返回提交历史
Modified
.gitignore
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gui/README.md
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gui/__init__.py
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gui/image1.png
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gui/image2.png
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gui/query_methods.py
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gui/streamlit_chat_app.py
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requirements.txt
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XFEstudio/gpt4free
First implementation of streamlit chat app in gui folder
952f7dbe
代码差异
8 个文件
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/dataSources/
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/dataSources.local.xml
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# Ignore local python virtual environment
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venv/
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# Ignore streamlit_chat_app.py conversations pickle
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conversations.pkl
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# Ignore accounts created by api's
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accounts.txt
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.idea/
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*/__pycache__/
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# gpt4free gui
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mode `streamlit_app.py` into base folder to run
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This code provides a Graphical User Interface (GUI) for gpt4free. Users can ask questions and get answers from GPT-4 API's, utilizing multiple API implementations. The project contains two different Streamlit applications: `streamlit_app.py` and `streamlit_chat_app.py`.
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Installation
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------------
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1. Clone the repository.
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2. Install the required dependencies with: `pip install -r requirements.txt`.
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3. To use `streamlit_chat_app.py`, note that it depends on a pull request (PR #24) from the https://github.com/AI-Yash/st-chat/ repository, which may change in the future. The current dependency library can be found at https://github.com/AI-Yash/st-chat/archive/refs/pull/24/head.zip.
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Usage
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-----
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Choose one of the Streamlit applications to run:
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### streamlit\_app.py
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This application provides a simple interface for asking GPT-4 questions and receiving answers.
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To run the application:
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run:
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```arduino
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streamlit run gui/streamlit_app.py
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```
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<br>
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<img width="724" alt="image" src="https://user-images.githubusercontent.com/98614666/234232449-0d5cd092-a29d-4759-8197-e00ba712cb1a.png">
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<br>
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<br>
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preview:
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<img width="1125" alt="image" src="https://user-images.githubusercontent.com/98614666/234232398-09e9d3c5-08e6-4b8a-b4f2-0666e9790c7d.png">
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run:
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<img width="724" alt="image" src="https://user-images.githubusercontent.com/98614666/234232449-0d5cd092-a29d-4759-8197-e00ba712cb1a.png">
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### streamlit\_chat\_app.py
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This application provides a chat-like interface for asking GPT-4 questions and receiving answers. It supports multiple query methods, and users can select the desired API for their queries. The application also maintains a conversation history.
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To run the application:
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```arduino
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streamlit run streamlit_chat_app.py
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```
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<br>
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<img width="724" alt="image" src="image1.png">
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<br>
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<br>
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preview:
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<img width="1125" alt="image" src="image2.png">
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Contributing
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------------
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Feel free to submit pull requests, report bugs, or request new features by opening issues on the GitHub repository.
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Bug
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----
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There is a bug in `streamlit_chat_app.py` right now that I haven't pinpointed yet, probably is really simple but havent had the time to look for it. Whenever you open a new conversation or access an old conversation it will only start prompt-answering after the second time you input to the text input, other than that, everything else seems to work accordingly.
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License
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-------
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This project is licensed under the MIT License.
此文件没有可显示的逐行差异。
二进制文件已变更，无法进行逐行预览。
二进制文件已变更，无法进行逐行预览。
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import forefront, quora, theb, you
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import random
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def query_forefront(question: str) -> str:
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# create an account
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token = forefront.Account.create(logging=True)
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# get a response
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try:
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result = forefront.StreamingCompletion.create(token = token, prompt = 'hello world', model='gpt-4')
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return result['response']
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except Exception as e:
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# Return error message if an exception occurs
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return f'An error occurred: {e}. Please make sure you are using a valid cloudflare clearance token and user agent.'
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def query_quora(question: str) -> str:
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token = quora.Account.create(logging=False, enable_bot_creation=True)
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response = quora.Completion.create(
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model='gpt-4',
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prompt=question,
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token=token
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)
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return response.completion.choices[0].tex
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def query_theb(question: str) -> str:
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# Set cloudflare clearance cookie and get answer from GPT-4 model
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try:
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result = theb.Completion.create(
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prompt = question)
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return result['response']
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except Exception as e:
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# Return error message if an exception occurs
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return f'An error occurred: {e}. Please make sure you are using a valid cloudflare clearance token and user agent.'
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def query_you(question: str) -> str:
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# Set cloudflare clearance cookie and get answer from GPT-4 model
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try:
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result = you.Completion.create(
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prompt = question)
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return result['response']
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except Exception as e:
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# Return error message if an exception occurs
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return f'An error occurred: {e}. Please make sure you are using a valid cloudflare clearance token and user agent.'
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# Define a dictionary containing all query methods
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avail_query_methods = {
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"Forefront": query_forefront,
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"Quora": query_quora,
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"Theb": query_theb,
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"You": query_you,
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# "Writesonic": query_writesonic,
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# "T3nsor": query_t3nsor,
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# "Phind": query_phind,
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# "Ora": query_ora,
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}
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def query(user_input: str, selected_method: str = "Random") -> str:
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# If a specific query method is selected (not "Random") and the method is in the dictionary, try to call it
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if selected_method != "Random" and selected_method in avail_query_methods:
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try:
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return avail_query_methods[selected_method](user_input)
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except Exception as e:
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print(f"Error with {selected_method}: {e}")
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return "😵 Sorry, some error occurred please try again."
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# Initialize variables for determining success and storing the result
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success = False
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result = "😵 Sorry, some error occurred please try again."
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# Create a list of available query methods
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query_methods_list = list(avail_query_methods.values())
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# Continue trying different methods until a successful result is obtained or all methods have been tried
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while not success and query_methods_list:
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# Choose a random method from the list
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chosen_query = random.choice(query_methods_list)
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# Find the name of the chosen method
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chosen_query_name = [k for k, v in avail_query_methods.items() if v == chosen_query][0]
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try:
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# Try to call the chosen method with the user input
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result = chosen_query(user_input)
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success = True
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except Exception as e:
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print(f"Error with {chosen_query_name}: {e}")
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# Remove the failed method from the list of available methods
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query_methods_list.remove(chosen_query)
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return result
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__all__ = ['query', 'avail_query_methods']
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# def query_ora(question:str)->str:
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# result =""
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# try:
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# gpt4_chatbot_ids = ['b8b12eaa-5d47-44d3-92a6-4d706f2bcacf', 'fbe53266-673c-4b70-9d2d-d247785ccd91', 'bd5781cf-727a-45e9-80fd-a3cfce1350c6', '993a0102-d397-47f6-98c3-2587f2c9ec3a', 'ae5c524e-d025-478b-ad46-8843a5745261', 'cc510743-e4ab-485e-9191-76960ecb6040', 'a5cd2481-8e24-4938-aa25-8e26d6233390', '6bca5930-2aa1-4bf4-96a7-bea4d32dcdac', '884a5f2b-47a2-47a5-9e0f-851bbe76b57c', 'd5f3c491-0e74-4ef7-bdca-b7d27c59e6b3', 'd72e83f6-ef4e-4702-844f-cf4bd432eef7', '6e80b170-11ed-4f1a-b992-fd04d7a9e78c', '8ef52d68-1b01-466f-bfbf-f25c13ff4a72', 'd0674e11-f22e-406b-98bc-c1ba8564f749', 'a051381d-6530-463f-be68-020afddf6a8f', '99c0afa1-9e32-4566-8909-f4ef9ac06226', '1be65282-9c59-4a96-99f8-d225059d9001', 'dba16bd8-5785-4248-a8e9-b5d1ecbfdd60', '1731450d-3226-42d0-b41c-4129fe009524', '8e74635d-000e-4819-ab2c-4e986b7a0f48', 'afe7ed01-c1ac-4129-9c71-2ca7f3800b30', 'e374c37a-8c44-4f0e-9e9f-1ad4609f24f5']
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# chatbot_id = random.choice(gpt4_chatbot_ids)
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# model = ora.CompletionModel.load(chatbot_id, 'gpt-4')
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# response = ora.Completion.create(model, question)
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# result = response.completion.choices[0].text
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# except Exception as e:
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# print(f"Error : {e}")
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# result = "😵 Sorry, some error occurred please try again."
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# return result
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# def query_writesonic(question:str)->str:
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# account = writesonic.Account.create(logging = False)
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# response = writesonic.Completion.create(
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# api_key = account.key,
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# prompt = question,
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# )
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# return response.completion.choices[0].text
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# def query_t3nsor(question: str) -> str:
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# messages = []
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# user = question
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# t3nsor_cmpl = t3nsor.Completion.create(
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# prompt=user,
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# messages=messages
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# )
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# messages.extend([
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# {'role': 'user', 'content': user},
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# {'role': 'assistant', 'content': t3nsor_cmpl.completion.choices[0].text}
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# ])
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# return t3nsor_cmpl.completion.choices[0].text
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# def query_phind(question:str)->str:
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# phind.cf_clearance = 'KvXc1rh.TFQG1rNF0eMlcpJbsdmJkYgvmqS42OOfqUk-1682393898-0-160'
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# # phind.cf_clearance = 'heguhSRBB9d0sjLvGbQECS8b80m2BQ31xEmk9ChshKI-1682268995-0-160'
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# # phind.user_agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36'
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# phind.user_agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.4.1 Safari/605.1.15'
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# result = phind.Completion.create(
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# model = 'gpt-4',
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# prompt = question,
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# results = phind.Search.create(question, actualSearch = False),
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# creative = False,
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# detailed = False,
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# codeContext = '')
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# # print(result.completion.choices[0].text)
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# return result.completion.choices[0].text
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import os
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import sys
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sys.path.append(os.path.join(os.path.dirname(__file__), os.path.pardir))
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import streamlit as st
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from streamlit_chat import message
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from query_methods import query, avail_query_methods
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import pickle
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conversations_file = "conversations.pkl"
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def load_conversations():
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try:
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with open(conversations_file, "rb") as f:
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return pickle.load(f)
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except FileNotFoundError:
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return []
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def save_conversations(conversations, current_conversation):
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updated = False
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for i, conversation in enumerate(conversations):
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if conversation == current_conversation:
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conversations[i] = current_conversation
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updated = True
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break
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if not updated:
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conversations.append(current_conversation)
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with open(conversations_file, "wb") as f:
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pickle.dump(conversations, f)
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st.header("Chat Placeholder")
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if 'conversations' not in st.session_state:
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st.session_state['conversations'] = load_conversations()
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if 'input_text' not in st.session_state:
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st.session_state['input_text'] = ''
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if 'selected_conversation' not in st.session_state:
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st.session_state['selected_conversation'] = None
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if 'input_field_key' not in st.session_state:
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st.session_state['input_field_key'] = 0
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if 'query_method' not in st.session_state:
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st.session_state['query_method'] = query
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# Initialize new conversation
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if 'current_conversation' not in st.session_state or st.session_state['current_conversation'] is None:
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st.session_state['current_conversation'] = {'user_inputs': [], 'generated_responses': []}
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input_placeholder = st.empty()
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user_input = input_placeholder.text_input('You:', key=f'input_text_{len(st.session_state["current_conversation"]["user_inputs"])}')
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submit_button = st.button("Submit")
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if user_input or submit_button:
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output = query(user_input, st.session_state['query_method'])
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st.session_state.current_conversation['user_inputs'].append(user_input)
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st.session_state.current_conversation['generated_responses'].append(output)
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save_conversations(st.session_state.conversations, st.session_state.current_conversation)
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user_input = input_placeholder.text_input('You:', value='', key=f'input_text_{len(st.session_state["current_conversation"]["user_inputs"])}') # Clear the input field
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# Add a button to create a new conversation
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if st.sidebar.button("New Conversation"):
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st.session_state['selected_conversation'] = None
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st.session_state['current_conversation'] = {'user_inputs': [], 'generated_responses': []}
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st.session_state['input_field_key'] += 1
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st.session_state['query_method'] = st.sidebar.selectbox(
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"Select API:",
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options=avail_query_methods.keys(),
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index=0
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)
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# Sidebar
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st.sidebar.header("Conversation History")
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for i, conversation in enumerate(st.session_state.conversations):
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if st.sidebar.button(f"Conversation {i + 1}: {conversation['user_inputs'][0]}", key=f"sidebar_btn_{i}"):
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st.session_state['selected_conversation'] = i
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st.session_state['current_conversation'] = st.session_state.conversations[i]
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if st.session_state['selected_conversation'] is not None:
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conversation_to_display = st.session_state.conversations[st.session_state['selected_conversation']]
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else:
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conversation_to_display = st.session_state.current_conversation
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if conversation_to_display['generated_responses']:
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for i in range(len(conversation_to_display['generated_responses']) - 1, -1, -1):
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message(conversation_to_display["generated_responses"][i], key=f"display_generated_{i}")
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message(conversation_to_display['user_inputs'][i], is_user=True, key=f"display_user_{i}")
@@ -9,3 +9,4 @@ streamlit==1.21.0
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selenium
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fake-useragent
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twocaptcha
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https://github.com/AI-Yash/st-chat/archive/refs/pull/24/head.zip