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[CLEANUP][Models]

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Your Name 4 months ago
parent 06488efc53
commit 46726f9974
17 changed files with 50 additions and 25 deletions
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6
README.md
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@ -131,7 +131,8 @@ import os
from swarms_memory import ChromaDB 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 ( from swarms.prompts.finance_agent_sys_prompt import (
FINANCIAL_AGENT_SYS_PROMPT, FINANCIAL_AGENT_SYS_PROMPT,
) )
@ -369,7 +370,8 @@ The following is an example of an agent that intakes a pydantic basemodel and ou
```python ```python
from pydantic import BaseModel, Field 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 # Initialize the schema for the person's information

3
agent_with_rag.py
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@ -2,7 +2,8 @@ import os
from swarms_memory import ChromaDB 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 ( from swarms.prompts.finance_agent_sys_prompt import (
FINANCIAL_AGENT_SYS_PROMPT, FINANCIAL_AGENT_SYS_PROMPT,
) )

9
docs/swarms/memory/diy_memory.md
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@ -455,7 +455,8 @@ Now, how do you integrate a vector datbase with an agent? This is how:
```python ```python
from typing import List, Dict, Any from typing import List, Dict, Any
from swarms_memory import PineconeMemory from swarms_memory import PineconeMemory
from swarms import Agent, Anthropic from swarms import Agent
from swarm_models import Anthropic
from transformers import AutoTokenizer, AutoModel from transformers import AutoTokenizer, AutoModel
import torch import torch
import os import os
@ -508,7 +509,8 @@ ChromaDB is a simple, high-performance vector store for use with embeddings. Her
```python ```python
from swarms_memory import ChromaDB from swarms_memory import ChromaDB
from swarms import Agent, Anthropic from swarms import Agent
from swarm_models import Anthropic
import os import os
# Initialize the ChromaDB client # Initialize the ChromaDB client
@ -540,7 +542,8 @@ Faiss is a library for efficient similarity search and clustering of dense vecto
```python ```python
from typing import List, Dict, Any from typing import List, Dict, Any
from swarms_memory.faiss_wrapper import FAISSDB 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 from transformers import AutoTokenizer, AutoModel
import torch import torch
import os import os

3
docs/swarms/structs/agent.md
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@ -319,7 +319,8 @@ import os
from swarms_memory import ChromaDB 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 ( from swarms.prompts.finance_agent_sys_prompt import (
FINANCIAL_AGENT_SYS_PROMPT, FINANCIAL_AGENT_SYS_PROMPT,
) )

6
docs/swarms/structs/index.md
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@ -157,7 +157,8 @@ Implementation of Devin in less than 90 lines of code with several tools:
terminal, browser, and edit files. terminal, browser, and edit files.
```python ```python
from swarms import Agent, Anthropic from swarms import Agent
from swarm_models import Anthropic
import subprocess import subprocess
# Model # Model
@ -263,7 +264,8 @@ The following is an example of an agent that intakes a pydantic basemodel and ou
```python ```python
from pydantic import BaseModel, Field 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 # Initialize the schema for the person's information

3
examples/agents/memory/agents_and_memory/finance_agent_with_memory
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@ -2,7 +2,8 @@ import os
from swarms_memory import ChromaDB 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 ( from swarms.prompts.finance_agent_sys_prompt import (
FINANCIAL_AGENT_SYS_PROMPT, FINANCIAL_AGENT_SYS_PROMPT,
) )

3
examples/agents/tools/devin.py
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@ -1,4 +1,5 @@
from swarms import Agent, Anthropic, tool from swarms import Agent
from swarm_models import Anthropic, tool
import subprocess import subprocess
# Model # Model

3
examples/agents/tools/full_stack_agent.py
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@ -1,4 +1,5 @@
from swarms import Agent, Anthropic, tool from swarms import Agent
from swarm_models import Anthropic, tool
# Tool # Tool

3
examples/agents/tools/tool.py
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@ -1,4 +1,5 @@
from swarms import Agent, Anthropic, tool from swarms import Agent
from swarm_models import Anthropic, tool
# Model # Model
llm = Anthropic( llm = Anthropic(

3
examples/agents/use_cases/finance/first_agent_example.py
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@ -1,5 +1,6 @@
import os import os
from swarms import Agent, Anthropic from swarms import Agent
from swarm_models import Anthropic
from swarms.prompts.finance_agent_sys_prompt import ( from swarms.prompts.finance_agent_sys_prompt import (
FINANCIAL_AGENT_SYS_PROMPT, FINANCIAL_AGENT_SYS_PROMPT,
) )

12
examples/collabs/swarms_example.ipynb
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@ -201,7 +201,8 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"from swarms import Agent, Anthropic\n", "from swarms import Agent
from swarm_models import Anthropic\n",
"\n", "\n",
"\n", "\n",
"## Initialize the workflow\n", "## Initialize the workflow\n",
@ -240,7 +241,8 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"from swarms import Agent, Anthropic, tool\n", "from swarms import Agent
from swarm_models import Anthropic, tool\n",
"import subprocess\n", "import subprocess\n",
"\n", "\n",
"# Model\n", "# Model\n",
@ -361,7 +363,8 @@
"outputs": [], "outputs": [],
"source": [ "source": [
"from pydantic import BaseModel, Field\n", "from pydantic import BaseModel, Field\n",
"from swarms import Anthropic, Agent\n", "from swarms import Agent
from swarm_models import Anthropic\n",
"\n", "\n",
"\n", "\n",
"# Initialize the schema for the person's information\n", "# Initialize the schema for the person's information\n",
@ -1388,7 +1391,8 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"from swarms import Agent, Anthropic, AgentRearrange \n", "from swarms import Agent
from swarm_models import Anthropic, AgentRearrange \n",
"\n", "\n",
"## Initialize the workflow\n", "## Initialize the workflow\n",
"agent = Agent(\n", "agent = Agent(\n",

3
examples/demos/evelyn_swarmathon_submission/Swarmshackathon2024.ipynb
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@ -505,7 +505,8 @@
} }
], ],
"source": [ "source": [
"from swarms import Agent, Anthropic\n", "from swarms import Agent
from swarm_models import Anthropic\n",
"import subprocess\n", "import subprocess\n",
"\n", "\n",
"# Model\n", "# Model\n",

3
examples/demos/fintech/main.py
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@ -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 # Define the agents with specific tasks for financial activities
agent_risk_analysis = Agent( agent_risk_analysis = Agent(

3
examples/structs/swarms/multi_agent_collab/multi_agent_collab_demo.py
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@ -1,6 +1,7 @@
import os 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 ( from swarms.prompts.finance_agent_sys_prompt import (
FINANCIAL_AGENT_SYS_PROMPT, FINANCIAL_AGENT_SYS_PROMPT,
) )

3
examples/structs/swarms/multi_agent_collaboration/round_robin_example.py
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@ -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 from swarms.structs.round_robin import RoundRobinSwarm
# Initialize the director agent # Initialize the director agent

3
examples/structs/swarms/multi_agent_collaboration/society_of_agents.py
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@ -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 from swarms.structs.society_of_agents import SocietyOfAgents
# Initialize the director agent # Initialize the director agent

6
examples/structs/swarms/spreadsheet_swarm/spreadsheet_swarm_examples/csvs/README.md
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@ -131,7 +131,8 @@ import os
from swarms_memory import ChromaDB 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 ( from swarms.prompts.finance_agent_sys_prompt import (
FINANCIAL_AGENT_SYS_PROMPT, FINANCIAL_AGENT_SYS_PROMPT,
) )
@ -369,7 +370,8 @@ The following is an example of an agent that intakes a pydantic basemodel and ou
```python ```python
from pydantic import BaseModel, Field 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 # Initialize the schema for the person's information

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