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main works, cli bugs

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This commit is contained in:
Edward Sun
2025-06-15 22:20:59 -07:00
parent 90b23e72f5
commit da84ef43aa
11 changed files with 5577 additions and 50 deletions
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55
cli/main.py
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@@ -295,10 +295,27 @@ def update_display(layout, spinner_text=None):
# Add regular messages
for timestamp, msg_type, content in message_buffer.messages:
# Convert content to string if it's not already
content_str = content
if isinstance(content, list):
# Handle list of content blocks (Anthropic format)
text_parts = []
for item in content:
if isinstance(item, dict):
if item.get('type') == 'text':
text_parts.append(item.get('text', ''))
elif item.get('type') == 'tool_use':
text_parts.append(f"[Tool: {item.get('name', 'unknown')}]")
else:
text_parts.append(str(item))
content_str = ' '.join(text_parts)
elif not isinstance(content_str, str):
content_str = str(content)
# Truncate message content if too long
if isinstance(content, str) and len(content) > 200:
content = content[:197] + "..."
all_messages.append((timestamp, msg_type, content))
if len(content_str) > 200:
content_str = content_str[:197] + "..."
all_messages.append((timestamp, msg_type, content_str))
# Sort by timestamp
all_messages.sort(key=lambda x: x[0])
@@ -450,7 +467,7 @@ def get_user_selections():
"Step 5: OpenAI backend", "Select which service to talk to"
)
)
selected_openai_backend = select_openai_backend()
selected_llm_provider, backend_url = select_llm_provider()
# Step 6: Thinking agents
console.print(
@@ -458,15 +475,16 @@ def get_user_selections():
"Step 6: Thinking Agents", "Select your thinking agents for analysis"
)
)
selected_shallow_thinker = select_shallow_thinking_agent(selected_openai_backend)
selected_deep_thinker = select_deep_thinking_agent(selected_openai_backend)
selected_shallow_thinker = select_shallow_thinking_agent(selected_llm_provider)
selected_deep_thinker = select_deep_thinking_agent(selected_llm_provider)
return {
"ticker": selected_ticker,
"analysis_date": analysis_date,
"analysts": selected_analysts,
"research_depth": selected_research_depth,
"openai_backend": selected_openai_backend,
"llm_provider": selected_llm_provider.lower(),
"backend_url": backend_url,
"shallow_thinker": selected_shallow_thinker,
"deep_thinker": selected_deep_thinker,
}
@@ -692,6 +710,24 @@ def update_research_team_status(status):
for agent in research_team:
message_buffer.update_agent_status(agent, status)
def extract_content_string(content):
"""Extract string content from various message formats."""
if isinstance(content, str):
return content
elif isinstance(content, list):
# Handle Anthropic's list format
text_parts = []
for item in content:
if isinstance(item, dict):
if item.get('type') == 'text':
text_parts.append(item.get('text', ''))
elif item.get('type') == 'tool_use':
text_parts.append(f"[Tool: {item.get('name', 'unknown')}]")
else:
text_parts.append(str(item))
return ' '.join(text_parts)
else:
return str(content)
def run_analysis():
# First get all user selections
@@ -703,7 +739,8 @@ def run_analysis():
config["max_risk_discuss_rounds"] = selections["research_depth"]
config["quick_think_llm"] = selections["shallow_thinker"]
config["deep_think_llm"] = selections["deep_thinker"]
config["openai_backend"] = selections["openai_backend"]
config["backend_url"] = selections["backend_url"]
config["llm_provider"] = selections["llm_provider"].lower()
# Initialize the graph
graph = TradingAgentsGraph(
@@ -764,7 +801,7 @@ def run_analysis():
# Extract message content and type
if hasattr(last_message, "content"):
content = last_message.content
content = extract_content_string(last_message.content) # Use the helper function
msg_type = "Reasoning"
else:
content = str(last_message)