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https://github.com/sukarnascience/opennlp

Ai Chat Bot which supports Online (using Gimini) or Offline (preTrain Models)
https://github.com/sukarnascience/opennlp

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Ai Chat Bot which supports Online (using Gimini) or Offline (preTrain Models)

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README 

        
# openNLP



**Title:** Alternative GPT with Gemini API and Offline Capabilities



**Introduction:**



This project offers a cost-effective alternative to GPT by leveraging the Gemini API for online interactions and a locally trained model for offline scenarios. It aims to provide a robust chatbot with a 0% fail rate, ensuring continuous responses regardless of internet connectivity.



**Key Features:**



* **Cost-Effective Alternative:** Utilizes the free tier of the Gemini API for online interactions, reducing costs compared to traditional GPT solutions.

* **Dual Response Strategy:** Employs a combination of online and offline models to guarantee a response even without an internet connection.

* **Zero Fail Rate:** Ensures the chatbot can always respond to user queries, maintaining a seamless interaction experience.

* **Self-Learning (WIP):** This feature is under development and aims to enable the model to learn and improve through user interactions, similar to how we teach children.

* **Learning from Uploads (Work in Progress):** Future enhancements will allow the model to learn from uploaded datasets, expanding its knowledge base and improving its responses.



**Technical Overview:**



This section will be added once you provide more details about the implementation.  Here are some potential areas to cover:



* Programming language and libraries used

* Architecture of the online and offline models

* Details about the self-learning and upload learning functionalities (when implemented)



**Installation:**



(Provide instructions on how to install any required dependencies or packages)



**Usage:**



(Describe how to run the chatbot and interact with it, including any command-line arguments or configuration options)



**Current Limitations:**



* **Self-Learning and Upload Learning (WIP):** These features are currently under development and may have limited functionality.

* **Accuracy and Fluency:** As a young project, the model's responses may not always be perfectly accurate or fluent. We are actively working on improving its performance.



**Future Work:**



* **Refine Self-Learning:** Enhance the ability of the model to learn from user interactions.

* **Develop Upload Learning:** Implement functionality for the model to learn from uploaded data.

* **Improve Accuracy and Fluency:** Continuously improve the model's ability to generate reliable, informative, and engaging responses.

* **Expand Online Capabilities:** Explore advanced use cases with the Gemini API.



**Contributing:**



We welcome contributions from the community! If you're interested in helping, please feel free to open an issue or pull request.



**License:** MIT License



**Author:** Sukarna Jana 2024-25



**Additional Notes:**



* Consider adding visuals (e.g., screenshots, diagrams) to enhance understanding.

* Use clear and concise language throughout the README.

* Maintain the README as the project evolves to keep users informed.



---



## Fix Errors (Solutions)



If You are getting error lie 

```sh

(aibot) myserver@myserver:~/Documents/openNLP$ python3 offlineNLP.py

Loading std-startup.xml...Traceback (most recent call last):

  File "/home/myserver/Documents/openNLP/offlineNLP.py", line 22, in 

    chatbot = Chatbot()

  File "/home/myserver/Documents/openNLP/offlineNLP.py", line 6, in __init__

    self.kernel.learn("std-startup.xml")

  File "/home/myserver/Documents/openNLP/aibot/lib/python3.10/site-packages/aiml/Kernel.py", line 335, in learn

    start = time.clock()

AttributeError: module 'time' has no attribute 'clock'

```



Solution: 



It appears that your code is using the `time.clock()` method, which was deprecated and eventually removed in Python 3.8. To address this, you can replace `time.clock()` with `time.process_time()`.



Here's the modified `Kernel.py` file:



```python

# File: aiml/Kernel.py



# Replace this line:

# start = time.clock()

# with:

start = time.process_time()

```



The `time.process_time()` method is used for measuring the CPU time, and it's the recommended replacement for the deprecated `time.clock()` method.



After making this change, you should be able to use your AIML code with Python 3.7 or later without encountering the `AttributeError` related to the `time.clock()` method.