Josephrp patch 2

.env.example

@@ -0,0 +1,2 @@
+# Path to the gorilla-cli executable
+GORILLA_CLI_PATH=/path/to/gorilla-cli

.gitignore

@@ -150,3 +150,4 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+.aider*

OAI_CONFIG_LIST.json

@@ -0,0 +1,28 @@
+[
+    {
+        "model": "gpt-4",
+        "api_key": "${OPENAI_API_KEY}"
+    },
+    {
+        "model": "gpt-4-1106-preview",
+        "api_key": "${OPENAI_API_KEY}"
+    },
+    {
+        "model": "gpt-3.5-turbo-16k",
+        "api_key": "${OPENAI_API_KEY}"
+    },
+    {
+        "model": "gpt-4",
+        "api_key": "${AZURE_OPENAI_API_KEY}",
+        "api_base": "${AZURE_OPENAI_API_BASE}",
+        "api_type": "azure",
+        "api_version": "2023-07-01-preview"
+    },
+    {
+        "model": "gpt-3.5-turbo",
+        "api_key": "${AZURE_OPENAI_API_KEY}",
+        "api_base": "${AZURE_OPENAI_API_BASE}",
+        "api_type": "azure",
+        "api_version": "2023-07-01-preview"
+    }
+]

README.md

@@ -10,23 +10,87 @@ pinned: false
 license: mit
 ---
 
-## Use and Install on the Command Line
+**Check the plugins folder for new Semantic Kernel Plugins**
 
-```bashh
-git clone https://github.com/Josephrp/LablabAutogen.git
-```
+## Before You Install and Use
+
+- sign up and get an api key for open ai
+- sign up and set up a project in [zilliz cloud](https://cloud.zilliz.com/)
+
+=======
+- sign up and get an api key for Bing! Search
+
+## Zilliz Plugin
+
+This plugin allows users to plug in their existing zilliz account to a multiagent framework using autogen and semantic-kernel.
+
+#### Set Up Zilliz
+![Screenshot 2023-12-11 131536](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/d1b42e9c-8fa0-4145-bf60-c975277c6f27)
+![Screenshot 2023-12-11 131608](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/5b6b1510-631a-43bb-a647-ea892793e821)
+
+#### Create an Account 
+
+1. Navigate to cloud.zilliz.com
+2. sign-up
+
+
+![Screenshot 2023-12-11 131518](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/5d657875-dc31-4f16-a36f-77f8f2391add)
+![Screenshot 2023-12-11 131237](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/4747afcf-8e34-40ae-9cd4-47d70a6fb908)
+![Screenshot 2023-12-11 131243](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/d90029c5-869b-444d-adc1-6a997cac0976)
+
+#### Create a Cluster
+![Screenshot 2023-12-11 131633](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/01af90cd-22d8-4813-b677-c13714c3b79c)
+![Screenshot 2023-12-11 131710](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/918eaa0a-cb67-4835-a302-2666193de29c)
+![Screenshot 2023-12-11 131739](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/515855a8-1ff8-407f-9184-972848f8b0af)
+![Screenshot 2023-12-11 131744](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/c728e6dc-b02d-476b-8b6a-8f5f7c6f8072)
+
+#### AutoCreate a Pipeline
+![Screenshot 2023-12-11 131824](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/0b9de3e2-74c2-428f-960a-bf7f2e901904)
+![Screenshot 2023-12-11 131913](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/73550d75-9a6d-4454-a12c-1935584cfc92)
+![Screenshot 2023-12-11 132006](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/3fd90763-d64d-4194-bd96-cda996921425)
+
+#### AutoCreate all the Pipeline
+![Screenshot 2023-12-11 132023](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/7f5a9910-fad7-45c9-9f18-af9e2b876699)
+![Screenshot 2023-12-11 132035](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/69b23ec3-ecb8-494d-bb69-c7665d9e31e8)
+
+#### Use Curl to Upload a Document
+![Screenshot 2023-12-11 135943](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/21bdfac4-99bf-413a-9cf8-a2fafeb9c837)
+![Screenshot 2023-12-11 140115](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/b89f3c69-258f-4311-962f-10f7f5bc0096)
+![Screenshot 2023-12-11 132130](https://github.com/Josephrp/semantic-kernel-v1.0-hackathon/assets/18212928/66a17880-699b-4dde-bc8a-d3e37b04e69e)
+
+#### Use Your Credentials + Existing Zilliz Cloud With Semantic Kernel !
+
+## Get Your Bing! Search API Key
+
+1. visit this weblink [https://aka.ms/bingapisignup](https://portal.azure.com/#create/microsoft.bingsearch)
+2. open your portal : [https://portal.azure.com/#create/microsoft.bingsearch](https://portal.azure.com/#create/microsoft.bingsearch) 
+
+# **Check the plugins folder for new Semantic Kernel Plugins**
+>>>>>>> 8ff1c563cb0c715e932c267d2fe967f50b8aee0d
+
+## Use and Install
+
+on the command line :
 
 ```bash
-cd LablabAutogen
+git clone https://github.com/Tonic-AI/EasyAGI
 ```
 
 ```bash
-nano app.py
+cd EasyAGI
 ```
 
-edit line 17 "    ```"openai_api_key": "YOUR_KEY_HERE",  # OpenAI API Key``` with your key
+If you're on Windows run the following command and edit the files below using notepad or VSCode and save them accordingly.
+
+```bash
+set PATH=%PATH%
+```
+then edit the OAI_CONFIG_LIST file or on the command line:
 
-then press:
+```bash
+nano OAI_CONFIG_LIST.json
+```
+on the command line , press:
 
 ```nano
  control + x
@@ -38,7 +102,38 @@ Write :
 Y
 ```
 
-to save then type :
+to save then run
+
+```bash
+nano app.py
+```
+
+and edit lines 25-27 of app.py 
+
+```python    
+    "host": "your_milvus_host",
+    "port": "your_milvus_port",
+    "collection_name": "your_collection_name"
+```
+
+with your zilliz cloud credentials. 
+
+and line 15 with your Bing! api key then save. 
+
+or if you're on the command line press:
+
+```nano
+ control + x
+```
+Write :
+
+```nano
+y
+```
+
+to save.
+
+then type the following in your command line
 
 ```bash
 pip install -r requirements.txt
@@ -49,4 +144,4 @@ and finally :
 ```bash
 python app.py
 ```
-to run.
+to run. or install and run the application inside your compiler - like VS Code. 

app.py

@@ -1,4 +1,5 @@
 import gradio as gr
+import semantic_kernel , autogen
 from pydantic import BaseModel, ValidationError
 from plugins.sk_bing_plugin import BingPlugin
 from plugins.sk_web_pages_plugin import WebPagesPlugin
@@ -8,28 +9,47 @@
 from azure.core.credentials import AzureKeyCredential
 from semantic_kernel.core_skills.text_skill import TextSkill
 from semantic_kernel.planning.basic_planner import BasicPlanner
+from semantic_kernel import Kernel
 
 # Configure your credentials here
 bing_api_key = "ArXXXXdpJ"  # Replace with your Bing API key
 
-llm_config = {
-    "type": "openai",  # "azure" or "openai"
-    "openai_api_key": "sk-rR5XXXXm",  # OpenAI API Key
-    "azure_deployment": "",  # Azure OpenAI deployment name
-    "azure_api_key": "",  # Azure OpenAI API key in the Azure portal
-    "azure_endpoint": ""  # Endpoint URL for Azure OpenAI, e.g. https://contoso.openai.azure.com/
+# llm_config = {
+#   "type": "openai",  # "azure" or "openai"
+#   "openai_api_key": "sk-rR5XXXXm",  # OpenAI API Key
+#   "azure_deployment": "",  # Azure OpenAI deployment name
+#   "azure_api_key": "",  # Azure OpenAI API key in the Azure portal
+#    "azure_endpoint": ""  # Endpoint URL for Azure OpenAI, e.g. https://contoso.openai.azure.com/
+#}
+llm_config = autogen.config_list_from_json(
+    env_or_file="OAI_CONFIG_LIST.json",
+    filter_dict={"model": {"gpt-4", "gpt-3.5-turbo-16k", "gpt-4-1106-preview"}}
+)
+
+builder_config_path = autogen.config_list_from_json(
+    env_or_file="OAI_CONFIG_LIST.json",
+    filter_dict={"model": {"gpt-4-1106-preview"}}
+)
+
+Zilliz_config = {
+    "host": "your_milvus_host", # use Zilliz Cloud
+    "port": "your_milvus_port", # use Zilliz Cloud
+    "collection_name": "your_collection_name" # use Zilliz Cloud
 }
-import semantic_kernel
 kernel = semantic_kernel.Kernel()
 kernel.import_skill(BingPlugin(bing_api_key))
 kernel.import_skill(WebPagesPlugin())
-sk_planner = AutoGenPlanner(kernel, llm_config)
-assistant = sk_planner.create_assistant_agent("Assistant")
+sk_planner = AutoGenPlanner(kernel, llm_config, builder_config_path)
 
+assistant = sk_planner.create_assistant_agent("Assistant")
 def get_response(question, max_auto_reply):
     worker = sk_planner.create_user_agent("Worker", max_auto_reply=max_auto_reply, human_input="NEVER")
+    assistant = sk_planner.create_assistant_agent("Assistant")
     worker.initiate_chat(assistant, message=question)
     return worker.get_response()
 
-iface = gr.Interface(fn=get_response, inputs=["text", "number"], outputs="text", inputs_label=["Question", "Max Auto Reply"])
-iface.launch()
+if __name__ == "__main__":
+    question = input("Tonic's EasyAGI builds multi-agent systems that use Semantic-Kernel Plugins to automate your business operations ! Describe your problem in detail, then optionally bullet point a brief step by step way to solve it, then (or optionally) give a clear command or instruction to solve the issues above:")
+    max_auto_reply = int(input("Set a maximum number of autoreplies by entering a number with minimum 10: "))
+    response = get_response(question, max_auto_reply) 
+    print("Response:", response)

chainlitdemo.py

@@ -0,0 +1,78 @@
+import gradio as gr
+from pydantic import BaseModel, ValidationError
+from plugins.sk_bing_plugin import BingPlugin
+from plugins.sk_web_pages_plugin import WebPagesPlugin
+from planning.autogen_planner import AutoGenPlanner
+from web_search_client import WebSearchClient
+from web_search_client.models import SafeSearch
+from azure.core.credentials import AzureKeyCredential
+from semantic_kernel.core_skills.text_skill import TextSkill
+from semantic_kernel.planning.basic_planner import BasicPlanner
+from semantic_kernel import Kernel
+
+# Configure your credentials here
+bing_api_key = "ArXXXXdpJ"  # Replace with your Bing API key
+
+llm_config = {
+    "type": "openai",  # "azure" or "openai"
+    "openai_api_key": "sk-rR5XXXXm",  # OpenAI API Key
+    "azure_deployment": "",  # Azure OpenAI deployment name
+    "azure_api_key": "",  # Azure OpenAI API key in the Azure portal
+    "azure_endpoint": ""  # Endpoint URL for Azure OpenAI, e.g. https://contoso.openai.azure.com/
+}
+import semantic_kernel
+kernel = semantic_kernel.Kernel()
+kernel.import_skill(BingPlugin(bing_api_key))
+kernel.import_skill(WebPagesPlugin())
+sk_planner = AutoGenPlanner(kernel, llm_config)
+assistant = sk_planner.create_assistant_agent("Assistant")
+
+def get_response(question, max_auto_reply):
+    worker = sk_planner.create_user_agent("Worker", max_auto_reply=max_auto_reply, human_input="NEVER")
+    assistant = sk_planner.create_assistant_agent("Assistant")
+    worker.initiate_chat(assistant, message=question)
+    return worker.get_response()
+
+class ChainlitAssistantAgent(AssistantAgent):
+    def __init__(self, name, sk_planner):
+        super().__init__(name)
+        self.sk_planner = sk_planner
+
+    async def process_message(self, message):
+        # Use sk_planner to process the message and generate a response
+        response = self.sk_planner.create_assistant_agent("Assistant")
+        response.initiate_chat(self, message=message)
+        return response.get_response()
+
+class ChainlitUserProxyAgent(UserProxyAgent):
+    def __init__(self, name, assistant_agent):
+        super().__init__(name)
+        self.assistant_agent = assistant_agent
+
+    async def get_human_input(self, prompt):
+        # Get input from the user via Chainlit interface
+        reply = await cl.ask_user_message(content=prompt)
+        return reply["content"].strip()
+
+    async def send(self, message):
+        # Send the message to the assistant agent and get the response
+        response = await self.assistant_agent.process_message(message)
+        # Display the response in the Chainlit interface
+        cl.message(content=response, author=self.assistant_agent.name).send()
+
+# Initialize the agents
+assistant_agent = ChainlitAssistantAgent("Assistant", sk_planner)
+user_proxy_agent = ChainlitUserProxyAgent("User_Proxy", assistant_agent)
+
+# Chainlit Web Interface
+@cl.page("/")
+def main_page():
+    with cl.form("user_input_form"):
+        question = cl.text_input("Describe your problem:")
+        submit_button = cl.button("Submit")
+
+        if submit_button:
+            cl.run_async(user_proxy_agent.send(question))
+
+if __name__ == "__main__":
+    cl.run(main_page)