instruction stringclasses 100
values | code stringlengths 78 193k | response stringlengths 259 170k | file stringlengths 59 203 |
|---|---|---|---|
Help me write clear docstrings | import logging
import uuid
from typing import Dict, List, Mapping, Optional
from urllib.parse import urlparse
from pydantic import BaseModel
try:
import weaviate
except ImportError:
raise ImportError(
"The 'weaviate' library is required. Please install it using 'pip install weaviate-client weaviate'."... | --- +++ @@ -37,6 +37,17 @@ auth_client_secret: str = None,
additional_headers: dict = None,
):
+ """
+ Initialize the Weaviate vector store.
+
+ Args:
+ collection_name (str): Name of the collection/class in Weaviate.
+ embedding_model_dims (int): Dimensi... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/vector_stores/weaviate.py |
Write Python docstrings for this snippet | from typing import Tuple
from app.models import App, User
from sqlalchemy.orm import Session
def get_or_create_user(db: Session, user_id: str) -> User:
user = db.query(User).filter(User.user_id == user_id).first()
if not user:
user = User(user_id=user_id)
db.add(user)
db.commit()
... | --- +++ @@ -5,6 +5,7 @@
def get_or_create_user(db: Session, user_id: str) -> User:
+ """Get or create a user with the given user_id"""
user = db.query(User).filter(User.user_id == user_id).first()
if not user:
user = User(user_id=user_id)
@@ -15,6 +16,7 @@
def get_or_create_app(db: Session... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/openmemory/api/app/utils/db.py |
Generate consistent documentation across files | from typing import Any, Dict, Optional
from app.database import get_db
from app.models import Config as ConfigModel
from app.utils.memory import reset_memory_client
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel, Field
from sqlalchemy.orm import Session
router = APIRouter(prefix=... | --- +++ @@ -47,6 +47,7 @@ mem0: Optional[Mem0Config] = None
def get_default_configuration():
+ """Get the default configuration with sensible defaults for LLM and embedder."""
return {
"openmemory": {
"custom_instructions": None
@@ -73,6 +74,7 @@ }
def get_config_from_db(db: ... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/openmemory/api/app/routers/config.py |
Fully document this Python code with docstrings | import logging
from abc import ABC, abstractmethod
from mem0.memory.utils import format_entities
try:
from rank_bm25 import BM25Okapi
except ImportError:
raise ImportError("rank_bm25 is not installed. Please install it using pip install rank-bm25")
from mem0.graphs.tools import (
DELETE_MEMORY_STRUCT_TOO... | --- +++ @@ -23,9 +23,16 @@
class NeptuneBase(ABC):
+ """
+ Abstract base class for neptune (neptune analytics and neptune db) calls using OpenCypher
+ to store/retrieve data
+ """
@staticmethod
def _create_embedding_model(config):
+ """
+ :return: the Embedder model used for me... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/graphs/neptune/base.py |
Add standardized docstrings across the file | import logging
import uuid
from typing import List, Optional
from pydantic import BaseModel
try:
import vecs
except ImportError:
raise ImportError("The 'vecs' library is required. Please install it using 'pip install vecs'.")
from mem0.configs.vector_stores.supabase import IndexMeasure, IndexMethod
from mem0... | --- +++ @@ -30,6 +30,16 @@ index_method: IndexMethod = IndexMethod.AUTO,
index_measure: IndexMeasure = IndexMeasure.COSINE,
):
+ """
+ Initialize the Supabase vector store using vecs.
+
+ Args:
+ connection_string (str): PostgreSQL connection string
+ col... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/vector_stores/supabase.py |
Write docstrings that follow conventions | import os
from typing import Dict, List, Optional
try:
from google import genai
from google.genai import types
except ImportError:
raise ImportError("The 'google-genai' library is required. Please install it using 'pip install google-genai'.")
from mem0.configs.llms.base import BaseLlmConfig
from mem0.llm... | --- +++ @@ -22,6 +22,16 @@ self.client = genai.Client(api_key=api_key)
def _parse_response(self, response, tools):
+ """
+ Process the response based on whether tools are used or not.
+
+ Args:
+ response: The raw response from API.
+ tools: The list of tools pr... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/llms/gemini.py |
Add return value explanations in docstrings | import logging
from mem0.memory.utils import format_entities
try:
import kuzu
except ImportError:
raise ImportError("kuzu is not installed. Please install it using pip install kuzu")
try:
from rank_bm25 import BM25Okapi
except ImportError:
raise ImportError("rank_bm25 is not installed. Please install... | --- +++ @@ -96,6 +96,13 @@ return list(results.rows_as_dict())
def add(self, data, filters):
+ """
+ Adds data to the graph.
+
+ Args:
+ data (str): The data to add to the graph.
+ filters (dict): A dictionary containing filters to be applied during the addition... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/memory/kuzu_memory.py |
Document all public functions with docstrings | import json
import os
from typing import Dict, List, Optional, Union
from openai import OpenAI
from mem0.configs.llms.base import BaseLlmConfig
from mem0.configs.llms.deepseek import DeepSeekConfig
from mem0.llms.base import LLMBase
from mem0.memory.utils import extract_json
class DeepSeekLLM(LLMBase):
def __in... | --- +++ @@ -41,6 +41,16 @@ self.client = OpenAI(api_key=api_key, base_url=base_url)
def _parse_response(self, response, tools):
+ """
+ Process the response based on whether tools are used or not.
+
+ Args:
+ response: The raw response from API.
+ tools: The lis... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/llms/deepseek.py |
Generate missing documentation strings | import asyncio
import concurrent
import gc
import hashlib
import json
import logging
import os
import uuid
import warnings
from copy import deepcopy
from datetime import datetime
from typing import Any, Dict, Optional
import pytz
from pydantic import ValidationError
from mem0.configs.base import MemoryConfig, MemoryI... | --- +++ @@ -52,6 +52,7 @@
def _safe_deepcopy_config(config):
+ """Safely deepcopy config, falling back to JSON serialization for non-serializable objects."""
try:
return deepcopy(config)
except Exception as e:
@@ -94,6 +95,40 @@ input_metadata: Optional[Dict[str, Any]] = None,
input_f... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/memory/main.py |
Create docstrings for all classes and functions | from abc import ABC, abstractmethod
class MemoryBase(ABC):
@abstractmethod
def get(self, memory_id):
pass
@abstractmethod
def get_all(self):
pass
@abstractmethod
def update(self, memory_id, data):
pass
@abstractmethod
def delete(self, memory_id):
pass... | --- +++ @@ -4,20 +4,60 @@ class MemoryBase(ABC):
@abstractmethod
def get(self, memory_id):
+ """
+ Retrieve a memory by ID.
+
+ Args:
+ memory_id (str): ID of the memory to retrieve.
+
+ Returns:
+ dict: Retrieved memory.
+ """
pass
@abs... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/memory/base.py |
Write Python docstrings for this snippet | import logging
import uuid
from datetime import datetime
import pytz
from .base import NeptuneBase
try:
from langchain_aws import NeptuneGraph
except ImportError:
raise ImportError("langchain_aws is not installed. Please install it using 'make install_all'.")
logger = logging.getLogger(__name__)
class Memor... | --- +++ @@ -14,6 +14,9 @@
class MemoryGraph(NeptuneBase):
def __init__(self, config):
+ """
+ Initialize the Neptune DB memory store.
+ """
self.config = config
@@ -58,6 +61,15 @@ self.vector_store_limit=5
def _delete_entities_cypher(self, source, destination, rel... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/graphs/neptune/neptunedb.py |
Add minimal docstrings for each function | import json
from typing import Dict, List, Optional
try:
import litellm
except ImportError:
raise ImportError("The 'litellm' library is required. Please install it using 'pip install litellm'.")
from mem0.configs.llms.base import BaseLlmConfig
from mem0.llms.base import LLMBase
from mem0.memory.utils import e... | --- +++ @@ -19,6 +19,16 @@ self.config.model = "gpt-4.1-nano-2025-04-14"
def _parse_response(self, response, tools):
+ """
+ Process the response based on whether tools are used or not.
+
+ Args:
+ response: The raw response from API.
+ tools: The list of to... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/llms/litellm.py |
Add detailed documentation for each class | import os
import re
import glob
import json
import logging
import torch
from nanochat.common import get_base_dir
from nanochat.gpt import GPT, GPTConfig
from nanochat.tokenizer import get_tokenizer
from nanochat.common import setup_default_logging
# Set up logging
setup_default_logging()
logger = logging.getLogger(__... | --- +++ @@ -1,3 +1,6 @@+"""
+Utilities for saving and loading model/optim/state checkpoints.
+"""
import os
import re
import glob
@@ -18,12 +21,14 @@ logger.info(message)
def _patch_missing_config_keys(model_config_kwargs):
+ """Add default values for new config keys missing in old checkpoints."""
... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/checkpoint_manager.py |
Write beginner-friendly docstrings |
import torch
import pyarrow.parquet as pq
from nanochat.common import get_dist_info
from nanochat.dataset import list_parquet_files
def _document_batches(split, resume_state_dict, tokenizer_batch_size):
ddp, ddp_rank, ddp_local_rank, ddp_world_size = get_dist_info()
warn_on_legacy = ddp_rank == 0 and split ... | --- +++ @@ -1,3 +1,20 @@+"""
+Distributed dataloaders for pretraining.
+
+BOS-aligned bestfit:
+ - Every row starts with BOS token
+ - Documents packed using best-fit algorithm to minimize cropping
+ - When no document fits remaining space, crops a document to fill exactly
+ - 100% utilization (no padding), ~35... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/dataloader.py |
Add docstrings to meet PEP guidelines |
import os
import re
import logging
import urllib.request
import torch
import torch.distributed as dist
from filelock import FileLock
# The dtype used for compute (matmuls, activations). Master weights stay fp32 for optimizer precision.
# Linear layers cast their weights to this dtype in forward, replacing torch.amp.a... | --- +++ @@ -1,3 +1,6 @@+"""
+Common utilities for nanochat.
+"""
import os
import re
@@ -28,6 +31,7 @@ COMPUTE_DTYPE, COMPUTE_DTYPE_REASON = _detect_compute_dtype()
class ColoredFormatter(logging.Formatter):
+ """Custom formatter that adds colors to log messages."""
# ANSI color codes
COLORS = {
... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/common.py |
Write reusable docstrings | import logging
import os
from typing import Any, Dict, List, Optional
from dotenv import load_dotenv
from fastapi import FastAPI, HTTPException
from fastapi.responses import JSONResponse, RedirectResponse
from pydantic import BaseModel, Field
from mem0 import Memory
logging.basicConfig(level=logging.INFO, format="%(... | --- +++ @@ -88,6 +88,7 @@
@app.post("/configure", summary="Configure Mem0")
def set_config(config: Dict[str, Any]):
+ """Set memory configuration."""
global MEMORY_INSTANCE
MEMORY_INSTANCE = Memory.from_config(config)
return {"message": "Configuration set successfully"}
@@ -95,6 +96,7 @@
@app.pos... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/server/main.py |
Generate consistent docstrings | #!/usr/bin/env python3
import argparse
import json
import sys
import urllib.error
import urllib.parse
import urllib.request
DOCS_BASE = "https://docs.mem0.ai"
SEARCH_ENDPOINT = f"{DOCS_BASE}/api/search"
LLMS_INDEX = f"{DOCS_BASE}/llms.txt"
# Known documentation sections for targeted retrieval
SECTION_MAP = {
"pl... | --- +++ @@ -1,4 +1,24 @@ #!/usr/bin/env python3
+"""
+Mem0 Documentation Search Agent (Mintlify-based)
+On-demand search tool for querying Mem0 documentation without storing content locally.
+
+This tool leverages Mintlify's documentation structure to perform just-in-time
+retrieval of technical information from docs.m... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/skills/mem0/scripts/mem0_doc_search.py |
Generate docstrings for exported functions | import logging
from typing import Dict, List, Optional
from pydantic import BaseModel
try:
from langchain_community.vectorstores import VectorStore
except ImportError:
raise ImportError(
"The 'langchain_community' library is required. Please install it using 'pip install langchain_community'."
)
... | --- +++ @@ -27,6 +27,15 @@ self.collection_name = collection_name
def _parse_output(self, data: Dict) -> List[OutputData]:
+ """
+ Parse the output data.
+
+ Args:
+ data (Dict): Output data or list of Document objects.
+
+ Returns:
+ List[OutputData]: Pa... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/vector_stores/langchain.py |
Add docstrings to improve code quality |
import os
import argparse
import time
import requests
import pyarrow.parquet as pq
from multiprocessing import Pool
from nanochat.common import get_base_dir
# -----------------------------------------------------------------------------
# The specifics of the current pretraining dataset
# The URL on the internet wh... | --- +++ @@ -1,3 +1,11 @@+"""
+The base/pretraining dataset is a set of parquet files.
+This file contains utilities for:
+- iterating over the parquet files and yielding documents from it
+- download the files on demand if they are not on disk
+
+For details of how the dataset was prepared, see `repackage_data_referenc... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/dataset.py |
Add detailed docstrings explaining each function | import datetime
import enum
import uuid
import sqlalchemy as sa
from app.database import Base
from app.utils.categorization import get_categories_for_memory
from sqlalchemy import (
JSON,
UUID,
Boolean,
Column,
DateTime,
Enum,
ForeignKey,
Index,
Integer,
String,
Table,
e... | --- +++ @@ -23,6 +23,7 @@
def get_current_utc_time():
+ """Get current UTC time"""
return datetime.datetime.now(datetime.UTC)
@@ -187,6 +188,7 @@ )
def categorize_memory(memory: Memory, db: Session) -> None:
+ """Categorize a memory using OpenAI and store the categories in the database."""
... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/openmemory/api/app/models.py |
Create simple docstrings for beginners |
import contextvars
import datetime
import json
import logging
import uuid
from app.database import SessionLocal
from app.models import Memory, MemoryAccessLog, MemoryState, MemoryStatusHistory
from app.utils.db import get_user_and_app
from app.utils.memory import get_memory_client
from app.utils.permissions import ch... | --- +++ @@ -1,3 +1,19 @@+"""
+MCP Server for OpenMemory with resilient memory client handling.
+
+This module implements an MCP (Model Context Protocol) server that provides
+memory operations for OpenMemory. The memory client is initialized lazily
+to prevent server crashes when external dependencies (like Ollama) are... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/openmemory/api/app/mcp_server.py |
Add docstrings to incomplete code | import logging
from mem0.memory.utils import format_entities, sanitize_relationship_for_cypher
try:
from langchain_neo4j import Neo4jGraph
except ImportError:
raise ImportError("langchain_neo4j is not installed. Please install it using pip install langchain-neo4j")
try:
from rank_bm25 import BM25Okapi
ex... | --- +++ @@ -74,6 +74,13 @@ self.threshold = self.config.graph_store.threshold if hasattr(self.config.graph_store, 'threshold') else 0.7
def add(self, data, filters):
+ """
+ Adds data to the graph.
+
+ Args:
+ data (str): The data to add to the graph.
+ filters ... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/memory/graph_memory.py |
Add docstrings with type hints explained | import random
from jinja2 import Template
import torch
import torch.distributed as dist
# -----------------------------------------------------------------------------
# Prompt rendering utilities
def render_prompts_mc(item, continuation_delimiter, fewshot_examples=None):
template_str = """
{%- for example in fe... | --- +++ @@ -1,3 +1,10 @@+"""
+Functions for evaluating the CORE metric, as described in the DCLM paper.
+https://arxiv.org/abs/2406.11794
+
+TODOs:
+- All tasks ~match except for squad. We get 31% reference is 37%. Figure out why.
+"""
import random
from jinja2 import Template
@@ -8,6 +15,7 @@ # Prompt rendering ut... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/core_eval.py |
Help me document legacy Python code | from typing import Dict, List, Optional
from mem0.configs.llms.base import BaseLlmConfig
from mem0.llms.base import LLMBase
try:
from langchain.chat_models.base import BaseChatModel
from langchain_core.messages import AIMessage
except ImportError:
raise ImportError("langchain is not installed. Please inst... | --- +++ @@ -23,6 +23,16 @@ self.langchain_model = self.config.model
def _parse_response(self, response: AIMessage, tools: Optional[List[Dict]]):
+ """
+ Process the response based on whether tools are used or not.
+
+ Args:
+ response: AI Message.
+ tools: The l... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/llms/langchain.py |
Document all public functions with docstrings |
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
from dataclasses import dataclass
from typing import Optional
# -----------------------------------------------------------------------------
@dataclass
class ExecutionResult:
success: b... | --- +++ @@ -1,3 +1,25 @@+"""
+Sandboxed execution utilities for running Python code that comes out of an LLM.
+Adapted from OpenAI HumanEval code:
+https://github.com/openai/human-eval/blob/master/human_eval/execution.py
+
+What is covered:
+- Each execution runs in its own process (can be killed if it hangs or crashes... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/execution.py |
Add docstrings including usage examples | import math
import torch
import torch.distributed as dist
@torch.no_grad()
def evaluate_bpb(model, batches, steps, token_bytes):
# record the losses
total_nats = torch.tensor(0.0, dtype=torch.float32, device=model.get_device())
total_bytes = torch.tensor(0, dtype=torch.int64, device=model.get_device())
... | --- +++ @@ -1,9 +1,29 @@+"""
+A number of functions that help with evaluating a base model.
+"""
import math
import torch
import torch.distributed as dist
@torch.no_grad()
def evaluate_bpb(model, batches, steps, token_bytes):
+ """
+ Instead of the naive 'mean loss', this function returns the bits per byte... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/loss_eval.py |
Add docstrings that explain logic | import requests
import json
import os
import copy
import random
from concurrent.futures import ThreadPoolExecutor, as_completed
from dotenv import load_dotenv
from nanochat.common import get_base_dir
load_dotenv()
api_key = os.environ["OPENROUTER_API_KEY"]
url = "https://openrouter.ai/api/v1/chat/completions"
header... | --- +++ @@ -1,3 +1,23 @@+"""
+Synthetic data generation for teaching nanochat about its identity and capabilities.
+
+This script uses the OpenRouter API to generate diverse multi-turn conversations
+between a user and nanochat. The conversations are saved to a .jsonl file for use
+in supervised finetuning (SFT) via th... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/dev/gen_synthetic_data.py |
Add missing documentation to my Python functions | import logging
from mem0.memory.utils import format_entities, sanitize_relationship_for_cypher
try:
from langchain_memgraph.graphs.memgraph import Memgraph
except ImportError:
raise ImportError("langchain_memgraph is not installed. Please install it using pip install langchain-memgraph")
try:
from rank_b... | --- +++ @@ -79,6 +79,13 @@ self.graph.query("CREATE INDEX ON :Entity;")
def add(self, data, filters):
+ """
+ Adds data to the graph.
+
+ Args:
+ data (str): The data to add to the graph.
+ filters (dict): A dictionary containing filters to be applied during... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/memory/memgraph_memory.py |
Add docstrings to meet PEP guidelines |
import torch
import torch.distributed as dist
from torch import Tensor
# -----------------------------------------------------------------------------
"""
Good old AdamW optimizer, fused kernel.
https://arxiv.org/abs/1711.05101
"""
@torch.compile(dynamic=False, fullgraph=True)
def adamw_step_fused(
p: Tensor, ... | --- +++ @@ -1,3 +1,11 @@+"""
+A nice and efficient mixed AdamW/Muon Combined Optimizer.
+Usually the embeddings and scalars go into AdamW, and the matrix parameters go into Muon.
+Two versions are provided (MuonAdamW, DistMuonAdamW), for single GPU and distributed.
+
+Addapted from: https://github.com/KellerJordan/modd... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/optim.py |
Add docstrings to incomplete code |
import re
from datasets import load_dataset
from nanochat.execution import execute_code
from tasks.common import Task
def extract_imports(prompt):
imports = []
for line in prompt.split('\n'):
stripped = line.strip()
if stripped.startswith('import ') or stripped.startswith('from '):
... | --- +++ @@ -1,3 +1,8 @@+"""
+Evaluate the Chat model on HumanEval dataset.
+Btw this dataset is a misnomer and has nothing to do with humans.
+It is a coding benchmark.
+"""
import re
from datasets import load_dataset
@@ -5,6 +10,7 @@ from tasks.common import Task
def extract_imports(prompt):
+ """Extract imp... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/tasks/humaneval.py |
Document all public functions with docstrings |
import re
from datasets import load_dataset
from tasks.common import Task
GSM_RE = re.compile(r"#### (\-?[0-9\.\,]+)")
def extract_answer(completion):
match = GSM_RE.search(completion)
if match:
match_str = match.group(1).strip()
match_str = match_str.replace(",", "")
return match_str... | --- +++ @@ -1,3 +1,18 @@+"""
+GSM8K evaluation.
+https://huggingface.co/datasets/openai/gsm8k
+
+Example problem instance:
+
+Question:
+Weng earns $12 an hour for babysitting. Yesterday, she just did 50 minutes of babysitting. How much did she earn?
+Answer:
+Weng earns 12/60 = $<<12/60=0.2>>0.2 per minute.
+Working 5... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/tasks/gsm8k.py |
Document all endpoints with docstrings |
import hashlib
import json
import os
import socket
from app.database import SessionLocal
from app.models import Config as ConfigModel
from mem0 import Memory
_memory_client = None
_config_hash = None
def _get_config_hash(config_dict):
config_str = json.dumps(config_dict, sort_keys=True)
return hashlib.md5... | --- +++ @@ -1,3 +1,31 @@+"""
+Memory client utilities for OpenMemory.
+
+This module provides functionality to initialize and manage the Mem0 memory client
+with automatic configuration management and Docker environment support.
+
+Docker Ollama Configuration:
+When running inside a Docker container and using Ollama as... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/openmemory/api/app/utils/memory.py |
Add docstrings to existing functions | import torch
import torch.nn.functional as F
# =============================================================================
# Detection: Try to load FA3 on Hopper+ GPUs
# =============================================================================
def _load_flash_attention_3():
if not torch.cuda.is_available():... | --- +++ @@ -1,3 +1,18 @@+"""
+Unified Flash Attention interface with automatic FA3/SDPA switching.
+
+Exports `flash_attn` module that matches the FA3 API exactly, but falls back
+to PyTorch SDPA on non-Hopper GPUs (including Blackwell), MPS, and CPU.
+
+Usage (drop-in replacement for FA3):
+ from nanochat.flash_att... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/flash_attention.py |
Write docstrings for data processing functions | from abc import ABC, abstractmethod
from typing import List, Dict, Any
class BaseReranker(ABC):
@abstractmethod
def rerank(self, query: str, documents: List[Dict[str, Any]], top_k: int = None) -> List[Dict[str, Any]]:
pass | --- +++ @@ -2,7 +2,19 @@ from typing import List, Dict, Any
class BaseReranker(ABC):
+ """Abstract base class for all rerankers."""
@abstractmethod
def rerank(self, query: str, documents: List[Dict[str, Any]], top_k: int = None) -> List[Dict[str, Any]]:
+ """
+ Rerank documents based... | https://raw.githubusercontent.com/mem0ai/mem0/HEAD/mem0/reranker/base.py |
Generate docstrings with parameter types |
from functools import partial
from dataclasses import dataclass
import torch
import torch.nn as nn
import torch.nn.functional as F
from nanochat.common import get_dist_info, print0, COMPUTE_DTYPE
from nanochat.optim import MuonAdamW, DistMuonAdamW
# Our custom Flash Attention module that automatically uses FA3 on H... | --- +++ @@ -1,3 +1,16 @@+"""
+GPT model (rewrite, a lot simpler)
+Notable features:
+- rotary embeddings (and no positional embeddings)
+- QK norm
+- untied weights for token embedding and lm_head
+- relu^2 activation in MLP
+- norm after token embedding
+- no learnable params in rmsnorm
+- no bias in linear layers
+- ... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/gpt.py |
Generate docstrings with parameter types |
import torch
import torch.nn.functional as F
import signal
import warnings
from contextlib import contextmanager
from collections import deque
from nanochat.common import compute_init, autodetect_device_type
from nanochat.checkpoint_manager import load_model
# ---------------------------------------------------------... | --- +++ @@ -1,3 +1,15 @@+"""
+Engine for efficient inference of our models.
+
+Everything works around token sequences:
+- The user can send token sequences to the engine
+- The engine returns the next token
+
+Notes:
+- The engine knows nothing about tokenization, it's purely token id sequences.
+
+The whole thing is ... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/engine.py |
Write docstrings describing each step |
import torch
import torch.nn as nn
from nanochat.common import COMPUTE_DTYPE
# Avoid division by zero when computing scale from an all-zeros tensor
EPS = 1e-12
@torch.no_grad()
def _to_fp8(x, fp8_dtype):
fp8_max = torch.finfo(fp8_dtype).max
# Compute the max absolute value across the entire tensor
amax... | --- +++ @@ -1,3 +1,73 @@+"""Minimal FP8 training for nanochat — tensorwise dynamic scaling only.
+
+Drop-in replacement for torchao's Float8Linear (~2000 lines) with ~150 lines.
+We only need the "tensorwise" recipe (one scalar scale per tensor), not the full
+generality of torchao (rowwise scaling, FSDP float8 all-gat... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/fp8.py |
Fill in missing docstrings in my code |
import os
import copy
from functools import lru_cache
SPECIAL_TOKENS = [
# every document begins with the Beginning of Sequence (BOS) token that delimits documents
"<|bos|>",
# tokens below are only used during finetuning to render Conversations into token ids
"<|user_start|>", # user messages
"<|... | --- +++ @@ -1,3 +1,10 @@+"""
+BPE Tokenizer in the style of GPT-4.
+
+Two implementations are available:
+1) HuggingFace Tokenizer that can do both training and inference but is really confusing
+2) Our own RustBPE Tokenizer for training and tiktoken for efficient inference
+"""
import os
import copy
@@ -30,6 +37,7... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/tokenizer.py |
Add docstrings that explain purpose and usage |
import os
import re
import shutil
import subprocess
import socket
import datetime
import platform
import psutil
import torch
def run_command(cmd):
try:
result = subprocess.run(cmd, shell=True, capture_output=True, text=True, timeout=5)
# Return stdout if we got output (even if some files in xargs ... | --- +++ @@ -1,3 +1,6 @@+"""
+Utilities for generating training report cards. More messy code than usual, will fix.
+"""
import os
import re
@@ -10,6 +13,7 @@ import torch
def run_command(cmd):
+ """Run a shell command and return output, or None if it fails."""
try:
result = subprocess.run(cmd, s... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/nanochat/report.py |
Generate descriptive docstrings automatically | import os
import csv
import time
import json
import yaml
import shutil
import random
import zipfile
import tempfile
import argparse
import torch
from nanochat.common import compute_init, compute_cleanup, print0, get_base_dir, autodetect_device_type, download_file_with_lock
from nanochat.tokenizer import HuggingFaceTok... | --- +++ @@ -1,3 +1,24 @@+"""
+Unified evaluation script for base models.
+
+Supports three evaluation modes (comma-separated):
+ --eval core : CORE metric (accuracy on ICL tasks)
+ --eval bpb : Bits per byte on train/val splits
+ --eval sample : Generate samples from the model
+
+Default is all three: --eval... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/scripts/base_eval.py |
Replace inline comments with docstrings |
import os
os.environ["PYTORCH_ALLOC_CONF"] = "expandable_segments:True"
import gc
import json
import time
import math
import argparse
from dataclasses import asdict
from contextlib import contextmanager
import wandb
import torch
import torch.distributed as dist
from nanochat.gpt import GPT, GPTConfig, Linear
from na... | --- +++ @@ -1,3 +1,15 @@+"""
+Train model. From root directory of the project, run as:
+
+python -m scripts.base_train
+
+or distributed as:
+
+torchrun --nproc_per_node=8 -m scripts.base_train
+
+If you are only on CPU/Macbook, you'll want to train a much much smaller LLM. Example:
+python -m scripts.base_train --dept... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/scripts/base_train.py |
Write Python docstrings for this snippet | #!/usr/bin/env python3
import argparse
import json
import os
import torch
import asyncio
import logging
import random
from contextlib import asynccontextmanager
from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import StreamingResponse, HTMLResponse, F... | --- +++ @@ -1,4 +1,34 @@ #!/usr/bin/env python3
+"""
+Unified web chat server - serves both UI and API from a single FastAPI instance.
+
+Uses data parallelism to distribute requests across multiple GPUs. Each GPU loads
+a full copy of the model, and incoming requests are distributed to available workers.
+
+Launch exa... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/scripts/chat_web.py |
Write proper docstrings for these functions |
import argparse
import os
import itertools
import wandb
import torch
import torch.distributed as dist
from nanochat.common import compute_init, compute_cleanup, print0, get_base_dir, DummyWandb, autodetect_device_type
from nanochat.checkpoint_manager import save_checkpoint, load_model
from nanochat.engine import Engin... | --- +++ @@ -1,3 +1,20 @@+"""
+Reinforcement learning on GSM8K via "GRPO".
+
+I put GRPO in quotes because we actually end up with something a lot
+simpler and more similar to just REINFORCE:
+
+1) Delete trust region, so there is no KL regularization to a reference model
+2) We are on policy, so there's no need for PPO... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/scripts/chat_rl.py |
Expand my code with proper documentation strings | from sqlalchemy.orm import Session
from sqlalchemy import func
from typing import List, Optional
from datetime import datetime
from app.backend.database.models import ApiKey
class ApiKeyRepository:
def __init__(self, db: Session):
self.db = db
def create_or_update_api_key(
self,
... | --- +++ @@ -7,6 +7,7 @@
class ApiKeyRepository:
+ """Repository for API key database operations"""
def __init__(self, db: Session):
self.db = db
@@ -18,6 +19,7 @@ description: str = None,
is_active: bool = True
) -> ApiKey:
+ """Create a new API key or update exi... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/repositories/api_key_repository.py |
Improve my code by adding docstrings |
import gc
import argparse
import os
os.environ["PYTORCH_ALLOC_CONF"] = "expandable_segments:True"
import time
import wandb
import torch
from nanochat.common import compute_init, compute_cleanup, print0, DummyWandb, get_base_dir, autodetect_device_type, get_peak_flops, COMPUTE_DTYPE, COMPUTE_DTYPE_REASON, is_ddp_initia... | --- +++ @@ -1,3 +1,13 @@+"""
+Supervised fine-tuning (SFT) the model.
+Run as:
+
+python -m scripts.chat_sft
+
+Or torchrun for training:
+
+torchrun --standalone --nproc_per_node=8 -m scripts.chat_sft -- --device-batch-size=16
+"""
import gc
import argparse
@@ -175,6 +185,14 @@ approx_progress = 0.0 # will go from... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/scripts/chat_sft.py |
Write beginner-friendly docstrings |
from nanochat.tokenizer import get_tokenizer, RustBPETokenizer
from nanochat.dataset import parquets_iter_batched
# Random text I got from a random website this morning
news_text = r"""
(Washington, D.C., July 9, 2025)- Yesterday, Mexico’s National Service of Agro-Alimentary Health, Safety, and Quality (SENASICA) rep... | --- +++ @@ -1,3 +1,6 @@+"""
+Evaluate compression ratio of the tokenizer.
+"""
from nanochat.tokenizer import get_tokenizer, RustBPETokenizer
from nanochat.dataset import parquets_iter_batched
@@ -198,6 +201,7 @@ print(f"Ours: {vocab_sizes['ours']}")
def print_comparison(baseline_name, baseline_results, ours_res... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/scripts/tok_eval.py |
Document my Python code with docstrings | import os
import time
import argparse
import torch
from nanochat.tokenizer import RustBPETokenizer
from nanochat.common import get_base_dir
from nanochat.dataset import parquets_iter_batched
# -----------------------------------------------------------------------------
# Parse command line arguments
parser = argpars... | --- +++ @@ -1,3 +1,7 @@+"""
+Train a tokenizer using our own BPE Tokenizer library.
+In the style of GPT-4 tokenizer.
+"""
import os
import time
import argparse
@@ -22,6 +26,11 @@ # Text iterator
def text_iterator():
+ """
+ 1) Flatten the batches into a single iterator
+ 2) Crop every document to args.d... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/scripts/tok_train.py |
Turn comments into proper docstrings |
import os
import json
from tasks.common import Task
class CustomJSON(Task):
def __init__(self, filepath, **kwargs):
super().__init__(**kwargs)
self.filepath = filepath
self.conversations = []
# Load all conversations from the JSONL file
if not os.path.exists(filepath):
... | --- +++ @@ -1,9 +1,18 @@+"""
+CustomJSON task for loading conversations from JSONL files.
+Each line in the JSONL file should be a JSON array of messages.
+"""
import os
import json
from tasks.common import Task
class CustomJSON(Task):
+ """
+ Load conversations from a JSONL file.
+ Each line should be... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/tasks/customjson.py |
Add professional docstrings to my codebase | from fastapi import APIRouter, HTTPException, Depends, Query
from sqlalchemy.orm import Session
from typing import List, Optional
from app.backend.database import get_db
from app.backend.repositories.flow_run_repository import FlowRunRepository
from app.backend.repositories.flow_repository import FlowRepository
from a... | --- +++ @@ -30,6 +30,7 @@ request: FlowRunCreateRequest,
db: Session = Depends(get_db)
):
+ """Create a new flow run for the specified flow"""
try:
# Verify flow exists
flow_repo = FlowRepository(db)
@@ -64,6 +65,7 @@ offset: int = Query(0, ge=0, description="Number of runs to s... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/routes/flow_runs.py |
Generate docstrings for script automation |
import random
class Task:
def __init__(self, start=0, stop=None, step=1):
# allows a lightweight logical view over a dataset
assert start >= 0, f"Start must be non-negative, got {start}"
assert stop is None or stop >= start, f"Stop should be greater than or equal to start, got {stop} and ... | --- +++ @@ -1,7 +1,16 @@+"""
+Base class for all Tasks.
+A Task is basically a dataset of conversations, together with some
+metadata and often also evaluation criteria.
+Example tasks: MMLU, ARC-Easy, ARC-Challenge, GSM8K, HumanEval, SmolTalk.
+"""
import random
class Task:
+ """
+ Base class of a Task. Al... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/tasks/common.py |
Document functions with clear intent | from fastapi import APIRouter, HTTPException, Request, Depends
from fastapi.responses import StreamingResponse
from sqlalchemy.orm import Session
import asyncio
from app.backend.database import get_db
from app.backend.models.schemas import ErrorResponse, HedgeFundRequest, BacktestRequest, BacktestDayResult, BacktestPe... | --- +++ @@ -50,6 +50,7 @@
# Function to detect client disconnection
async def wait_for_disconnect():
+ """Wait for client disconnect and return True when it happens"""
try:
while True:
message = await request.receive()
@@ -167,6 +168,7 @@ ... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/routes/hedge_fund.py |
Provide docstrings following PEP 257 |
from datasets import load_dataset
from tasks.common import Task
class SmolTalk(Task):
def __init__(self, split, **kwargs):
super().__init__(**kwargs)
assert split in ["train", "test"], "SmolTalk split must be train|test"
self.ds = load_dataset("HuggingFaceTB/smol-smoltalk", split=split).s... | --- +++ @@ -1,8 +1,14 @@+"""
+SmolTalk by HuggingFace. Good "general" conversational dataset.
+https://huggingface.co/datasets/HuggingFaceTB/smol-smoltalk
+We use the "smol" version, which is more appropriate for smaller models.
+"""
from datasets import load_dataset
from tasks.common import Task
class SmolTalk(... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/tasks/smoltalk.py |
Write beginner-friendly docstrings |
import re
import random
from tasks.common import Task
from nanochat.common import download_file_with_lock
# Letters of the alphabet
LETTERS = "abcdefghijklmnopqrstuvwxyz"
# A list of 370K English words of large variety
WORD_LIST_URL = "https://raw.githubusercontent.com/dwyl/english-words/refs/heads/master/words_alpha... | --- +++ @@ -1,3 +1,30 @@+"""
+Task intended to make nanochat better in spelling and counting, for example:
+
+"How many r are in strawberry?" -> 3
+
+An interesting part of this task is that we will get the assistant to
+solve the problem using a combination of manual counting and Python.
+This is a good problem solvin... | https://raw.githubusercontent.com/karpathy/nanochat/HEAD/tasks/spellingbee.py |
Insert docstrings into my code | from fastapi import APIRouter, HTTPException
from typing import List, Dict, Any
from app.backend.models.schemas import ErrorResponse
from app.backend.services.ollama_service import OllamaService
from src.llm.models import get_models_list
router = APIRouter(prefix="/language-models")
# Initialize Ollama service
ollam... | --- +++ @@ -18,6 +18,7 @@ },
)
async def get_language_models():
+ """Get the list of available cloud-based and Ollama language models."""
try:
# Start with cloud models
models = get_models_list()
@@ -38,6 +39,7 @@ },
)
async def get_language_model_providers():
+ """Get the list ... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/routes/language_models.py |
Create docstrings for API functions | from sqlalchemy import Column, Integer, String, DateTime, Text, Boolean, JSON, ForeignKey
from sqlalchemy.sql import func
from .connection import Base
class HedgeFundFlow(Base):
__tablename__ = "hedge_fund_flows"
id = Column(Integer, primary_key=True, index=True)
created_at = Column(DateTime(timezone... | --- +++ @@ -4,6 +4,7 @@
class HedgeFundFlow(Base):
+ """Table to store React Flow configurations (nodes, edges, viewport)"""
__tablename__ = "hedge_fund_flows"
id = Column(Integer, primary_key=True, index=True)
@@ -26,6 +27,7 @@
class HedgeFundFlowRun(Base):
+ """Table to track individual ... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/database/models.py |
Improve my code by adding docstrings | from datetime import datetime, timedelta
from pydantic import BaseModel, Field, field_validator
from typing import List, Optional, Dict, Any
from src.llm.models import ModelProvider
from enum import Enum
from app.backend.services.graph import extract_base_agent_key
class FlowRunStatus(str, Enum):
IDLE = "IDLE"
... | --- +++ @@ -70,9 +70,11 @@ api_keys: Optional[Dict[str, str]] = None
def get_agent_ids(self) -> List[str]:
+ """Extract agent IDs from graph structure"""
return [node.id for node in self.graph_nodes]
def get_agent_model_config(self, agent_id: str) -> tuple[str, ModelProvider]:
+ ... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/models/schemas.py |
Write docstrings describing functionality | from sqlalchemy.orm import Session
from typing import Dict, Optional
from app.backend.repositories.api_key_repository import ApiKeyRepository
class ApiKeyService:
def __init__(self, db: Session):
self.repository = ApiKeyRepository(db)
def get_api_keys_dict(self) -> Dict[str, str]:
ap... | --- +++ @@ -4,14 +4,20 @@
class ApiKeyService:
+ """Simple service to load API keys for requests"""
def __init__(self, db: Session):
self.repository = ApiKeyRepository(db)
def get_api_keys_dict(self) -> Dict[str, str]:
+ """
+ Load all active API keys from database an... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/services/api_key_service.py |
Improve my code by adding docstrings | from src.graph.state import AgentState, show_agent_reasoning
from src.tools.api import get_financial_metrics, get_market_cap, search_line_items
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage
from pydantic import BaseModel
import json
from typing_extensions import ... | --- +++ @@ -17,6 +17,13 @@
def cathie_wood_agent(state: AgentState, agent_id: str = "cathie_wood_agent"):
+ """
+ Analyzes stocks using Cathie Wood's investing principles and LLM reasoning.
+ 1. Prioritizes companies with breakthrough technologies or business models
+ 2. Focuses on industries with rapid... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/cathie_wood.py |
Create Google-style docstrings for my code | from typing import List, Optional, Dict, Any
from datetime import datetime
from sqlalchemy.orm import Session
from sqlalchemy import desc, func
from app.backend.database.models import HedgeFundFlowRun
from app.backend.models.schemas import FlowRunStatus
class FlowRunRepository:
def __init__(self, db: Session... | --- +++ @@ -7,11 +7,13 @@
class FlowRunRepository:
+ """Repository for HedgeFundFlowRun CRUD operations"""
def __init__(self, db: Session):
self.db = db
def create_flow_run(self, flow_id: int, request_data: Dict[str, Any] = None) -> HedgeFundFlowRun:
+ """Create a new flow r... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/repositories/flow_run_repository.py |
Write reusable docstrings | import asyncio
import json
import re
from langchain_core.messages import HumanMessage
from langgraph.graph import END, StateGraph
from app.backend.services.agent_service import create_agent_function
from src.agents.portfolio_manager import portfolio_management_agent
from src.agents.risk_manager import risk_management_... | --- +++ @@ -13,6 +13,15 @@
def extract_base_agent_key(unique_id: str) -> str:
+ """
+ Extract the base agent key from a unique node ID.
+
+ Args:
+ unique_id: The unique node ID with suffix (e.g., "warren_buffett_abc123")
+
+ Returns:
+ The base agent key (e.g., "warren_buffett")
+... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/services/graph.py |
Add docstrings that explain logic | from logging.config import fileConfig
from sqlalchemy import engine_from_config
from sqlalchemy import pool
from alembic import context
# this is the Alembic Config object, which provides
# access to the values within the .ini file in use.
config = context.config
# Interpret the config file for Python logging.
# Th... | --- +++ @@ -26,6 +26,17 @@
def run_migrations_offline() -> None:
+ """Run migrations in 'offline' mode.
+
+ This configures the context with just a URL
+ and not an Engine, though an Engine is acceptable
+ here as well. By skipping the Engine creation
+ we don't even need a DBAPI to be available.
+
... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/alembic/env.py |
Write docstrings for this repository | from src.graph.state import AgentState, show_agent_reasoning
from src.tools.api import get_financial_metrics, get_market_cap, search_line_items, get_insider_trades, get_company_news
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage
from pydantic import BaseModel
impo... | --- +++ @@ -16,6 +16,10 @@
def charlie_munger_agent(state: AgentState, agent_id: str = "charlie_munger_agent"):
+ """
+ Analyzes stocks using Charlie Munger's investing principles and mental models.
+ Focuses on moat strength, management quality, predictability, and valuation.
+ """
data = state["d... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/charlie_munger.py |
Write docstrings describing functionality | from __future__ import annotations
import json
from typing_extensions import Literal
from pydantic import BaseModel
from src.graph.state import AgentState, show_agent_reasoning
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage
from src.tools.api import (
get_f... | --- +++ @@ -25,6 +25,14 @@
def aswath_damodaran_agent(state: AgentState, agent_id: str = "aswath_damodaran_agent"):
+ """
+ Analyze US equities through Aswath Damodaran's intrinsic-value lens:
+ • Cost of Equity via CAPM (risk-free + β·ERP)
+ • 5-yr revenue / FCFF growth trends & reinvestment effici... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/aswath_damodaran.py |
Fully document this Python code with docstrings | from src.graph.state import AgentState, show_agent_reasoning
from src.tools.api import get_financial_metrics, get_market_cap, search_line_items
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage
from pydantic import BaseModel
import json
from typing_extensions import ... | --- +++ @@ -18,6 +18,13 @@
def ben_graham_agent(state: AgentState, agent_id: str = "ben_graham_agent"):
+ """
+ Analyzes stocks using Benjamin Graham's classic value-investing principles:
+ 1. Earnings stability over multiple years.
+ 2. Solid financial strength (low debt, adequate liquidity).
+ 3. D... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/ben_graham.py |
Document classes and their methods | from typing import List, Optional
from sqlalchemy.orm import Session
from app.backend.database.models import HedgeFundFlow
class FlowRepository:
def __init__(self, db: Session):
self.db = db
def create_flow(self, name: str, nodes: dict, edges: dict, description: str = None,
... | --- +++ @@ -4,12 +4,14 @@
class FlowRepository:
+ """Repository for HedgeFundFlow CRUD operations"""
def __init__(self, db: Session):
self.db = db
def create_flow(self, name: str, nodes: dict, edges: dict, description: str = None,
viewport: dict = None, data: d... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/repositories/flow_repository.py |
Generate consistent documentation across files | import asyncio
import os
import sys
import platform
import subprocess
import time
import re
import json
import queue
import threading
from pathlib import Path
from typing import Dict, List, Optional, AsyncGenerator
import logging
import signal
import ollama
logger = logging.getLogger(__name__)
class OllamaService:
... | --- +++ @@ -17,6 +17,7 @@ logger = logging.getLogger(__name__)
class OllamaService:
+ """Service for managing Ollama integration in the backend."""
def __init__(self):
self._download_progress = {}
@@ -31,6 +32,7 @@ # =========================================================================... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/services/ollama_service.py |
Annotate my code with docstrings | from src.graph.state import AgentState, show_agent_reasoning
from src.tools.api import get_financial_metrics, get_market_cap, search_line_items
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage
from pydantic import BaseModel
import json
from typing_extensions import ... | --- +++ @@ -17,6 +17,11 @@
def bill_ackman_agent(state: AgentState, agent_id: str = "bill_ackman_agent"):
+ """
+ Analyzes stocks using Bill Ackman's investing principles and LLM reasoning.
+ Fetches multiple periods of data for a more robust long-term view.
+ Incorporates brand/competitive advantage, a... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/bill_ackman.py |
Write Python docstrings for this snippet | from __future__ import annotations
"""Valuation Agent
Implements four complementary valuation methodologies and aggregates them with
configurable weights.
"""
import json
import statistics
from langchain_core.messages import HumanMessage
from src.graph.state import AgentState, show_agent_reasoning
from src.utils.pr... | --- +++ @@ -19,6 +19,7 @@ )
def valuation_analyst_agent(state: AgentState, agent_id: str = "valuation_analyst_agent"):
+ """Run valuation across tickers and write signals back to `state`."""
data = state["data"]
end_date = data["end_date"]
@@ -232,6 +233,7 @@ margin_of_safety: float = 0.25,
n... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/valuation.py |
Expand my code with proper documentation strings | from typing import Dict, Optional, Any, Literal
from pydantic import BaseModel
class BaseEvent(BaseModel):
type: str
def to_sse(self) -> str:
event_type = self.type.lower()
return f"event: {event_type}\ndata: {self.model_dump_json()}\n\n"
class StartEvent(BaseEvent):
type: Literal["st... | --- +++ @@ -3,20 +3,24 @@
class BaseEvent(BaseModel):
+ """Base class for all Server-Sent Event events"""
type: str
def to_sse(self) -> str:
+ """Convert to Server-Sent Event format"""
event_type = self.type.lower()
return f"event: {event_type}\ndata: {self.model_dump_json(... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/models/events.py |
Create structured documentation for my script | import sys
from dotenv import load_dotenv
from langchain_core.messages import HumanMessage
from langgraph.graph import END, StateGraph
from colorama import Fore, Style, init
import questionary
from src.agents.portfolio_manager import portfolio_management_agent
from src.agents.risk_manager import risk_management_agent
... | --- +++ @@ -28,6 +28,7 @@
def parse_hedge_fund_response(response):
+ """Parses a JSON string and returns a dictionary."""
try:
return json.loads(response)
except json.JSONDecodeError as e:
@@ -92,10 +93,12 @@
def start(state: AgentState):
+ """Initialize the workflow with the input mess... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/main.py |
Generate docstrings for script automation |
import platform
import subprocess
import requests
import time
from typing import List
import questionary
from colorama import Fore, Style
import os
from . import docker
# Constants
DEFAULT_OLLAMA_SERVER_URL = "http://localhost:11434"
def _get_ollama_base_url() -> str:
url = os.environ.get("OLLAMA_BASE_URL", DEF... | --- +++ @@ -1,3 +1,4 @@+"""Utilities for working with Ollama models"""
import platform
import subprocess
@@ -14,6 +15,7 @@
def _get_ollama_base_url() -> str:
+ """Return the configured Ollama base URL, trimming any trailing slash."""
url = os.environ.get("OLLAMA_BASE_URL", DEFAULT_OLLAMA_SERVER_URL)
... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/utils/ollama.py |
Generate NumPy-style docstrings | from src.graph.state import AgentState, show_agent_reasoning
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage
from pydantic import BaseModel, Field
import json
from typing_extensions import Literal
from src.tools.api import get_financial_metrics, get_market_cap, sea... | --- +++ @@ -17,6 +17,7 @@
def warren_buffett_agent(state: AgentState, agent_id: str = "warren_buffett_agent"):
+ """Analyzes stocks using Buffett's principles and LLM reasoning."""
data = state["data"]
end_date = data["end_date"]
tickers = data["tickers"]
@@ -153,6 +154,7 @@
def analyze_fundam... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/warren_buffett.py |
Create docstrings for API functions | from src.graph.state import AgentState, show_agent_reasoning
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage
from pydantic import BaseModel
import json
from typing_extensions import Literal
from src.tools.api import get_financial_metrics, get_market_cap, search_lin... | --- +++ @@ -15,6 +15,7 @@ reasoning: str
def rakesh_jhunjhunwala_agent(state: AgentState, agent_id: str = "rakesh_jhunjhunwala_agent"):
+ """Analyzes stocks using Rakesh Jhunjhunwala's principles and LLM reasoning."""
data = state["data"]
end_date = data["end_date"]
tickers = data["tickers"]
@@... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/rakesh_jhunjhunwala.py |
Add clean documentation to messy code |
from src.agents import portfolio_manager
from src.agents.aswath_damodaran import aswath_damodaran_agent
from src.agents.ben_graham import ben_graham_agent
from src.agents.bill_ackman import bill_ackman_agent
from src.agents.cathie_wood import cathie_wood_agent
from src.agents.charlie_munger import charlie_munger_agent... | --- +++ @@ -1,3 +1,4 @@+"""Constants and utilities related to analysts configuration."""
from src.agents import portfolio_manager
from src.agents.aswath_damodaran import aswath_damodaran_agent
@@ -172,10 +173,12 @@
def get_analyst_nodes():
+ """Get the mapping of analyst keys to their (node_name, agent_func)... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/utils/analysts.py |
Document all public functions with docstrings | from fastapi import APIRouter, HTTPException, Depends
from sqlalchemy.orm import Session
from typing import List
from app.backend.database import get_db
from app.backend.repositories.api_key_repository import ApiKeyRepository
from app.backend.models.schemas import (
ApiKeyCreateRequest,
ApiKeyUpdateRequest,
... | --- +++ @@ -25,6 +25,7 @@ },
)
async def create_or_update_api_key(request: ApiKeyCreateRequest, db: Session = Depends(get_db)):
+ """Create a new API key or update existing one"""
try:
repo = ApiKeyRepository(db)
api_key = repo.create_or_update_api_key(
@@ -46,6 +47,7 @@ },
)
async... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/app/backend/routes/api_keys.py |
Write docstrings describing each step | import math
from langchain_core.messages import HumanMessage
from src.graph.state import AgentState, show_agent_reasoning
from src.utils.api_key import get_api_key_from_state
import json
import pandas as pd
import numpy as np
from src.tools.api import get_prices, prices_to_df
from src.utils.progress import progress
... | --- +++ @@ -13,6 +13,16 @@
def safe_float(value, default=0.0):
+ """
+ Safely convert a value to float, handling NaN cases
+
+ Args:
+ value: The value to convert (can be pandas scalar, numpy value, etc.)
+ default: Default value to return if the input is NaN or invalid
+
+ Returns... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/technicals.py |
Help me comply with documentation standards |
import requests
import time
from colorama import Fore, Style
import questionary
def ensure_ollama_and_model(model_name: str, ollama_url: str) -> bool:
print(f"{Fore.CYAN}Using Ollama endpoint at {ollama_url}{Style.RESET_ALL}")
# Step 1: Check if Ollama service is available
if not is_ollama_available(... | --- +++ @@ -1,3 +1,4 @@+"""Utilities for working with Ollama models in Docker environments"""
import requests
import time
@@ -5,6 +6,7 @@ import questionary
def ensure_ollama_and_model(model_name: str, ollama_url: str) -> bool:
+ """Ensure the Ollama model is available at the target Ollama endpoint."""
p... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/utils/docker.py |
Write docstrings describing each step | from src.graph.state import AgentState, show_agent_reasoning
from src.tools.api import (
get_financial_metrics,
get_market_cap,
search_line_items,
get_insider_trades,
get_company_news,
get_prices,
)
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMe... | --- +++ @@ -24,6 +24,15 @@
def stanley_druckenmiller_agent(state: AgentState, agent_id: str = "stanley_druckenmiller_agent"):
+ """
+ Analyzes stocks using Stanley Druckenmiller's investing principles:
+ - Seeking asymmetric risk-reward opportunities
+ - Emphasizing growth, momentum, and sentiment
+... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/stanley_druckenmiller.py |
Add inline docstrings for readability | # coding=utf-8
import json
import os
import re
import smtplib
import time
from datetime import datetime
from email.header import Header
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.utils import formataddr, formatdate, make_msgid
from pathlib import Path
from typing imp... | --- +++ @@ -1,4 +1,10 @@ # coding=utf-8
+"""
+通知推送工具
+
+支持向已配置的通知渠道发送消息，自动检测 config.yaml 和 .env 中的渠道配置。
+接受 markdown 格式内容，内部按各渠道要求自动转换格式后发送。
+"""
import json
import os
@@ -89,6 +95,20 @@
def _split_text_into_batches(text: str, max_bytes: int) -> List[str]:
+ """将文本按字节限制分批，优先在段落边界（双换行）切割
+
+ 分割策略（参考 trendr... | https://raw.githubusercontent.com/sansan0/TrendRadar/HEAD/mcp_server/tools/notification.py |
Add docstrings to my Python code | from __future__ import annotations
"""Growth Agent
Implements a growth-focused valuation methodology.
"""
import json
import statistics
from langchain_core.messages import HumanMessage
from src.graph.state import AgentState, show_agent_reasoning
from src.utils.progress import progress
from src.utils.api_key import g... | --- +++ @@ -17,6 +17,7 @@ )
def growth_analyst_agent(state: AgentState, agent_id: str = "growth_analyst_agent"):
+ """Run growth analysis across tickers and write signals back to `state`."""
data = state["data"]
end_date = data["end_date"]
@@ -135,6 +136,7 @@ #############################
def _calc... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/growth_agent.py |
Generate missing documentation strings |
from typing import Dict, List, Optional, Union
from ..services.data_service import DataService
from ..utils.validators import (
validate_platforms,
validate_limit,
validate_keyword,
validate_date_range,
validate_top_n,
validate_mode,
validate_date_query,
normalize_date_range
)
from ..u... | --- +++ @@ -1,3 +1,8 @@+"""
+数据查询工具
+
+实现P0核心的数据查询工具。
+"""
from typing import Dict, List, Optional, Union
@@ -16,8 +21,15 @@
class DataQueryTools:
+ """数据查询工具类"""
def __init__(self, project_root: str = None):
+ """
+ 初始化数据查询工具
+
+ Args:
+ project_root: 项目根目录
+ "... | https://raw.githubusercontent.com/sansan0/TrendRadar/HEAD/mcp_server/tools/data_query.py |
Include argument descriptions in docstrings | class Cache:
def __init__(self):
self._prices_cache: dict[str, list[dict[str, any]]] = {}
self._financial_metrics_cache: dict[str, list[dict[str, any]]] = {}
self._line_items_cache: dict[str, list[dict[str, any]]] = {}
self._insider_trades_cache: dict[str, list[dict[str, any]]] = {}... | --- +++ @@ -1,4 +1,5 @@ class Cache:
+ """In-memory cache for API responses."""
def __init__(self):
self._prices_cache: dict[str, list[dict[str, any]]] = {}
@@ -8,6 +9,7 @@ self._company_news_cache: dict[str, list[dict[str, any]]] = {}
def _merge_data(self, existing: list[dict] | None,... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/data/cache.py |
Generate descriptive docstrings automatically |
import re
from collections import Counter
from datetime import datetime, timedelta
from typing import Dict, List, Optional, Tuple
from .cache_service import get_cache
from .parser_service import ParserService
from ..utils.errors import DataNotFoundError
class DataService:
# 中文停用词列表（用于 auto_extract 模式）
STOP... | --- +++ @@ -1,3 +1,8 @@+"""
+数据访问服务
+
+提供统一的数据查询接口,封装数据访问逻辑。
+"""
import re
from collections import Counter
@@ -10,6 +15,7 @@
class DataService:
+ """数据访问服务类"""
# 中文停用词列表（用于 auto_extract 模式）
STOPWORDS = {
@@ -28,6 +34,12 @@ }
def __init__(self, project_root: str = None):
+ """
+... | https://raw.githubusercontent.com/sansan0/TrendRadar/HEAD/mcp_server/services/data_service.py |
Add clean documentation to messy code | from src.graph.state import AgentState, show_agent_reasoning
from src.tools.api import get_financial_metrics, get_market_cap, search_line_items
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage
from pydantic import BaseModel
import json
from typing_extensions import ... | --- +++ @@ -17,6 +17,7 @@
def mohnish_pabrai_agent(state: AgentState, agent_id: str = "mohnish_pabrai_agent"):
+ """Evaluate stocks using Mohnish Pabrai's checklist and 'heads I win, tails I don't lose much' approach."""
data = state["data"]
end_date = data["end_date"]
tickers = data["tickers"]
@@... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/mohnish_pabrai.py |
Create documentation strings for testing functions |
import re
import sqlite3
from pathlib import Path
from typing import Dict, List, Tuple, Optional
from datetime import datetime
import yaml
from ..utils.errors import FileParseError, DataNotFoundError
from .cache_service import get_cache
class ParserService:
def __init__(self, project_root: str = None):
... | --- +++ @@ -1,3 +1,9 @@+"""
+数据解析服务
+
+v2.0.0: 仅支持 SQLite 数据库，移除 TXT 文件支持
+新存储结构：output/{type}/{date}.db
+"""
import re
import sqlite3
@@ -12,8 +18,15 @@
class ParserService:
+ """数据解析服务类"""
def __init__(self, project_root: str = None):
+ """
+ 初始化解析服务
+
+ Args:
+ proje... | https://raw.githubusercontent.com/sansan0/TrendRadar/HEAD/mcp_server/services/parser_service.py |
Add standardized docstrings across the file | import datetime
import logging
import os
import pandas as pd
import requests
import time
logger = logging.getLogger(__name__)
from src.data.cache import get_cache
from src.data.models import (
CompanyNews,
CompanyNewsResponse,
FinancialMetrics,
FinancialMetricsResponse,
Price,
PriceResponse,
... | --- +++ @@ -27,6 +27,22 @@
def _make_api_request(url: str, headers: dict, method: str = "GET", json_data: dict = None, max_retries: int = 3) -> requests.Response:
+ """
+ Make an API request with rate limiting handling and moderate backoff.
+
+ Args:
+ url: The URL to request
+ headers: H... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/tools/api.py |
Generate docstrings with parameter types | import os
import json
from langchain_anthropic import ChatAnthropic
from langchain_deepseek import ChatDeepSeek
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_groq import ChatGroq
from langchain_xai import ChatXAI
from langchain_openai import ChatOpenAI, AzureChatOpenAI
from langchain_gigachat... | --- +++ @@ -15,6 +15,7 @@
class ModelProvider(str, Enum):
+ """Enum for supported LLM providers"""
ALIBABA = "Alibaba"
ANTHROPIC = "Anthropic"
@@ -32,18 +33,22 @@
class LLMModel(BaseModel):
+ """Represents an LLM model configuration"""
display_name: str
model_name: str
provide... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/llm/models.py |
Create docstrings for all classes and functions | from src.graph.state import AgentState, show_agent_reasoning
from src.tools.api import (
get_market_cap,
search_line_items,
get_insider_trades,
get_company_news,
)
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage
from pydantic import BaseModel
import... | --- +++ @@ -22,6 +22,17 @@
def phil_fisher_agent(state: AgentState, agent_id: str = "phil_fisher_agent"):
+ """
+ Analyzes stocks using Phil Fisher's investing principles:
+ - Seek companies with long-term above-average growth potential
+ - Emphasize quality of management and R&D
+ - Look for s... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/phil_fisher.py |
Add professional docstrings to my codebase | from src.graph.state import AgentState, show_agent_reasoning
from src.tools.api import (
get_market_cap,
search_line_items,
get_insider_trades,
get_company_news,
)
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.messages import HumanMessage
from pydantic import BaseModel
import... | --- +++ @@ -16,12 +16,28 @@
class PeterLynchSignal(BaseModel):
+ """
+ Container for the Peter Lynch-style output signal.
+ """
signal: Literal["bullish", "bearish", "neutral"]
confidence: float
reasoning: str
def peter_lynch_agent(state: AgentState, agent_id: str = "peter_lynch_agent")... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/peter_lynch.py |
Improve documentation using docstrings |
from typing import Dict, Optional, Any, TypedDict
from ..services.data_service import DataService
from ..utils.validators import validate_config_section
from ..utils.errors import MCPError
class ErrorInfo(TypedDict, total=False):
code: str
message: str
suggestion: str
class ConfigResult(TypedDict):
... | --- +++ @@ -1,3 +1,8 @@+"""
+配置管理工具
+
+实现配置查询和管理功能。
+"""
from typing import Dict, Optional, Any, TypedDict
@@ -7,12 +12,14 @@
class ErrorInfo(TypedDict, total=False):
+ """错误信息结构"""
code: str
message: str
suggestion: str
class ConfigResult(TypedDict):
+ """配置查询结果 - success 字段必需，其他字段可选... | https://raw.githubusercontent.com/sansan0/TrendRadar/HEAD/mcp_server/tools/config_mgmt.py |
Include argument descriptions in docstrings | from __future__ import annotations
from datetime import datetime, timedelta
import json
from typing_extensions import Literal
from src.graph.state import AgentState, show_agent_reasoning
from langchain_core.messages import HumanMessage
from langchain_core.prompts import ChatPromptTemplate
from pydantic import BaseMod... | --- +++ @@ -22,6 +22,7 @@
class MichaelBurrySignal(BaseModel):
+ """Schema returned by the LLM."""
signal: Literal["bullish", "bearish", "neutral"]
confidence: float # 0–100
@@ -29,6 +30,7 @@
def michael_burry_agent(state: AgentState, agent_id: str = "michael_burry_agent"):
+ """Analyse stock... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/michael_burry.py |
Fully document this Python code with docstrings |
import time
from typing import Dict, List
import requests
from ..utils.errors import MCPError, InvalidParameterError
# Jina Reader 配置
JINA_READER_BASE = "https://r.jina.ai"
DEFAULT_TIMEOUT = 30 # 秒
MAX_BATCH_SIZE = 5 # 单次批量最大篇数
BATCH_INTERVAL = 5.0 # 批量请求间隔（秒）
class ArticleReaderTools:
def __init__(self,... | --- +++ @@ -1,3 +1,10 @@+"""
+文章内容读取工具
+
+通过 Jina AI Reader API 将 URL 转换为 LLM 友好的 Markdown 格式。
+支持单篇和批量读取，内置速率限制和并发控制。
+
+"""
import time
from typing import Dict, List
@@ -15,13 +22,22 @@
class ArticleReaderTools:
+ """文章内容读取工具类"""
def __init__(self, project_root: str = None, jina_api_key: str = None)... | https://raw.githubusercontent.com/sansan0/TrendRadar/HEAD/mcp_server/tools/article_reader.py |
Write docstrings for data processing functions |
import hashlib
import json
import time
from typing import Any, Optional
from threading import Lock
def make_cache_key(namespace: str, **params) -> str:
if not params:
return namespace
# 对参数进行规范化处理
normalized_params = {}
for k, v in params.items():
if v is None:
continue ... | --- +++ @@ -1,3 +1,8 @@+"""
+缓存服务
+
+实现TTL缓存机制，提升数据访问性能。
+"""
import hashlib
import json
@@ -7,6 +12,24 @@
def make_cache_key(namespace: str, **params) -> str:
+ """
+ 生成结构化缓存 key
+
+ 通过对参数排序和哈希，确保相同参数组合总是生成相同的 key。
+
+ Args:
+ namespace: 缓存命名空间，如 "latest_news", "trending_topics"
+ **p... | https://raw.githubusercontent.com/sansan0/TrendRadar/HEAD/mcp_server/services/cache_service.py |
Add standardized docstrings across the file | from datetime import datetime, timezone
from rich.console import Console
from rich.live import Live
from rich.table import Table
from rich.style import Style
from rich.text import Text
from typing import Dict, Optional, Callable, List
console = Console()
class AgentProgress:
def __init__(self):
self.age... | --- +++ @@ -10,6 +10,7 @@
class AgentProgress:
+ """Manages progress tracking for multiple agents."""
def __init__(self):
self.agent_status: Dict[str, Dict[str, str]] = {}
@@ -19,24 +20,29 @@ self.update_handlers: List[Callable[[str, Optional[str], str], None]] = []
def register_ha... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/utils/progress.py |
Generate missing documentation strings | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import sys
import subprocess
import time
import signal
from pathlib import Path
from datetime import datetime
# Web 服务器配置
WEBSERVER_PORT = int(os.environ.get("WEBSERVER_PORT", "8080"))
WEBSERVER_DIR = "/app/output"
WEBSERVER_PID_FILE = "/tmp/webserver.pid"
WEBS... | --- +++ @@ -1,5 +1,8 @@ #!/usr/bin/env python3
# -*- coding: utf-8 -*-
+"""
+新闻爬虫容器管理工具 - supercronic
+"""
import os
import sys
@@ -17,6 +20,7 @@
def _env_bool(name: str, default: bool) -> bool:
+ """读取布尔环境变量，兼容 true/1/yes/on。"""
value = os.environ.get(name)
if value is None:
return defau... | https://raw.githubusercontent.com/sansan0/TrendRadar/HEAD/docker/manage.py |
Create documentation strings for testing functions | from langchain_core.messages import HumanMessage
from src.graph.state import AgentState, show_agent_reasoning
from src.utils.progress import progress
from src.tools.api import get_prices, prices_to_df
import json
import numpy as np
import pandas as pd
from src.utils.api_key import get_api_key_from_state
##### Risk Man... | --- +++ @@ -9,6 +9,7 @@
##### Risk Management Agent #####
def risk_management_agent(state: AgentState, agent_id: str = "risk_management_agent"):
+ """Controls position sizing based on volatility-adjusted risk factors for multiple tickers."""
portfolio = state["data"]["portfolio"]
data = state["data"]
... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/risk_manager.py |
Write docstrings for this repository |
import asyncio
import json
from typing import List, Optional, Dict, Union
from fastmcp import FastMCP
from .tools.data_query import DataQueryTools
from .tools.analytics import AnalyticsTools
from .tools.search_tools import SearchTools
from .tools.config_mgmt import ConfigManagementTools
from .tools.system import Sys... | --- +++ @@ -1,3 +1,9 @@+"""
+TrendRadar MCP Server - FastMCP 2.0 实现
+
+使用 FastMCP 2.0 提供生产级 MCP 工具服务器。
+支持 stdio 和 HTTP 两种传输模式。
+"""
import asyncio
import json
@@ -25,6 +31,7 @@
def _get_tools(project_root: Optional[str] = None):
+ """获取或创建工具实例（单例模式）"""
if not _tools_instances:
_tools_instances... | https://raw.githubusercontent.com/sansan0/TrendRadar/HEAD/mcp_server/server.py |
Annotate my code with docstrings |
import os
import re
from collections import Counter, defaultdict
from datetime import datetime, timedelta
from typing import Dict, List, Optional, Union
from difflib import SequenceMatcher
import yaml
from trendradar.core.analyzer import calculate_news_weight as _calculate_news_weight
from ..services.data_service i... | --- +++ @@ -1,3 +1,8 @@+"""
+高级数据分析工具
+
+提供热度趋势分析、平台对比、关键词共现、情感分析等高级分析功能。
+"""
import os
import re
@@ -35,6 +40,14 @@
def _get_weight_config() -> Dict:
+ """
+ 从 config.yaml 读取权重配置（带 mtime 缓存）
+
+ 仅当配置文件被修改时才重新读取，避免循环内重复 IO。
+
+ Returns:
+ 权重配置字典，包含 RANK_WEIGHT, FREQUENCY_WEIGHT, HOTNESS_WEIG... | https://raw.githubusercontent.com/sansan0/TrendRadar/HEAD/mcp_server/tools/analytics.py |
Write documentation strings for class attributes |
from langchain_core.messages import HumanMessage
from pydantic import BaseModel, Field
from src.data.models import CompanyNews
import pandas as pd
import numpy as np
import json
from src.graph.state import AgentState, show_agent_reasoning
from src.tools.api import get_company_news
from src.utils.api_key import get_a... | --- +++ @@ -16,12 +16,27 @@
class Sentiment(BaseModel):
+ """Represents the sentiment of a news article."""
sentiment: Literal["positive", "negative", "neutral"]
confidence: int = Field(description="Confidence 0-100")
def news_sentiment_agent(state: AgentState, agent_id: str = "news_sentiment_ag... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/news_sentiment.py |
Add detailed docstrings explaining each function | import json
import time
from langchain_core.messages import HumanMessage
from langchain_core.prompts import ChatPromptTemplate
from src.graph.state import AgentState, show_agent_reasoning
from pydantic import BaseModel, Field
from typing_extensions import Literal
from src.utils.progress import progress
from src.utils.... | --- +++ @@ -23,6 +23,7 @@
##### Portfolio Management Agent #####
def portfolio_management_agent(state: AgentState, agent_id: str = "portfolio_manager"):
+ """Makes final trading decisions and generates orders for multiple tickers"""
portfolio = state["data"]["portfolio"]
analyst_signals = state["data"... | https://raw.githubusercontent.com/virattt/ai-hedge-fund/HEAD/src/agents/portfolio_manager.py |
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