[CLEANUP][Models]

README.md

@@ -131,7 +131,8 @@ import os
 
 from swarms_memory import ChromaDB
 
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 from swarms.prompts.finance_agent_sys_prompt import (
     FINANCIAL_AGENT_SYS_PROMPT,
 )
@@ -369,7 +370,8 @@ The following is an example of an agent that intakes a pydantic basemodel and ou
 
 ```python
 from pydantic import BaseModel, Field
-from swarms import Anthropic, Agent
+from swarms import Agent
+from swarm_models import Anthropic
 
 
 # Initialize the schema for the person's information

agent_with_rag.py

@@ -2,7 +2,8 @@ import os
 
 from swarms_memory import ChromaDB
 
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 from swarms.prompts.finance_agent_sys_prompt import (
     FINANCIAL_AGENT_SYS_PROMPT,
 )

docs/swarms/memory/diy_memory.md

@@ -455,7 +455,8 @@ Now, how do you integrate a vector datbase with an agent? This is how:
 ```python
 from typing import List, Dict, Any
 from swarms_memory import PineconeMemory
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 from transformers import AutoTokenizer, AutoModel
 import torch
 import os
@@ -508,7 +509,8 @@ ChromaDB is a simple, high-performance vector store for use with embeddings. Her
 
 ```python
 from swarms_memory import ChromaDB
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 import os
 
 # Initialize the ChromaDB client
@@ -540,7 +542,8 @@ Faiss is a library for efficient similarity search and clustering of dense vecto
 ```python
 from typing import List, Dict, Any
 from swarms_memory.faiss_wrapper import FAISSDB
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 from transformers import AutoTokenizer, AutoModel
 import torch
 import os

docs/swarms/structs/agent.md

@@ -319,7 +319,8 @@ import os
 
 from swarms_memory import ChromaDB
 
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 from swarms.prompts.finance_agent_sys_prompt import (
     FINANCIAL_AGENT_SYS_PROMPT,
 )

docs/swarms/structs/index.md

@@ -157,7 +157,8 @@ Implementation of Devin in less than 90 lines of code with several tools:
 terminal, browser, and edit files.
 
 ```python
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 import subprocess
 
 # Model
@@ -263,7 +264,8 @@ The following is an example of an agent that intakes a pydantic basemodel and ou
 
 ```python
 from pydantic import BaseModel, Field
-from swarms import Anthropic, Agent
+from swarms import Agent
+from swarm_models import Anthropic
 
 
 # Initialize the schema for the person's information

examples/agents/memory/agents_and_memory/finance_agent_with_memory

@@ -2,7 +2,8 @@ import os
 
 from swarms_memory import ChromaDB
 
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 from swarms.prompts.finance_agent_sys_prompt import (
     FINANCIAL_AGENT_SYS_PROMPT,
 )

examples/agents/tools/devin.py

@@ -1,4 +1,5 @@
-from swarms import Agent, Anthropic, tool
+from swarms import Agent
+from swarm_models import Anthropic, tool
 import subprocess
 
 # Model

examples/agents/tools/full_stack_agent.py

@@ -1,4 +1,5 @@
-from swarms import Agent, Anthropic, tool
+from swarms import Agent
+from swarm_models import Anthropic, tool
 
 
 # Tool

examples/agents/tools/tool.py

@@ -1,4 +1,5 @@
-from swarms import Agent, Anthropic, tool
+from swarms import Agent
+from swarm_models import Anthropic, tool
 
 # Model
 llm = Anthropic(

examples/agents/use_cases/finance/first_agent_example.py

@@ -1,5 +1,6 @@
 import os
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 from swarms.prompts.finance_agent_sys_prompt import (
     FINANCIAL_AGENT_SYS_PROMPT,
 )

examples/collabs/swarms_example.ipynb

@@ -201,7 +201,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from swarms import Agent, Anthropic\n",
+    "from swarms import Agent
+from swarm_models import Anthropic\n",
     "\n",
     "\n",
     "## Initialize the workflow\n",
@@ -240,7 +241,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from swarms import Agent, Anthropic, tool\n",
+    "from swarms import Agent
+from swarm_models import Anthropic, tool\n",
     "import subprocess\n",
     "\n",
     "# Model\n",
@@ -361,7 +363,8 @@
    "outputs": [],
    "source": [
     "from pydantic import BaseModel, Field\n",
-    "from swarms import Anthropic, Agent\n",
+    "from swarms import Agent
+from swarm_models import Anthropic\n",
     "\n",
     "\n",
     "# Initialize the schema for the person's information\n",
@@ -1388,7 +1391,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from swarms import Agent, Anthropic, AgentRearrange \n",
+    "from swarms import Agent
+from swarm_models import Anthropic, AgentRearrange \n",
     "\n",
     "## Initialize the workflow\n",
     "agent = Agent(\n",

examples/demos/evelyn_swarmathon_submission/Swarmshackathon2024.ipynb

@@ -505,7 +505,8 @@
     }
    ],
    "source": [
-    "from swarms import Agent, Anthropic\n",
+    "from swarms import Agent
+from swarm_models import Anthropic\n",
     "import subprocess\n",
     "\n",
     "# Model\n",

examples/demos/fintech/main.py

@@ -1,4 +1,5 @@
-from swarms import Agent, Anthropic, AgentRearrange
+from swarms import Agent
+from swarm_models import Anthropic, AgentRearrange
 
 # Define the agents with specific tasks for financial activities
 agent_risk_analysis = Agent(

examples/structs/swarms/multi_agent_collab/multi_agent_collab_demo.py

@@ -1,6 +1,7 @@
 import os
 
-from swarms import Agent, Anthropic, MultiAgentCollaboration
+from swarms import Agent
+from swarm_models import Anthropic, MultiAgentCollaboration
 from swarms.prompts.finance_agent_sys_prompt import (
     FINANCIAL_AGENT_SYS_PROMPT,
 )

examples/structs/swarms/multi_agent_collaboration/round_robin_example.py

@@ -1,4 +1,5 @@
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 from swarms.structs.round_robin import RoundRobinSwarm
 
 # Initialize the director agent

examples/structs/swarms/multi_agent_collaboration/society_of_agents.py

@@ -1,4 +1,5 @@
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 from swarms.structs.society_of_agents import SocietyOfAgents
 
 # Initialize the director agent

examples/structs/swarms/spreadsheet_swarm/spreadsheet_swarm_examples/csvs/README.md

@@ -131,7 +131,8 @@ import os
 
 from swarms_memory import ChromaDB
 
-from swarms import Agent, Anthropic
+from swarms import Agent
+from swarm_models import Anthropic
 from swarms.prompts.finance_agent_sys_prompt import (
     FINANCIAL_AGENT_SYS_PROMPT,
 )
@@ -369,7 +370,8 @@ The following is an example of an agent that intakes a pydantic basemodel and ou
 
 ```python
 from pydantic import BaseModel, Field
-from swarms import Anthropic, Agent
+from swarms import Agent
+from swarm_models import Anthropic
 
 
 # Initialize the schema for the person's information