7 |
8 | ## Prerequisites
9 |
10 | - Python 3.9 or higher
11 | - Flask
12 | - Langchain
13 | - OpenAI API
14 | - OpenAI Python library
15 |
16 | ## Getting Started
17 |
18 | 1. Clone the repository:
19 |
20 | ```bash
21 | git clone https://github.com/paramsgit/autochat-bot
22 |
23 | 2 Navigate to the project directory:
24 |
25 | cd autochat-bot
26 |
27 | 3 Install the required dependencies using pip:
28 |
29 | pip install -r requirements.txt
30 |
31 | 4 Set up OpenAI API:
32 |
33 | - Create an OpenAI account and obtain an API key.
34 | - Set the OPENAI_API_KEY environment variable with your API key
35 |
36 | On Windows:
37 | - Use the search bar in the Start menu to find “Edit the system environment variables”.
38 | - Click “Environment variables”
39 | - Use the upper “New…” button to add a User variable
40 | - Create a new variable called OPENAI_API_KEY and set the value to the secret key you got from your account settings on openai.com
41 |
42 | For Mac or Linux:
43 | - Find the .bashrc, .bash_profile, or .zshrc in your home directory
44 | - Open the file in a text editor
45 | - Add a new line to the file:
46 | ``export OPENAI_API_KEY= [your secret key]``
47 |
48 | 5 Run the application:
49 |
50 | python app.py
51 |
52 | 6 Open your web browser and visit http://127.0.0.1:{port}/ to access the chat bot.
53 |
54 |
55 |
56 | ## Usage
57 | Once the application is running, you can interact with the chat bot through the web interface. Type your messages in the input box, and the bot will respond accordingly.
58 |
59 | ## Deployment
60 | To deploy the chat bot to a production environment, follow the deployment instructions provided by the Flask documentation. It's recommended to use a production-ready WSGI server, such as Gunicorn or uWSGI.
61 |
62 | ## License
63 | This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
64 |
65 | ## Contributing
66 | Contributions are welcome! If you find any issues or have suggestions for improvements, please create a GitHub issue or submit a pull request.
67 |
68 | Feel free to modify and expand upon this template according to your specific project needs.
69 |
70 |
71 |
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/main.py:
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1 | from flask import Flask, render_template,jsonify,request
2 | from flask_cors import CORS
3 | import requests,openai,os
4 | from dotenv.main import load_dotenv
5 | from langchain.llms import OpenAI
6 | from langchain.memory import ConversationBufferMemory
7 | from langchain.chains import ConversationChain
8 | from langchain.memory import ConversationSummaryBufferMemory
9 | llm = OpenAI()
10 | memory = ConversationSummaryBufferMemory(llm=llm, max_token_limit=100)
11 | app = Flask(__name__)
12 | CORS(app)
13 |
14 | @app.route('/')
15 | def index():
16 | return render_template('index.html')
17 |
18 | @app.route('/data', methods=['POST'])
19 | def get_data():
20 | data = request.get_json()
21 | text=data.get('data')
22 | user_input = text
23 | try:
24 | conversation = ConversationChain(llm=llm,memory=memory)
25 | output = conversation.predict(input=user_input)
26 | memory.save_context({"input": user_input}, {"output": output})
27 | return jsonify({"response":True,"message":output})
28 | except Exception as e:
29 | print(e)
30 | error_message = f'Error: {str(e)}'
31 | return jsonify({"message":error_message,"response":False})
32 |
33 | if __name__ == '__main__':
34 | app.run()
35 |
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/requirements.txt:
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1 | aiohttp==3.8.4
2 | aiosignal==1.3.1
3 | annotated-types==0.5.0
4 | async-timeout==4.0.2
5 | attrs==23.1.0
6 | blinker==1.6.2
7 | certifi==2023.5.7
8 | charset-normalizer==3.1.0
9 | click==8.1.3
10 | colorama==0.4.6
11 | dataclasses-json==0.5.14
12 | Flask==2.3.2
13 | Flask-Cors==3.0.10
14 | frozenlist==1.3.3
15 | greenlet==2.0.2
16 | idna==3.4
17 | importlib-metadata==6.6.0
18 | itsdangerous==2.1.2
19 | Jinja2==3.1.2
20 | langchain==0.0.273
21 | langsmith==0.0.26
22 | MarkupSafe==2.1.2
23 | marshmallow==3.20.1
24 | multidict==6.0.4
25 | mypy-extensions==1.0.0
26 | numexpr==2.8.5
27 | numpy==1.25.2
28 | openai==0.27.6
29 | packaging==23.1
30 | pydantic==2.3.0
31 | pydantic_core==2.6.3
32 | python-dotenv==1.0.0
33 | PyYAML==6.0.1
34 | regex==2023.8.8
35 | requests==2.30.0
36 | six==1.16.0
37 | SQLAlchemy==2.0.20
38 | tenacity==8.2.3
39 | tiktoken==0.5.1
40 | tqdm==4.65.0
41 | typing-inspect==0.9.0
42 | typing_extensions==4.7.1
43 | urllib3==2.0.2
44 | Werkzeug==2.3.4
45 | yarl==1.9.2
46 | zipp==3.15.0
47 |
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/screenshot.png:
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https://raw.githubusercontent.com/paramsgit/autochat-bot/a31d5bef3fc913e391dbfb700dfa31957d593872/screenshot.png
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/temp.py:
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1 | from flask import Flask, render_template,jsonify,request
2 | from flask_cors import CORS
3 | import requests,openai,os
4 | from dotenv.main import load_dotenv
5 | from langchain.llms import OpenAI
6 | from langchain.memory import ConversationBufferMemory
7 | from langchain.chains import ConversationChain
8 | from langchain.memory import ConversationSummaryBufferMemory
9 | llm = OpenAI()
10 | memory = ConversationSummaryBufferMemory(llm=llm, max_token_limit=100)
11 | app = Flask(__name__)
12 | CORS(app)
13 |
14 | @app.route('/')
15 | def index():
16 | return render_template('index.html')
17 |
18 | @app.route('/data', methods=['POST'])
19 | def get_data():
20 | data = request.get_json()
21 | text=data.get('data')
22 | user_input = text
23 | print(user_input)
24 | try:
25 | print("Function started : ")
26 | conversation = ConversationChain(llm=llm,memory=memory,verbose=True)
27 | var1 = conversation.predict(input=user_input)
28 | memory.save_context({"input": user_input}, {"output": var1})
29 | return jsonify({"response":True,"message":var1})
30 | except Exception as e:
31 | print(e)
32 | error_message = f'Error: {str(e)}'
33 | return jsonify({"message":error_message,"response":False})
34 |
35 | if __name__ == '__main__':
36 | app.run()
37 |
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/tempCodeRunnerFile.py:
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1 | user_input
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/templates/index.html:
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7 |
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