chore: update to use free models

Signed-off-by: bjorn <bjornjee95@gmail.com>

cli/utils.py

@@ -131,6 +131,7 @@ def select_shallow_thinking_agent() -> str:
         ("GPT-4.1-nano - Ultra-lightweight model for basic operations", "gpt-4.1-nano"),
         ("GPT-4.1-mini - Compact model with good performance", "gpt-4.1-mini"),
         ("GPT-4o - Standard model with solid capabilities", "gpt-4o"),
+        ("Deepseek R1","deepseek/deepseek-chat-v3-0324:free"),
     ]
 
     choice = questionary.select(
@@ -170,6 +171,7 @@ def select_deep_thinking_agent() -> str:
         ("o3-mini - Advanced reasoning model (lightweight)", "o3-mini"),
         ("o3 - Full advanced reasoning model", "o3"),
         ("o1 - Premier reasoning and problem-solving model", "o1"),
+        ("Deepseek R1","deepseek/deepseek-chat-v3-0324:free"),
     ]
 
     choice = questionary.select(

requirements.txt

@@ -22,3 +22,4 @@ redis
 chainlit
 rich
 questionary
+sentence-transformers

tradingagents/agents/utils/memory.py

@@ -2,21 +2,23 @@ import chromadb
 from chromadb.config import Settings
 from openai import OpenAI
 import numpy as np
+from sentence_transformers import SentenceTransformer
 
 
 class FinancialSituationMemory:
     def __init__(self, name):
-        self.client = OpenAI()
+        self.embedding_model = SentenceTransformer("all-MiniLM-L6-v2")
         self.chroma_client = chromadb.Client(Settings(allow_reset=True))
         self.situation_collection = self.chroma_client.create_collection(name=name)
 
     def get_embedding(self, text):
         """Get OpenAI embedding for a text"""
-        response = self.client.embeddings.create(
+        # response = self.client.embeddings.create(
-            model="text-embedding-ada-002", input=text
+        #     model="text-embedding-ada-002", input=text
-        )
+        # )
-        return response.data[0].embedding
+        # return response.data[0].embedding
-
+        return self.embedding_model.encode(text, convert_to_tensor=False)
+        
     def add_situations(self, situations_and_advice):
         """Add financial situations and their corresponding advice. Parameter is a list of tuples (situation, rec)"""
 

tradingagents/default_config.py

@@ -8,8 +8,9 @@ DEFAULT_CONFIG = {
         "dataflows/data_cache",
     ),
     # LLM settings
-    "deep_think_llm": "o4-mini",
+    "base_url": "https://openrouter.ai/api/v1",
-    "quick_think_llm": "gpt-4o-mini",
+    "deep_think_llm": "deepseek/deepseek-r1:free",
+    "quick_think_llm": "deepseek/deepseek-r1:free",
     # Debate and discussion settings
     "max_debate_rounds": 1,
     "max_risk_discuss_rounds": 1,

tradingagents/graph/trading_graph.py

@@ -55,8 +55,9 @@ class TradingAgentsGraph:
         )
 
         # Initialize LLMs
-        self.deep_thinking_llm = ChatOpenAI(model=self.config["deep_think_llm"])
+        self.deep_thinking_llm = ChatOpenAI(base_url=self.config['base_url'],model=self.config["deep_think_llm"])
         self.quick_thinking_llm = ChatOpenAI(
+            base_url=self.config['base_url'],
             model=self.config["quick_think_llm"], temperature=0.1
         )
         self.toolkit = Toolkit(config=self.config)