copy

.gitignore

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+# Python
+__pycache__
+*.py[cod]
+*.pyo
+*.pyd
+
+# Directories
+__pycache__
+
+# Files
+.DS_Store

LICENSE

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+MIT License
+
+Copyright (c) 2023 Leric Dax (LAK), Mnemosyne Labs, and Azoth Corp.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,12 +1,24 @@
----
-title: Claude100K API
-emoji: 💻
-colorFrom: indigo
-colorTo: green
-sdk: gradio
-sdk_version: 3.35.2
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# AnthropologAI
+ quick gradio chat interface for Anthropic AI's API for Claude, including 100k
+
+
+# Anthropic AI Chatbot
+
+This is a simple chatbot that uses the Anthropic AI API to generate responses. It uses the Gradio library to provide a basic chat interface.
+
+## Installation
+
+First, clone this repository to your local machine using `git clone https://github.com/AzothCorp/AnthropologAI.git`.
+
+Then, navigate to the project directory and install the necessary dependencies using `pip install -r requirements.txt`.
+
+## Usage
+
+Run the script using `python main.py`.
+
+This will launch a Gradio interface in your web browser where you can interact with the chatbot.
+
+## License
+
+This project is licensed under the terms of the MIT license.
+By Leric Dax (LAK), Mnemosyne Labs, and Azoth Corp (2023).

main.py

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+import gradio as gr
+import requests
+import json
+
+# Define a global variable for the conversation history
+conversation_history = ""
+
+def chat_with_ai(user_question, api_key, model):
+    global conversation_history
+
+    # Instantiate the endpoint URL
+    url = 'https://api.anthropic.com/v1/complete'
+
+    # Define the headers for the HTTP request
+    headers = {
+        'Content-Type': 'application/json',
+        'X-API-Key': api_key,
+    }
+
+    # Define the parameters for the request
+    params = {
+        'prompt': f'{conversation_history}\n\nHuman: {user_question}\n\nAssistant:',
+        'model': model,
+        'max_tokens_to_sample': 4000,
+        'stop_sequences': ['\n\nHuman:'],
+        'temperature': 0.8,
+        'top_p': -1,
+        'metadata': {}
+    }
+
+    # Convert the params dict to a JSON string
+    params_json = json.dumps(params)
+
+    # Send the HTTP request to the API
+    response = requests.post(url, headers=headers, data=params_json)
+
+    # Check if the request was successful
+    if response.status_code == 200:
+        # Parse the JSON response
+        response_json = response.json()
+        conversation_history += f'\n\nHuman: {user_question}\n\nAssistant: {response_json["completion"]}'
+
+        # Return the entire conversation history
+        return conversation_history
+    else:
+        return f'Error: {response.status_code}'
+
+# Define the model options
+model_options = ["claude-v1", "claude-v1-100k", "claude-v1.0", "claude-v1.2", "claude-v1.3", "claude-v1.3-100k", "claude-instant-v1", "claude-instant-v1-100k", "claude-instant-v1.0", "claude-instant-v1.1", "claude-instant-v1.1-100k"]
+
+iface = gr.Interface(fn=chat_with_ai, 
+                     inputs=["text", "text", gr.inputs.Dropdown(model_options)], 
+                     outputs="text",
+                     layout="vertical")
+iface.launch()

requirements.txt

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+gradio
+requests