")
        await self.send_message(f"{'Updating existing' if file_content else 'Creating new'} file {file_name} ...")
        self.next_state.action = (
            f'Update file "{basename(file_name)}"' if file_content else f'Create file "{basename(file_name)}"'
        )
        attempt = 1
        feedback = None

    iterations = self.current_state.iterations
    user_feedback = None
    user_feedback_qa = None
    llm = self.get_llm()
    if iterations:
        if "description" in iterations[-1]:
            instructions = iterations[-1]["description"]
        if "user_feedback" in iterations[-1]:
            user_feedback = iterations[-1]["user_feedback"]
        if "user_feedback_qa" in iterations[-1]:
            user_feedback_qa = iterations[-1]["user_feedback_qa"]
    else:
        instructions = self.current_state.current_task["instructions"]

    convo = AgentConvo(self).template(
        "implement_changes",
        file_name=file_name,
        file_content=file_content,
        instructions=instructions,
        user_feedback=user_feedback,
        user_feedback_qa=user_feedback_qa,
    )
    if feedback:
        convo.assistant(f"```\n{self.prev_response.data['new_content']}\n```\n").template(
            "review_feedback",
            content=self.prev_response.data["approved_content"],
            original_content=file_content,
            rework_feedback=feedback,
        )

    response: str = await llm(convo, temperature=0, parser=OptionalCodeBlockParser())
    # FIXME: provide a counter here so that we don't have an endless loop here
    return AgentResponse.code_review(self, file_name, task["instructions"], file_content, response, attempt)

async def describe_files(self) -> AgentResponse:
    llm = self.get_llm(DESCRIBE_FILES_AGENT_NAME)
    to_describe = {
        file.path: file.content.content for file in self.current_state.files if not file.meta.get("description")
    }

    for file in self.next_state.files:
        content = to_describe.get(file.path)
        if content is None:
            continue

        if content == "":
            file.meta = {
                **file.meta,
                "description": "Empty file",
                "references": [],
            }
            continue

        log.debug(f"Describing file {file.path}")
        await self.send_message(f"Describing file {file.path} ...")

        convo = (
            AgentConvo(self)
            .template(
                "describe_file",
                path=file.path,
                content=content,
            )
            .require_schema(FileDescription)
        )
        llm_response: FileDescription = await llm(convo, parser=JSONParser(spec=FileDescription))

        file.meta = {
            **file.meta,
            "description": llm_response.summary,
            "references": llm_response.references,
        }
    return AgentResponse.done(self)

[shakib5326]

`from os.path import basename
from pydantic import BaseModel, Field
from core.agents.base import BaseAgent
from core.agents.convo import AgentConvo
from core.agents.response import AgentResponse, ResponseType
from core.config import DESCRIBE_FILES_AGENT_NAME
from core.llm.parser import JSONParser, OptionalCodeBlockParser
from core.log import get_logger

log = get_logger(name)

class FileDescription(BaseModel):
summary: str = Field(
description="Detailed description summarized what the file is about, and what the major classes, functions, elements or other functionality is implemented."
)
references: list[str] = Field(
description="List of references the file imports or includes (only files local to the project), where each element specifies the project-relative path of the referenced file, including the file extension."
)

class CodeMonkey(BaseAgent):
agent_type = "code-monkey"
display_name = "Code Monkey"

async def run(self) -> AgentResponse:
    if self.prev_response and self.prev_response.type == ResponseType.DESCRIBE_FILES:
        return await self.describe_files()
    else:
        return await self.implement_changes()

async def implement_changes(self) -> AgentResponse:
    file_name = self.step["save_file"]["path"]

    current_file = await self.state_manager.get_file_by_path(file_name)
    file_content = current_file.content.content if current_file else ""

    task = self.current_state.current_task

    if self.prev_response and self.prev_response.type == ResponseType.CODE_REVIEW_FEEDBACK:
        attempt = self.prev_response.data["attempt"] + 1
        feedback = self.prev_response.data["feedback"]
        log.debug(f"Fixing file {file_name} after review feedback: {feedback} ({attempt}. attempt)")
        await self.send_message(f"Reworking changes I made to {file_name} ...")
    else:
        log.debug(f"Implementing file {file_name}")
        await self.send_message(f"{'Updating existing' if file_content else 'Creating new'} file {file_name} ...")
        self.next_state.action = (
            f'Update file "{basename(file_name)}"' if file_content else f'Create file "{basename(file_name)}"'
        )
        attempt = 1
        feedback = None

    iterations = self.current_state.iterations
    user_feedback = None
    user_feedback_qa = None
    llm = self.get_llm()
    if iterations:
        last_iteration = iterations[-1]
        instructions = last_iteration.get("description", "")
        user_feedback = last_iteration.get("user_feedback", None)
        user_feedback_qa = last_iteration.get("user_feedback_qa", None)
    else:
        instructions = self.current_state.current_task["instructions"]

    convo = AgentConvo(self).template(
        "implement_changes",
        file_name=file_name,
        file_content=file_content,
        instructions=instructions,
        user_feedback=user_feedback,
        user_feedback_qa=user_feedback_qa,
    )
    if feedback:
        convo.assistant(f"```\n{self.prev_response.data['new_content']}\n```\n").template(
            "review_feedback",
            content=self.prev_response.data["approved_content"],
            original_content=file_content,
            rework_feedback=feedback,
        )

    response: str = await llm(convo, temperature=0, parser=OptionalCodeBlockParser())
    # FIXME: provide a counter here so that we don't have an endless loop here
    return AgentResponse.code_review(self, file_name, task["instructions"], file_content, response, attempt)

async def describe_files(self) -> AgentResponse:
    llm = self.get_llm(DESCRIBE_FILES_AGENT_NAME)
    to_describe = {
        file.path: file.content.content for file in self.current_state.files if not file.meta.get("description")
    }

    for file in self.next_state.files:
        content = to_describe.get(file.path)
        if content is None:
            continue

        if content == "":
            file.meta = {
                **file.meta,
                "description": "Empty file",
                "references": [],
            }
            continue

        log.debug(f"Describing file {file.path}")
        await self.send_message(f"Describing file {file.path} ...")

        convo = (
            AgentConvo(self)
            .template(
                "describe_file",
                path=file.path,
                content=content,
            )
            .require_schema(FileDescription)
        )
        llm_response: FileDescription = await llm(convo, parser=JSONParser(spec=FileDescription))

        file.meta = {
            **file.meta,
            "description": llm_response.summary,
            "references": llm_response.references,
        }
    return AgentResponse.done(self)

`

This version of the CodeMonkey class ensures that the keys description, user_feedback, and user_feedback_qa are accessed safely using the get method, preventing KeyError exceptions if these keys are missing.

[PNdlovu]

This is strange because I had the same solution from chatgtp but it didn't work and even after copying your code still does not work. pythagora won't load the window to upload or create a new application. I wonder how its gonna be before the bug is ironed out. I have tried this in both windows 10 and 11. please help mybe am doing something wrong

[DaveTacker]

Is it exactly the same error?

…

On Thu, Jun 27, 2024, 7:34 AM Philani ***@***.***> wrote: This is strange because I had the same solution from chatgtp but it didn't work and even after copying your code still does not work. pythagora won't load the window to upload or create a new application. I wonder how its gonna be before the bug is ironed out. I have tried this in both windows 10 and 11. please help mybe am doing something wrong — Reply to this email directly, view it on GitHub <#1025 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAHXDSJO22FHCZEH3XJOHK3ZJREJNAVCNFSM6AAAAABJSFIZFCVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDCOJVGI4DKNBVGQ> . You are receiving this because you were mentioned.Message ID: ***@***.***>