bug fixes, module error swarm. instead of swarms.

Former-commit-id: dbcab9a06b

README.md

@@ -45,14 +45,18 @@ from swarms.workers import Worker
 from swarms.swarms import MultiAgentDebate, select_speaker
 from swarms.models import OpenAIChat
 
+
+api_key = "sk-"
+
 llm = OpenAIChat(
     model_name='gpt-4', 
-    openai_api_key="api-key", 
+    openai_api_key=api_key, 
     temperature=0.5
 )
 
 node = Worker(
     llm=llm,
+    openai_api_key=api_key,
     ai_name="Optimus Prime",
     ai_role="Worker in a swarm",
     external_tools = None,
@@ -62,6 +66,7 @@ node = Worker(
 
 node2 = Worker(
     llm=llm,
+    openai_api_key=api_key,
     ai_name="Bumble Bee",
     ai_role="Worker in a swarm",
     external_tools = None,
@@ -71,6 +76,7 @@ node2 = Worker(
 
 node3 = Worker(
     llm=llm,
+    openai_api_key=api_key,
     ai_name="Bumble Bee",
     ai_role="Worker in a swarm",
     external_tools = None,
@@ -104,30 +110,31 @@ for result in results:
 - And, then place the openai api key in the Worker for the openai embedding model
 
 ```python
-from swarms.models import ChatOpenAI
-from swarms.workers import Worker
+from swarms.models import OpenAIChat
+from swarms import Worker
 
-llm = ChatOpenAI(
-    model_name='gpt-4', 
-    openai_api_key="api-key", 
-    temperature=0.5
+api_key = ""
+
+llm = OpenAIChat(
+    openai_api_key=api_key,
+    temperature=0.5,
 )
 
 node = Worker(
     llm=llm,
     ai_name="Optimus Prime",
-    #openai key for the embeddings
-    openai_api_key="sk-eee"
+    openai_api_key=api_key,
     ai_role="Worker in a swarm",
-    external_tools = None,
-    human_in_the_loop = False,
-    temperature = 0.5,
+    external_tools=None,
+    human_in_the_loop=False,
+    temperature=0.5,
 )
 
 task = "What were the winning boston marathon times for the past 5 years (ending in 2022)? Generate a table of the year, name, country of origin, and times."
 response = node.run(task)
 print(response)
 
+
 ```
 
 ------
@@ -139,8 +146,9 @@ print(response)
 from swarms.models import OpenAIChat
 from swarms.agents import OmniModalAgent
 
+api_key = "SK-"
 
-llm = OpenAIChat(model_name="gpt-4")
+llm = OpenAIChat(model_name="gpt-4", openai_api_key=api_key)
 
 agent = OmniModalAgent(llm)
 

example.py

@@ -1,15 +1,17 @@
 from swarms.models import OpenAIChat
 from swarms import Worker
 
+api_key = ""
+
 llm = OpenAIChat(
-    openai_api_key="Enter in your key",
+    openai_api_key=api_key,
     temperature=0.5,
 )
 
 node = Worker(
     llm=llm,
     ai_name="Optimus Prime",
-    openai_api_key="entter in your key",
+    openai_api_key=api_key,
     ai_role="Worker in a swarm",
     external_tools=None,
     human_in_the_loop=False,

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "swarms"
-version = "1.8.2"
+version = "1.9.1"
 description = "Swarms - Pytorch"
 license = "MIT"
 authors = ["Kye Gomez <kye@apac.ai>"]
@@ -38,6 +38,7 @@ duckduckgo-search = "*"
 faiss-cpu = "*"
 diffusers = "*"
 wget = "*"
+griptape = "*"
 httpx = "*"
 ggl = "*"
 beautifulsoup4 = "*"

requirements.txt

@@ -25,7 +25,7 @@ chromadb
 open-interpreter
 tabulate 
 colored
-
+griptape
 addict
 albumentations
 basicsr

swarms/__init__.py

@@ -12,11 +12,10 @@ os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
 
 from swarms import workers
 from swarms.workers.worker import Worker
-from swarms.chunkers import chunkers
+# from swarms import chunkers
 from swarms import models
 from swarms import structs
 from swarms import swarms
-from swarms.swarms.orchestrate import Orchestrator
 from swarms import agents
 from swarms.logo import logo
 print(logo)

swarms/chunkers/base.py

@@ -3,7 +3,7 @@ from abc import ABC
 from typing import Optional
 from attr import define, field, Factory
 from griptape.artifacts import TextArtifact
-from swarm.chunkers.chunk_seperators import ChunkSeparator
+from swarms.chunkers.chunk_seperators import ChunkSeparator
 from griptape.tokenizers import OpenAiTokenizer
 
 

swarms/chunkers/markdown.py

@@ -1,5 +1,5 @@
 from swarms.chunkers.base import BaseChunker
-from swarms.chunk_seperator import ChunkSeparator
+from swarms.chunkers.chunk_seperator import ChunkSeparator
 
 
 class MarkdownChunker(BaseChunker):

swarms/hivemind/hivemind.py

@@ -7,8 +7,11 @@
 import concurrent.futures
 import logging
 
+import faiss
 
+from swarms.embeddings.openai import OpenAIEmbeddings
 from swarms.swarms.swarms import HierarchicalSwarm
+from swarms.vectorstore.vectorstore import FAISS, InMemoryDocstore
 
 logging.basicConfig(
     level=logging.DEBUG, format="%(asctime)s - %(levelname)s - %(message)s"

swarms/models/__init__.py

@@ -9,4 +9,5 @@ from swarms.models.zephyr import Zephyr
 # MultiModal Models
 from swarms.models.idefics import Idefics
 from swarms.models.kosmos_two import Kosmos
-from swarms.models.vilt import Vilt
+from swarms.models.vilt import Vilt
+# from swarms.models.fuyu import Fuyu

swarms/models/anthropic.py

@@ -3,7 +3,15 @@ import os
 
 
 class Anthropic:
-    """Anthropic large language models."""
+    """
+    
+    Anthropic large language models.
+    
+    
+    Args:
+    
+    
+    """
 
     def __init__(
         self,
@@ -41,12 +49,12 @@ class Anthropic:
             d["top_p"] = self.top_p
         return d
 
-    def generate(self, prompt, stop=None):
+    def run(self, task: str, stop=None):
         """Call out to Anthropic's completion endpoint."""
         stop = stop or []
         params = self._default_params()
         headers = {"Authorization": f"Bearer {self.anthropic_api_key}"}
-        data = {"prompt": prompt, "stop_sequences": stop, **params}
+        data = {"prompt": task, "stop_sequences": stop, **params}
         response = requests.post(
             f"{self.anthropic_api_url}/completions",
             headers=headers,
@@ -55,12 +63,12 @@ class Anthropic:
         )
         return response.json().get("completion")
 
-    def __call__(self, prompt, stop=None):
+    def __call__(self, task: str, stop=None):
         """Call out to Anthropic's completion endpoint."""
         stop = stop or []
         params = self._default_params()
         headers = {"Authorization": f"Bearer {self.anthropic_api_key}"}
-        data = {"prompt": prompt, "stop_sequences": stop, **params}
+        data = {"prompt": task, "stop_sequences": stop, **params}
         response = requests.post(
             f"{self.anthropic_api_url}/completions",
             headers=headers,

swarms/workers/worker.py

@@ -1,21 +1,22 @@
-import random
 import os
+import random
 from typing import Dict, Union
 
 import faiss
+from langchain.chains.qa_with_sources.loading import (
+    load_qa_with_sources_chain,
+)
 from langchain.docstore import InMemoryDocstore
 from langchain.embeddings import OpenAIEmbeddings
+from langchain.tools import ReadFileTool, WriteFileTool
 from langchain.tools.human.tool import HumanInputRun
 from langchain.vectorstores import FAISS
 from langchain_experimental.autonomous_agents import AutoGPT
 
 from swarms.agents.message import Message
 from swarms.tools.autogpt import (
-    ReadFileTool,
     WebpageQATool,
-    WriteFileTool,
     # compile,
-    load_qa_with_sources_chain,
     process_csv,
 )
 from swarms.utils.decorators import error_decorator, timing_decorator