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TradingAgents
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typecheck with pyrefly

This commit is contained in:
Martin C. Richards 2025-08-16 13:52:37 +02:00
parent 1cfe018f77
commit fd45639ad6
32 changed files with 220347 additions and 128 deletions
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14
.mise.toml
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@ -2,12 +2,10 @@
python = "3.13"
uv = "latest"
ruff = "latest"
"npm:pyright" = "latest"
[env]
_.file = ".env"
# Python environment settings
PYTHONPATH = "."
PYTHONDONTWRITEBYTECODE = "1"
PYTHONUNBUFFERED = "1"
@ -40,8 +38,8 @@ description = "Format code with ruff"
run = "ruff format ."
[tasks.typecheck]
description = "Run pyright type checking"
run = "pyright"
description = "Run pyrefly type checking"
run = "uv run pyrefly check ."
[tasks.fix]
description = "Auto-fix linting issues"
@ -49,7 +47,7 @@ run = "ruff check --fix ."
[tasks.all]
description = "Run format, lint, and typecheck"
run = ["ruff format .", "ruff check .", "pyright"]
run = ["ruff format .", "ruff check .", "uv run pyrefly check ."]
[tasks.clean]
description = "Clean up cache and build artifacts"
@ -60,9 +58,5 @@ run = [
"rm -rf .ruff_cache",
"rm -rf dist",
"rm -rf build",
"rm -rf *.egg-info"
"rm -rf *.egg-info",
]
[tasks.litellm]
run = "uvx --from litellm[proxy] litellm --config litellm.yml --port 4000"
description = "Start LiteLLM proxy for Claude Code → OpenRouter"

92
cli/main.py
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@ -2,6 +2,7 @@ import datetime
from collections import deque
from functools import wraps
from pathlib import Path
from typing import Literal, cast
import typer
from rich import box
@ -16,6 +17,7 @@ from rich.spinner import Spinner
from rich.table import Table
from rich.text import Text
from cli.models import AnalystType
from cli.utils import (
get_analysis_date,
get_ticker,
@ -39,6 +41,9 @@ app = typer.Typer(
# Create a deque to store recent messages with a maximum length
class MessageBuffer:
current_report: str | None
final_report: str | None
def __init__(self, max_length=100):
self.messages = deque(maxlen=max_length)
self.tool_calls = deque(maxlen=max_length)
@ -304,7 +309,7 @@ def update_display(layout, spinner_text=None):
content_str = content
if isinstance(content, list):
# Handle list of content blocks (Anthropic format)
text_parts = []
text_parts: list[str] = []
for item in content:
if isinstance(item, dict):
if item.get("type") == "text":
@ -396,7 +401,7 @@ def update_display(layout, spinner_text=None):
layout["footer"].update(Panel(stats_table, border_style="grey50"))
def get_user_selections():
def get_user_selections() -> dict[str, str | int | list[AnalystType]]:
"""Get all user selections before starting the analysis display."""
# Display ASCII art welcome message
with open("./cli/static/welcome.txt") as f:
@ -698,7 +703,7 @@ def extract_content_string(content):
return content
elif isinstance(content, list):
# Handle Anthropic's list format
text_parts = []
text_parts: list[str] = []
for item in content:
if isinstance(item, dict):
if item.get("type") == "text":
@ -717,23 +722,51 @@ def run_analysis():
selections = get_user_selections()
# Create config with selected research depth
research_depth = selections["research_depth"]
shallow_thinker = selections["shallow_thinker"]
deep_thinker = selections["deep_thinker"]
backend_url = selections["backend_url"]
llm_provider = selections["llm_provider"]
config = TradingAgentsConfig(
max_debate_rounds=selections["research_depth"],
max_risk_discuss_rounds=selections["research_depth"],
quick_think_llm=selections["shallow_thinker"],
deep_think_llm=selections["deep_thinker"],
backend_url=selections["backend_url"],
llm_provider=selections["llm_provider"].lower(),
max_debate_rounds=research_depth if isinstance(research_depth, int) else 1,
max_risk_discuss_rounds=research_depth
if isinstance(research_depth, int)
else 1,
quick_think_llm=shallow_thinker
if isinstance(shallow_thinker, str)
else "gpt-4o-mini",
deep_think_llm=deep_thinker if isinstance(deep_thinker, str) else "o4-mini",
backend_url=backend_url
if isinstance(backend_url, str)
else "https://api.openai.com/v1",
llm_provider=cast(
"Literal['openai', 'anthropic', 'google', 'ollama', 'openrouter']",
"openai"
if not isinstance(llm_provider, str)
else (
llm_provider.lower()
if llm_provider.lower()
in ["openai", "anthropic", "google", "ollama", "openrouter"]
else "openai"
),
),
)
# Initialize the graph
graph = TradingAgentsGraph(
[analyst.value for analyst in selections["analysts"]], config=config, debug=True
)
analysts_list = selections["analysts"]
if isinstance(analysts_list, list):
analyst_values = [analyst.value for analyst in analysts_list]
else:
analyst_values = []
graph = TradingAgentsGraph(analyst_values, config=config, debug=True)
# Create result directory
results_dir = (
Path(config.results_dir) / selections["ticker"] / selections["analysis_date"]
Path(config.results_dir)
/ str(selections["ticker"])
/ str(selections["analysis_date"])
)
results_dir.mkdir(parents=True, exist_ok=True)
report_dir = results_dir / "reports"
@ -805,9 +838,14 @@ def run_analysis():
message_buffer.add_message(
"System", f"Analysis date: {selections['analysis_date']}"
)
analysts_list = selections["analysts"]
if isinstance(analysts_list, list):
analysts_str = ", ".join(analyst.value for analyst in analysts_list)
else:
analysts_str = "None"
message_buffer.add_message(
"System",
f"Selected analysts: {', '.join(analyst.value for analyst in selections['analysts'])}",
f"Selected analysts: {analysts_str}",
)
update_display(layout)
@ -822,7 +860,11 @@ def run_analysis():
message_buffer.final_report = None
# Update agent status to in_progress for the first analyst
first_analyst = f"{selections['analysts'][0].value.capitalize()} Analyst"
analysts_list = selections["analysts"]
if isinstance(analysts_list, list) and len(analysts_list) > 0:
first_analyst = f"{analysts_list[0].value.capitalize()} Analyst"
else:
first_analyst = "Market Analyst"
message_buffer.update_agent_status(first_analyst, "in_progress")
update_display(layout)
@ -834,7 +876,7 @@ def run_analysis():
# Initialize state and get graph args
init_agent_state = graph.propagator.create_initial_state(
selections["ticker"], selections["analysis_date"]
str(selections["ticker"]), str(selections["analysis_date"])
)
args = graph.propagator.get_graph_args()
@ -877,7 +919,11 @@ def run_analysis():
)
message_buffer.update_agent_status("Market Analyst", "completed")
# Set next analyst to in_progress
if "social" in selections["analysts"]:
analysts_list = selections["analysts"]
if (
isinstance(analysts_list, list)
and AnalystType.SOCIAL in analysts_list
):
message_buffer.update_agent_status(
"Social Analyst", "in_progress"
)
@ -888,7 +934,11 @@ def run_analysis():
)
message_buffer.update_agent_status("Social Analyst", "completed")
# Set next analyst to in_progress
if "news" in selections["analysts"]:
analysts_list = selections["analysts"]
if (
isinstance(analysts_list, list)
and AnalystType.NEWS in analysts_list
):
message_buffer.update_agent_status(
"News Analyst", "in_progress"
)
@ -899,7 +949,11 @@ def run_analysis():
)
message_buffer.update_agent_status("News Analyst", "completed")
# Set next analyst to in_progress
if "fundamentals" in selections["analysts"]:
analysts_list = selections["analysts"]
if (
isinstance(analysts_list, list)
and AnalystType.FUNDAMENTALS in analysts_list
):
message_buffer.update_agent_status(
"Fundamentals Analyst", "in_progress"
)

1
pyproject.toml
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@ -137,6 +137,7 @@ markers = [
[dependency-groups]
dev = [
"pyrefly>=0.28.1",
"pytest>=8.4.1",
"pytest-asyncio>=1.1.0",
"pytest-cov>=6.2.1",

5
pyrefly.toml Normal file
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@ -0,0 +1,5 @@
python-version = "3.13.0"
search_path = ["."] # Changed from src-roots
[errors]
import-error = "warn"

3
pyrightconfig.json
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@ -7,6 +7,5 @@
"reportMissingTypeStubs": false,
"useLibraryCodeForTypes": true,
"autoSearchPaths": true,
"extraPaths": [],
"stubPath": "typings"
"extraPaths": []
}

5
tests/conftest.py
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@ -49,7 +49,10 @@ def temp_data_dir():
"""Temporary directory for testing real repository persistence."""
temp_dir = tempfile.mkdtemp()
yield temp_dir
shutil.rmtree(temp_dir)
try:
shutil.rmtree(temp_dir)
except OSError:
pass # Directory might already be deleted
@pytest.fixture

10
tests/domains/news/test_google_news_client.py
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@ -2,7 +2,7 @@
Tests for Google News RSS feed client using pytest-vcr.
"""
from datetime import datetime
from datetime import datetime, timezone
from unittest.mock import Mock, patch
import feedparser
@ -139,9 +139,9 @@ class TestGoogleNewsClient:
mock_entry.id = "guid-456"
# Should use current time as fallback
before = datetime.utcnow()
before = datetime.now(timezone.utc).replace(tzinfo=None)
article = client._parse_feed_entry(mock_entry)
after = datetime.utcnow()
after = datetime.now(timezone.utc).replace(tzinfo=None)
assert before <= article.published <= after
assert article.title == "Breaking News"
@ -259,7 +259,7 @@ class TestGoogleNewsClient:
GoogleNewsArticle(
title="Tech News",
link="https://tech.com",
published=datetime.utcnow(),
published=datetime.now(timezone.utc).replace(tzinfo=None),
summary="Tech summary",
source="TechSite",
guid="tech-1",
@ -351,7 +351,7 @@ class TestIntegrationScenarios:
successful_article = GoogleNewsArticle(
title="Success",
link="https://success.com",
published=datetime.utcnow(),
published=datetime.now(timezone.utc).replace(tzinfo=None),
summary="Successful fetch",
source="GoodSource",
guid="success-1",

6
tests/domains/news/test_news_service.py
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@ -12,9 +12,6 @@ from unittest.mock import Mock
import pytest
# Import mock ScrapeResult from conftest to avoid newspaper3k import issues
from conftest import ScrapeResult
from tradingagents.domains.news.news_repository import (
NewsData,
)
@ -26,6 +23,9 @@ from tradingagents.domains.news.news_service import (
SentimentScore,
)
# Import mock ScrapeResult from conftest to avoid newspaper3k import issues
from ...conftest import ScrapeResult
class TestNewsServiceCollaboratorInteractions:
"""Test NewsService interactions with its collaborators (I/O boundaries)."""

14992
tests/fixtures/vcr_cassettes/news/TestArticleScraperClient.test_scrape_article_barchart.yaml vendored Normal file
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tests/fixtures/vcr_cassettes/news/TestArticleScraperClient.test_scrape_article_bloomberg.yaml vendored Normal file
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tests/fixtures/vcr_cassettes/news/TestArticleScraperClient.test_scrape_article_business_insider.yaml vendored Normal file
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tests/fixtures/vcr_cassettes/news/TestArticleScraperClient.test_scrape_article_cnbc.yaml vendored Normal file
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tests/fixtures/vcr_cassettes/news/TestArticleScraperClient.test_scrape_article_forbes.yaml vendored Normal file
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293
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tests/fixtures/vcr_cassettes/news/TestArticleScraperClient.test_scrape_article_reuters.yaml vendored Normal file
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65678
tests/fixtures/vcr_cassettes/news/TestArticleScraperClient.test_scrape_article_yahoo_finance.yaml vendored Normal file
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73225
tests/fixtures/vcr_cassettes/news/TestArticleScraperClient.test_scrape_multiple_financial_sites.yaml vendored Normal file
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20
tradingagents/agents/libs/memory.py
View File

@ -13,19 +13,19 @@ class FinancialSituationMemory:
self.chroma_client = chromadb.Client(Settings(allow_reset=True))
self.situation_collection = self.chroma_client.create_collection(name=name)
def get_embedding(self, text):
def get_embedding(self, text) -> list[float]:
"""Get OpenAI embedding for a text"""
response = self.client.embeddings.create(model=self.embedding, input=text)
return response.data[0].embedding
def add_situations(self, situations_and_advice):
"""Add financial situations and their corresponding advice. Parameter is a list of tuples (situation, rec)"""
from typing import Any
situations = []
advice = []
ids = []
embeddings = []
situations: list[str] = []
advice: list[str] = []
ids: list[str] = []
embeddings: list[Any] = [] # ChromaDB expects flexible embedding types
offset = self.situation_collection.count()
@ -44,10 +44,11 @@ class FinancialSituationMemory:
def get_memories(self, current_situation, n_matches=1):
"""Find matching recommendations using OpenAI embeddings"""
query_embedding = self.get_embedding(current_situation)
results = self.situation_collection.query(
query_embeddings=[query_embedding],
query_embeddings=[query_embedding], # type: ignore
n_results=n_matches,
include=["metadatas", "documents", "distances"],
)
@ -58,6 +59,8 @@ class FinancialSituationMemory:
and "documents" in results
and results["documents"]
and len(results["documents"]) > 0
and results["documents"][0] is not None
and len(results["documents"][0]) > 0
):
for i in range(len(results["documents"][0])):
if (
@ -70,6 +73,9 @@ class FinancialSituationMemory:
and len(results["distances"]) > 0
and i < len(results["distances"][0])
):
# Type checker satisfaction - we've already checked these exist
assert results["documents"] is not None
assert results["documents"][0] is not None
matched_results.append(
{
"matched_situation": results["documents"][0][i],

22
tradingagents/domains/marketdata/clients/yfinance_client.py
View File

@ -3,7 +3,7 @@ Yahoo Finance client for live market data.
"""
import logging
from datetime import datetime, timedelta
from datetime import datetime, timedelta, timezone
from typing import Any
import pandas as pd
@ -99,7 +99,9 @@ class YFinanceClient:
"source": "yahoo_finance",
"record_count": len(records),
"columns": list(data.columns),
"retrieved_at": datetime.utcnow().isoformat(),
"retrieved_at": datetime.now(timezone.utc)
.replace(tzinfo=None)
.isoformat(),
},
}
@ -126,7 +128,9 @@ class YFinanceClient:
"info": info,
"metadata": {
"source": "yahoo_finance",
"retrieved_at": datetime.utcnow().isoformat(),
"retrieved_at": datetime.now(timezone.utc)
.replace(tzinfo=None)
.isoformat(),
},
}
@ -138,7 +142,9 @@ class YFinanceClient:
"metadata": {
"source": "yahoo_finance",
"error": str(e),
"retrieved_at": datetime.utcnow().isoformat(),
"retrieved_at": datetime.now(timezone.utc)
.replace(tzinfo=None)
.isoformat(),
},
}
@ -177,7 +183,9 @@ class YFinanceClient:
"quarterly": {},
"metadata": {
"source": "yahoo_finance",
"retrieved_at": datetime.utcnow().isoformat(),
"retrieved_at": datetime.now(timezone.utc)
.replace(tzinfo=None)
.isoformat(),
},
}
@ -209,7 +217,9 @@ class YFinanceClient:
"metadata": {
"source": "yahoo_finance",
"error": str(e),
"retrieved_at": datetime.utcnow().isoformat(),
"retrieved_at": datetime.now(timezone.utc)
.replace(tzinfo=None)
.isoformat(),
},
}

105
tradingagents/domains/marketdata/market_data_service.py
View File

@ -3,8 +3,8 @@ Market data service that provides structured market context.
"""
import logging
from datetime import datetime
from typing import Any
from datetime import datetime, timezone
from typing import Any, cast
import pandas as pd
import talib
@ -18,6 +18,8 @@ from tradingagents.domains.marketdata.models import (
IndicatorParamValue,
IndicatorPresets,
InputSpec,
OutputSpec,
ParamRanges,
PriceDataContext,
TAReportContext,
TechnicalAnalysisError,
@ -125,7 +127,9 @@ class MarketDataService:
"service": "market_data",
"record_count": len(price_data),
"source": "repository" if not df.empty else "client",
"retrieved_at": datetime.utcnow().isoformat(),
"retrieved_at": datetime.now(timezone.utc)
.replace(tzinfo=None)
.isoformat(),
}
return PriceDataContext(
@ -153,7 +157,9 @@ class MarketDataService:
"data_quality": DataQuality.LOW.value,
"service": "market_data",
"error": str(e),
"retrieved_at": datetime.utcnow().isoformat(),
"retrieved_at": datetime.now(timezone.utc)
.replace(tzinfo=None)
.isoformat(),
},
)
@ -224,27 +230,23 @@ class MarketDataService:
)
# Create indicator config from the calculation
definition = INDICATOR_DEFINITIONS.get(indicator.upper(), {})
indicator_config = IndicatorConfig(
name=indicator.upper(),
parameters=indicator_data[0].parameters if indicator_data else {},
input_types=INDICATOR_DEFINITIONS.get(indicator.upper(), {}).get(
"input_types", ["close"]
input_types=cast(
"list[InputSpec]", definition.get("input_types", ["close"])
),
output_format=INDICATOR_DEFINITIONS.get(indicator.upper(), {}).get(
"output_format", "single"
output_format=cast(
"OutputSpec", definition.get("output_format", "single")
),
param_ranges=INDICATOR_DEFINITIONS.get(indicator.upper(), {}).get(
"param_ranges", {}
),
default_params=INDICATOR_DEFINITIONS.get(indicator.upper(), {}).get(
"default_params", {}
),
talib_function=INDICATOR_DEFINITIONS.get(indicator.upper(), {}).get(
"talib_function", ""
),
description=INDICATOR_DEFINITIONS.get(indicator.upper(), {}).get(
"description", ""
param_ranges=cast("ParamRanges", definition.get("param_ranges", {})),
default_params=cast(
"dict[str, IndicatorParamValue]",
definition.get("default_params", {}),
),
talib_function=str(definition.get("talib_function", "")),
description=str(definition.get("description", "")),
)
# Generate parameter summary
@ -265,7 +267,9 @@ class MarketDataService:
"data_quality": DataQuality.HIGH.value,
"service": "technical_analysis",
"indicator_count": len(indicator_data),
"retrieved_at": datetime.utcnow().isoformat(),
"retrieved_at": datetime.now(timezone.utc)
.replace(tzinfo=None)
.isoformat(),
},
)
@ -308,19 +312,21 @@ class MarketDataService:
raise TechnicalAnalysisError(f"Unknown indicator: {indicator}")
definition = INDICATOR_DEFINITIONS[indicator.upper()]
param_ranges = definition.get("param_ranges", {})
param_ranges = cast("ParamRanges", definition.get("param_ranges", {}))
for param_name, value in params.items():
if param_name in param_ranges:
min_val, max_val = param_ranges[param_name]
if not isinstance(value, int | float):
raise TechnicalAnalysisError(
f"Parameter {param_name} must be numeric"
)
if not (min_val <= value <= max_val):
raise TechnicalAnalysisError(
f"Parameter {param_name}={value} out of range [{min_val}, {max_val}]"
)
range_tuple = param_ranges[param_name]
if isinstance(range_tuple, tuple) and len(range_tuple) == 2:
min_val, max_val = range_tuple
if not isinstance(value, int | float):
raise TechnicalAnalysisError(
f"Parameter {param_name} must be numeric"
)
if not (min_val <= value <= max_val):
raise TechnicalAnalysisError(
f"Parameter {param_name}={value} out of range [{min_val}, {max_val}]"
)
def _prepare_price_arrays(
self, price_data: list[dict[str, Any]], input_types: list[InputSpec]
@ -383,20 +389,26 @@ class MarketDataService:
# Use provided params or defaults
final_params: dict[str, IndicatorParamValue]
if params is None:
final_params = definition["default_params"].copy()
final_params = cast(
"dict[str, IndicatorParamValue]", definition["default_params"]
)
else:
# Merge with defaults for missing parameters
final_params = definition["default_params"].copy()
final_params = cast(
"dict[str, IndicatorParamValue]", definition["default_params"]
).copy()
final_params.update(params)
# Validate parameters
self._validate_parameters(indicator, final_params)
# Prepare price arrays
arrays = self._prepare_price_arrays(price_data, definition["input_types"])
arrays = self._prepare_price_arrays(
price_data, cast("list[InputSpec]", definition["input_types"])
)
# Get TA-Lib function
talib_func_name = definition["talib_function"].split(".")[
talib_func_name = str(definition["talib_function"]).split(".")[
-1
] # Extract function name
talib_func = getattr(talib, talib_func_name)
@ -406,7 +418,7 @@ class MarketDataService:
func_kwargs = {}
# Add required price arrays based on input types
for input_type in definition["input_types"]:
for input_type in list(definition["input_types"]):
if input_type == "close":
func_args.append(arrays["close"])
elif input_type == "ohlc":
@ -433,7 +445,7 @@ class MarketDataService:
# Process results based on output format
result = []
dates = arrays["dates"]
output_format = definition["output_format"]
output_format = str(definition["output_format"])
if output_format == "single":
# Single output array
@ -576,7 +588,8 @@ class MarketDataService:
def get_available_indicators(self) -> dict[str, str]:
"""Get list of all available indicators with descriptions."""
return {
name: info["description"] for name, info in INDICATOR_DEFINITIONS.items()
name: str(info["description"])
for name, info in INDICATOR_DEFINITIONS.items()
}
def get_available_presets(
@ -612,13 +625,17 @@ class MarketDataService:
definition = INDICATOR_DEFINITIONS[indicator_upper]
return IndicatorConfig(
name=indicator_upper,
parameters=definition["default_params"],
input_types=definition["input_types"],
output_format=definition["output_format"],
param_ranges=definition["param_ranges"],
default_params=definition["default_params"],
talib_function=definition["talib_function"],
description=definition["description"],
parameters=cast(
"dict[str, IndicatorParamValue]", definition["default_params"]
),
input_types=cast("list[InputSpec]", definition["input_types"]),
output_format=cast("OutputSpec", definition["output_format"]),
param_ranges=cast("ParamRanges", definition["param_ranges"]),
default_params=cast(
"dict[str, IndicatorParamValue]", definition["default_params"]
),
talib_function=str(definition["talib_function"]),
description=str(definition["description"]),
)
def _calculate_signal_strength(

2
tradingagents/domains/news/article_scraper_client.py
View File

@ -25,7 +25,7 @@ class ScrapeResult:
title: str = ""
publish_date: str = ""
is_paywall: bool = False
keywords: list[str] = None # Extracted keywords from newspaper4k
keywords: list[str] | None = None # Extracted keywords from newspaper4k
summary: str = "" # Article summary from newspaper4k

20
tradingagents/domains/news/google_news_client.py
View File

@ -4,7 +4,7 @@ Google News client for live news data via RSS feeds.
import logging
from dataclasses import dataclass
from datetime import datetime
from datetime import datetime, timezone
from urllib.parse import quote
import feedparser
@ -168,11 +168,19 @@ class GoogleNewsClient:
# Parse published date with fallback to current time
try:
published = (
date_parser.parse(published_str) if published_str else datetime.utcnow()
)
if published_str:
parsed_result = date_parser.parse(published_str)
# dateutil.parser.parse() always returns datetime unless fuzzy_with_tokens=True
# Since we're not using fuzzy_with_tokens, we know it's a datetime
if isinstance(parsed_result, datetime):
published = parsed_result
else:
# Fallback for any unexpected types (shouldn't happen)
published = datetime.now(timezone.utc).replace(tzinfo=None)
else:
published = datetime.now(timezone.utc).replace(tzinfo=None)
except (ValueError, OverflowError, TypeError):
published = datetime.utcnow()
published = datetime.now(timezone.utc).replace(tzinfo=None)
# Extract source from title (Google News format: "Title - Source")
title_parts = raw_title.split(" - ")
@ -181,7 +189,7 @@ class GoogleNewsClient:
return GoogleNewsArticle(
title=title,
link=link,
link=str(link) if link else "",
published=published,
summary=summary,
source=source,

7
tradingagents/domains/news/news_service.py
View File

@ -639,7 +639,7 @@ class NewsService:
return []
# Simple keyword extraction from titles
word_counts = {}
word_counts: dict[str, int] = {}
stop_words = {
"the",
"a",
@ -680,7 +680,10 @@ class NewsService:
# Clean word
word = "".join(c for c in word if c.isalnum())
if len(word) > 3 and word not in stop_words:
word_counts[word] = word_counts.get(word, 0) + 1
if word in word_counts:
word_counts[word] += 1
else:
word_counts[word] = 1
# Get top trending words
trending = sorted(word_counts.items(), key=lambda x: x[1], reverse=True)[:5]

2
tradingagents/graph/__init__.py
View File

@ -1,9 +1,9 @@
# TradingAgents/graph/__init__.py
from .conditional_logic import ConditionalLogic
from .graph_setup import GraphSetup
from .propagation import Propagator
from .reflection import Reflector
from .setup import GraphSetup
from .signal_processing import SignalProcessor
from .trading_graph import TradingAgentsGraph

0
tradingagents/graph/setup.py → tradingagents/graph/graph_setup.py
View File

36
tradingagents/graph/propagation.py
View File

@ -24,28 +24,24 @@ class Propagator:
"company_of_interest": company_name,
"trade_date": str(trade_date),
"investment_debate_state": InvestDebateState(
{
"bull_history": "",
"bear_history": "",
"history": "",
"current_response": "",
"judge_decision": "",
"count": 0,
}
bull_history="",
bear_history="",
history="",
current_response="",
judge_decision="",
count=0,
),
"risk_debate_state": RiskDebateState(
{
"risky_history": "",
"safe_history": "",
"neutral_history": "",
"history": "",
"latest_speaker": "",
"current_risky_response": "",
"current_safe_response": "",
"current_neutral_response": "",
"judge_decision": "",
"count": 0,
}
risky_history="",
safe_history="",
neutral_history="",
history="",
latest_speaker="",
current_risky_response="",
current_safe_response="",
current_neutral_response="",
judge_decision="",
count=0,
),
"market_report": "",
"fundamentals_report": "",

9
tradingagents/graph/trading_graph.py
View File

@ -3,6 +3,7 @@
import json
import os
from pathlib import Path
from typing import Any
from langchain_anthropic import ChatAnthropic
from langchain_google_genai import ChatGoogleGenerativeAI
@ -21,15 +22,20 @@ from tradingagents.domains.news.news_service import NewsService
from tradingagents.domains.socialmedia.social_media_service import SocialMediaService
from .conditional_logic import ConditionalLogic
from .graph_setup import GraphSetup
from .propagation import Propagator
from .reflection import Reflector
from .setup import GraphSetup
from .signal_processing import SignalProcessor
class TradingAgentsGraph:
"""Main class that orchestrates the trading agents framework."""
# Type annotations for LLM attributes
deep_thinking_llm: ChatOpenAI | ChatAnthropic | ChatGoogleGenerativeAI
quick_thinking_llm: ChatOpenAI | ChatAnthropic | ChatGoogleGenerativeAI
curr_state: dict[str, Any] | None
def __init__(
self,
selected_analysts=None,
@ -48,6 +54,7 @@ class TradingAgentsGraph:
self.debug = debug
self.config = config or TradingAgentsConfig()
self.curr_state = None
# Create necessary directories
os.makedirs(

18
uv.lock
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@ -2908,6 +2908,22 @@ wheels = [
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]
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[[package]]
name = "pyright"
version = "1.1.403"
@ -3649,6 +3665,7 @@ dev = [
[package.dev-dependencies]
dev = [
{ name = "pyrefly" },
{ name = "pytest" },
{ name = "pytest-asyncio" },
{ name = "pytest-cov" },
@ -3700,6 +3717,7 @@ provides-extras = ["dev"]
[package.metadata.requires-dev]
dev = [
{ name = "pyrefly", specifier = ">=0.28.1" },
{ name = "pytest", specifier = ">=8.4.1" },
{ name = "pytest-asyncio", specifier = ">=1.1.0" },
{ name = "pytest-cov", specifier = ">=6.2.1" },