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Khoangothe features add to vector store #8
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…but needs import fixes
…tructure as long as PGVECTOR_CONNECTION_STRING & GITHUB_TOKEN env vars are set
…rubber_ducker & tech_lead
…cess to fetch full files directly from a github branch based on file names - these full files are then passed into the prompts of the Rubber Ducker & Tech Lead Agents
…o full file contents & directory structure
…: adding discord-bot env token to main .env in root & running 'docker-compose --profile discord run --rm discord-bot'
…cord bot query runs to completion
…d back to the user via chat
… relevant file names, repo name & branch name)
…y & replies to user
…t or thread - runs to completion in chat
…o rubber_duck agent next
…d bot runs to completion with custom repo name & branch name
…ter than nodemon hanging
…l be logged within the same thread
…js server should log errors without restarting
…nnels - also added a cool down logic so that it only advises about the /ask command every 30 minutes per channel
My review is in progress 📖 - I will have feedback for you in a few minutes! |
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Review Summary by Korbit AI
Code Execution Comments
- Modify the 'ask' command to accept user input and correct the 'gpt-4o' typo for proper functionality.
- Add checks for 'query', 'vector_store', and use
await
inasimilarity_search
for robust and correct asynchronous behavior. - Address undefined 'result' in
trigger_dev_team_flow
error handling to prevent masking original exceptions.
Code Health Comments
- Ensure access to API Variables and integrate or remove unused
TechLeadAgent
to maintain clean code. - Enhance error handling with detailed log messages and specific exception handling for better debugging and issue diagnosis.
- Add error checking for GITHUB_TOKEN and state values to prevent runtime errors.
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module.exports = { | ||
data: new SlashCommandBuilder() | ||
.setName('ask') | ||
.setDescription('Ask a question to the bot'), | ||
async execute(interaction) { | ||
await interaction.reply('Please provide your question.'); | ||
} | ||
}; |
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Modify 'ask' command to accept user input.
The current implementation of the 'ask' command doesn't allow users to input their questions, which contradicts its purpose. To improve this, we should modify the command to accept a string option for the user's question. Here's an example of how you could update the command:
const { SlashCommandBuilder } = require('discord.js');
module.exports = {
data: new SlashCommandBuilder()
.setName('ask')
.setDescription('Ask a question to the bot')
.addStringOption(option =>
option.setName('question')
.setDescription('Your question for the bot')
.setRequired(true)),
async execute(interaction) {
const question = interaction.options.getString('question');
// Process the question and generate a response
await interaction.reply(`You asked: ${question}\nHere's my response: [Bot's response goes here]`);
}
};
This modification allows users to input their questions and sets up the structure for processing those questions and providing meaningful responses.
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except Exception as e: | ||
print(f"Error saving to vector store: {e}") | ||
return None |
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Avoid catching generic exceptions.
In the save_to_vector_store
method, you are catching a generic Exception
and only printing the error message. This can lead to swallowed exceptions and make it difficult to diagnose and fix issues. Consider catching specific exceptions that you expect to occur and handle them appropriately. If an unexpected exception occurs, re-raise it or log it with more details and context for better debugging.
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async def asimilarity_search(self, query, k, filter): | ||
"""Return query by vector store""" | ||
results = await self.vector_store.asimilarity_search(query=query, k=k, filter=filter) | ||
return results |
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Missing 'await' keyword in asynchronous method.
In the asimilarity_search
method, you have defined it as an asynchronous method using the async
keyword. However, when calling self.vector_store.asimilarity_search
, which is also an asynchronous method, you need to use the await
keyword to properly await its execution. Without await
, the asynchronous call will not be handled correctly, and the method will continue executing without waiting for the result. Please add the await
keyword before self.vector_store.asimilarity_search
to ensure proper asynchronous behavior.
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except Exception as e: | ||
if websocket and stream_output: | ||
try: | ||
await stream_output("logs", "dev_team_result", result, websocket) | ||
except Exception as e: | ||
print(f"Error sending result over WebSocket: {e}") |
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Undefined 'result' in error handling of 'trigger_dev_team_flow' function.
There's an issue with the error handling in the trigger_dev_team_flow
function. In the outer except block, you're trying to send 'result' over WebSocket, but 'result' is not defined in this scope if an exception occurs. This could lead to another exception being raised, masking the original error. Consider logging the original exception and sending an error message to the client instead. Also, you might want to return an error status or re-raise the exception after logging it.
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@@ -126,7 +126,7 @@ export default function Modal({ setChatBoxSettings, chatBoxSettings }) { | |||
<div className="relative p-6 flex-auto"> | |||
<div className="tabs"> | |||
<button onClick={() => setActiveTab('search')} className={`tab-button ${activeTab === 'search' ? 'active' : ''}`}>Search Settings</button> | |||
<button onClick={() => setActiveTab('api')} className={`tab-button ${activeTab === 'api' ? 'active' : ''}`}>API Variables</button> | |||
{/* <button onClick={() => setActiveTab('api')} className={`tab-button ${activeTab === 'api' ? 'active' : ''}`}>API Variables</button> */} |
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API Variables tab button is commented out.
The API Variables tab button has been commented out, which removes access to important configuration settings for various API services. If this was intentional, please ensure that an alternative method for configuring these settings is provided, or update the application to function without these settings. If this was unintentional, consider uncommenting the button to restore access to the API Variables configuration.
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query=query, | ||
repo_name=repo_name, | ||
branch_name=branch_name, | ||
model="gpt-4o", |
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Typo in model parameter initialization.
I noticed that in the AgentState
class, the model
parameter is initialized with the value 'gpt-4o'. This appears to be a typo, as there is no OpenAI model with this exact name. To ensure proper functionality, please update this to a valid model name, such as 'gpt-4' or another appropriate model identifier.
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self.tech_lead_agent = TechLeadAgent() | ||
|
||
def init_flow(self): | ||
workflow = StateGraph(AgentState) | ||
|
||
workflow.add_node("fetch_github", self.github_agent.fetch_repo_data) | ||
workflow.add_node("analyze_repo", self.repo_analyzer_agent.analyze_repo) | ||
# workflow.add_node("web_search", self.web_search_agent.search_web) | ||
workflow.add_node("fetch_files", self.file_search_agent.find_relevant_files) | ||
workflow.add_node("rubber_duck", self.rubber_ducker_agent.think_aloud) | ||
# workflow.add_node("tech_lead", self.tech_lead_agent.review_and_compose) | ||
|
||
workflow.set_entry_point("fetch_github") | ||
workflow.add_edge('fetch_github', 'fetch_files') | ||
workflow.add_edge('fetch_files', 'analyze_repo') | ||
workflow.add_edge('analyze_repo', 'rubber_duck') | ||
# workflow.add_edge('web_search', 'rubber_duck') | ||
# workflow.add_edge('rubber_duck', 'tech_lead') | ||
workflow.add_edge('rubber_duck', END) |
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Unused instantiation of TechLeadAgent
in DevTeamFlow
class.
The TechLeadAgent
is instantiated in the DevTeamFlow
class, but it's not being used in the workflow. The 'tech_lead' node and its corresponding edge are commented out. If the tech lead review functionality is intended to be part of the workflow, consider uncommenting and properly integrating these lines. Otherwise, you may want to remove the unused TechLeadAgent
to avoid confusion and maintain clean code.
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socket.onerror = (error) => { | ||
console.error('WebSocket error:', error); | ||
}; |
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Enhance error handling log messages.
I noticed that your error handling code could use more detailed log messages. Right now, it only logs the error object, which may not provide enough context about what was happening when the error occurred. I recommend adding log messages that describe what operation was being performed when the error occurred, and any other relevant context. This will make it easier to understand and debug the error.
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async def analyze_repo(self, state): | ||
query = state.get("query") | ||
vector_store = state.get("vector_store") | ||
print('state', state) | ||
print("Analyzing repo vector store", vector_store) |
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Add validation for 'query' and 'vector_store' in 'analyze_repo' method.
The analyze_repo
method currently assumes that 'query' and 'vector_store' are always present in the state dictionary. It's a good practice to add checks for these keys to ensure the method behaves correctly even if the state is not properly initialized. Consider adding validation at the beginning of the method, like this:
query = state.get('query')
vector_store = state.get('vector_store')
if not query or not vector_store:
raise ValueError("Both 'query' and 'vector_store' must be provided in the state.")
This will make the code more robust and easier to debug if issues arise.
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|
||
class RubberDuckerAgent: | ||
async def think_aloud(self, state): | ||
github_agent = GithubAgent(github_token=os.environ.get("GITHUB_TOKEN"), repo_name=state.get("repo_name"), branch_name=state.get("branch_name"), vector_store=state.get("vector_store")) |
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Add error checking for GITHUB_TOKEN and required state values.
Consider adding error checking for the GITHUB_TOKEN environment variable and required state values. This will prevent potential runtime errors if these values are missing. For example, you could use a try-except block or add conditional checks before accessing these values.
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…to verify everything is getting saved correctly
Description by Korbit AI
What change is being made?
Add a Discord bot feature to the project, integrate a new vector store wrapper for handling document storage and retrieval, and enhance the backend to support a new "dev_team" report type.
Why are these changes being made?
These changes introduce a Discord bot to facilitate user interaction and automate tasks, enhance the system's ability to manage and query document data efficiently using a vector store, and support a new report type that triggers a development team workflow, improving the overall functionality and user experience of the application.