chore: sync

.github/workflows/RELEASE.yml

@@ -23,7 +23,7 @@ jobs:
       - name: Install poetry
         run: pipx install poetry==$POETRY_VERSION
       - name: Set up Python 3.9
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: "3.9"
           cache: "poetry"

.github/workflows/docs.yml

@@ -11,7 +11,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: actions/setup-python@v4
+      - uses: actions/setup-python@v5
         with:
           python-version: 3.x
       - run: pip install mkdocs-material

.github/workflows/label.yml

@@ -17,6 +17,6 @@ jobs:
       pull-requests: write
 
     steps:
-    - uses: actions/labeler@v4
+    - uses: actions/labeler@v5
       with:
         repo-token: "${{ secrets.GITHUB_TOKEN }}"

.github/workflows/pr_request_checks.yml

@@ -15,7 +15,7 @@ jobs:
         uses: actions/checkout@v4
 
       - name: Set up Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: 3.x
 

.github/workflows/pylint.yml

@@ -9,9 +9,9 @@ jobs:
       matrix:
         python-version: ["3.8", "3.9", "3.10"]
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies

.github/workflows/python-app.yml

@@ -18,9 +18,9 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python 3.10
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v5
       with:
         python-version: "3.10"
     - name: Install dependencies

.github/workflows/python-package-conda.yml

@@ -9,9 +9,9 @@ jobs:
       max-parallel: 5
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python 3.10
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v5
       with:
         python-version: '3.10'
     - name: Add conda to system path

.github/workflows/python-package.yml

@@ -21,7 +21,7 @@ jobs:
     steps:
     - uses: actions/checkout@v4
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies

.github/workflows/python-publish.yml

@@ -16,7 +16,7 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: '3.x'
       - name: Install dependencies

.github/workflows/stale.yml

@@ -18,7 +18,7 @@ jobs:
       pull-requests: write
 
     steps:
-    - uses: actions/stale@v8
+    - uses: actions/stale@v9
       with:
         repo-token: ${{ secrets.GITHUB_TOKEN }}
         stale-issue-message: 'Stale issue message'

.github/workflows/testing.yml

@@ -14,7 +14,7 @@ jobs:
         uses: actions/checkout@v4
 
       - name: Set up Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: 3.x
 

.github/workflows/unit-test.yml

@@ -16,7 +16,7 @@ jobs:
     - uses: actions/checkout@v4
 
     - name: Setup Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.9'
 

LICENSE

@@ -186,7 +186,7 @@
       same "printed page" as the copyright notice for easier
       identification within third-party archives.
 
-   Copyright [yyyy] [name of copyright owner]
+   Copyright [2023] [Kye Gomez]
 
    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.

README.md

@@ -203,7 +203,117 @@ response = agent.run("Generate a video of a swarm of fish and then make an image
 print(response)
 ```
 
+---
+
+### Multi-Agent Swarm for Logistics
+- Swarms is a framework designed for real-world deployment here is a demo presenting a fully ready to use Swarm for a vast array of logistics tasks.
+- Swarms is designed to be modular and reliable for real-world deployments.
+- Swarms is the first framework that unleases multi-modal autonomous agents in the real world.
+
+```python
+from swarms.structs import Agent
+import os
+from dotenv import load_dotenv
+from swarms.models import GPT4VisionAPI
+from swarms.prompts.logistics import (
+    Health_Security_Agent_Prompt,
+    Quality_Control_Agent_Prompt,
+    Productivity_Agent_Prompt,
+    Safety_Agent_Prompt,
+    Security_Agent_Prompt,
+    Sustainability_Agent_Prompt,
+    Efficiency_Agent_Prompt,
+)
+
+# Load ENV
+load_dotenv()
+api_key = os.getenv("OPENAI_API_KEY")
 
+# GPT4VisionAPI 
+llm = GPT4VisionAPI(openai_api_key=api_key)
+
+# Image for analysis
+factory_image = "factory_image1.jpg"
+
+# Initialize agents with respective prompts
+health_security_agent = Agent(
+    llm=llm,
+    sop=Health_Security_Agent_Prompt,
+    max_loops=1,
+    multi_modal=True,
+)
+
+# Quality control agent
+quality_control_agent = Agent(
+    llm=llm,
+    sop=Quality_Control_Agent_Prompt,
+    max_loops=1,
+    multi_modal=True,
+)
+
+
+# Productivity Agent
+productivity_agent = Agent(
+    llm=llm,
+    sop=Productivity_Agent_Prompt,
+    max_loops=1,
+    multi_modal=True,
+)
+
+# Initiailize safety agent
+safety_agent = Agent(
+    llm=llm, sop=Safety_Agent_Prompt, max_loops=1, multi_modal=True
+)
+
+# Init the security agent
+security_agent = Agent(
+    llm=llm, sop=Security_Agent_Prompt, max_loops=1, multi_modal=True
+)
+
+
+# Initialize sustainability agent
+sustainability_agent = Agent(
+    llm=llm,
+    sop=Sustainability_Agent_Prompt,
+    max_loops=1,
+    multi_modal=True,
+)
+
+
+# Initialize efficincy agent
+efficiency_agent = Agent(
+    llm=llm,
+    sop=Efficiency_Agent_Prompt,
+    max_loops=1,
+    multi_modal=True,
+)
+
+# Run agents with respective tasks on the same image
+health_analysis = health_security_agent.run(
+    "Analyze the safety of this factory", factory_image
+)
+quality_analysis = quality_control_agent.run(
+    "Examine product quality in the factory", factory_image
+)
+productivity_analysis = productivity_agent.run(
+    "Evaluate factory productivity", factory_image
+)
+safety_analysis = safety_agent.run(
+    "Inspect the factory's adherence to safety standards",
+    factory_image,
+)
+security_analysis = security_agent.run(
+    "Assess the factory's security measures and systems",
+    factory_image,
+)
+sustainability_analysis = sustainability_agent.run(
+    "Examine the factory's sustainability practices", factory_image
+)
+efficiency_analysis = efficiency_agent.run(
+    "Analyze the efficiency of the factory's manufacturing process",
+    factory_image,
+)
+```
 ---
 
 # Features 🤖 
@@ -302,4 +412,4 @@ To see how to contribute, visit [Contribution guidelines](https://github.com/kye
 Book a discovery call with the Swarms team to learn how to optimize and scale your swarm! [Click here to book a time that works for you!](https://calendly.com/swarm-corp/30min?month=2023-11)
 
 # License
-MIT
+Apache License

docs/swarms/models/vllm.md

@@ -32,7 +32,7 @@ vLLM is designed to simplify the process of generating text using language model
 Before using vLLM, you need to install swarms. You can install vLLM using `pip`:
 
 ```bash
-pip install swarms
+pip install swarms vllm
 ```
 
 ### vLLM Class <a name="vllm-class"></a>

mkdocs.yml

@@ -96,6 +96,8 @@ nav:
       - LayoutLMDocumentQA: "swarms/models/layoutlm_document_qa.md"
       - DistilWhisperModel: "swarms/models/distilled_whisperx.md"
       - ElevenLabsText2SpeechTool: "swarms/models/elevenlabs.md"
+      - OpenAITTS: "swarms/models/openai_tts.md"
+      - Gemini: "swarms/models/gemini.md"
   - swarms.structs:
     - Overview: "swarms/structs/overview.md"
     - AutoScaler: "swarms/swarms/autoscaler.md"

playground/demos/multi_modal_chain_of_thought/vcot.py

@@ -0,0 +1,35 @@
+import os
+
+from dotenv import load_dotenv
+
+from swarms.models.gpt4_vision_api import GPT4VisionAPI
+from swarms.prompts.visual_cot import VISUAL_CHAIN_OF_THOUGHT
+from swarms.structs import Agent
+
+# Load the environment variables
+load_dotenv()
+
+# Get the API key from the environment
+api_key = os.environ.get("OPENAI_API_KEY")
+
+# Initialize the language model
+llm = GPT4VisionAPI(
+    openai_api_key=api_key,
+    max_tokens=500,
+)
+
+# Initialize the task
+task = "This is an eye test. What do you see?"
+img = "playground/demos/multi_modal_chain_of_thought/eyetest.jpg"
+
+## Initialize the workflow
+agent = Agent(
+    llm=llm,
+    max_loops=2,
+    autosave=True,
+    sop=VISUAL_CHAIN_OF_THOUGHT,
+)
+
+# Run the workflow on a task
+out = agent.run(task=task, img=img)
+print(out)

playground/demos/personal_stylist/personal_stylist.py

@@ -64,23 +64,43 @@
 
 # Run agents with respective tasks
 haircut_suggestions = haircut_stylist_agent.run(
-    "Suggest suitable haircuts for this user, considering their face shape and hair type.", user_selfie
+    (
+        "Suggest suitable haircuts for this user, considering their"
+        " face shape and hair type."
+    ),
+    user_selfie,
 )
 
 # Run Makeup or Beard agent based on gender
 if user_gender == "woman":
     makeup_suggestions = makeup_or_beard_stylist_agent.run(
-        "Recommend makeup styles for this user, complementing their features.", user_selfie
+        (
+            "Recommend makeup styles for this user, complementing"
+            " their features."
+        ),
+        user_selfie,
     )
 elif user_gender == "man":
     beard_suggestions = makeup_or_beard_stylist_agent.run(
-        "Provide beard styling advice for this user, considering their face shape.", user_selfie
+        (
+            "Provide beard styling advice for this user, considering"
+            " their face shape."
+        ),
+        user_selfie,
     )
 
 clothing_suggestions = clothing_stylist_agent.run(
-    "Match clothing styles and colors for this user, using color matching principles.", clothes_image
+    (
+        "Match clothing styles and colors for this user, using color"
+        " matching principles."
+    ),
+    clothes_image,
 )
 
 accessories_suggestions = accessories_stylist_agent.run(
-    "Suggest accessories to complement this user's outfit, considering the overall style.", clothes_image
+    (
+        "Suggest accessories to complement this user's outfit,"
+        " considering the overall style."
+    ),
+    clothes_image,
 )