System: 
Current model: gpt-4
Current date: 2024-10-27T18:21:00.518Z

You are a helpful assistant. You can help me by answering my questions. You can also ask me questions.
User: I have a python script that makes requests to the backend of a service called amigochat, that is based on gpt.
I'd like to use this service with an openai api compatible client.
I'll provide you the script and an example response, and you'll write a python script that acts as an intermediary / middleware for converting the requests and response from openai api format to amigochat format and viceversa.
Here's the script:
import requests

headers = {
    'Host': 'api.amigochat.io',
    'X-Device-Platform': 'android',
    'X-Device-Version': '11',
    'X-Device-Brand': 'samsung',
    'X-Device-Id': 'exynos96101',
    'X-App-Build-Number': '12',
    'X-App-Version': '1.0',
    'X-App-Default-Lang': 'it',
    'Content-Type': 'application/json',
    # 'Content-Length': '352',
    # 'Accept-Encoding': 'gzip, deflate, br',
    'User-Agent': 'okhttp/4.12.0',
}

json_data = {
    'messages': [
        {
            'role': 'system',
            'content': 'You are OpenAI o1.  If the response includes mathematical expressions, wrap them in markdown symbols ```math.',
        },
        {
            'role': 'user',
            'content': 'Write a python script for fibonacci pls',
        },
    ],
    'model': 'o1-preview',
    'frequency_penalty': 0,
    'max_tokens': 4000,
    'presence_penalty': 0,
    'stream': False,
    'temperature': 0.1,
    'top_p': 0.95,
}

response = requests.post('https://api.amigochat.io/v1/chat/completions', headers=headers, json=json_data, verify=False)

print(response.content)

# Note: json_data will not be serialized by requests
# exactly as it was in the original request.
#data = '{"messages":[{"role":"system","content":"You are OpenAI o1.  If the response includes mathematical expressions, wrap them in markdown symbols ```math."},{"role":"user","content":"How do I solve partial derivatives equations"}],"model":"o1-mini","frequency_penalty":0,"max_tokens":4000,"presence_penalty":0,"stream":false,"temperature":0.5,"top_p":0.95}'
#response = requests.post('https://api.amigochat.io/v1/chat/completions', headers=headers, data=data, verify=False)


Here's the output of the script:
PS C:\TMP\aiassist\amigochat> python .\request.py
C:\Users\Giovanni\AppData\Roaming\Python\Python310\site-packages\urllib3\connectionpool.py:1043: InsecureRequestWarning: Unverified HTTPS request is being made to host 'api.amigochat.io'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advanced-usage.html#ssl-warnings
  warnings.warn(
b'data: {"id":"chatcmpl-AN204xMe5A9Fs0BgsruI3xCMEJhMv","object":"chat.completion.chunk","created":1730052596,"model":"o1-preview-2024-09-12","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"Certainly! Here\'s a Python script that generates the Fibonacci sequence up to a specified number of terms:\\n\\n```python\\ndef fibonacci(n):\\n    sequence = []\\n    a, b = 0, 1\\n    for _ in range(n):\\n        sequence.append(a)\\n        a, b = b, a + b\\n    return sequence\\n\\n# Example usage:\\nnum_terms = int(input(\\"Enter the number of terms: \\"))\\nfib_sequence = fibonacci(num_terms)\\nprint(f\\"Fibonacci sequence up to {num_terms} terms:\\")\\nprint(fib_sequence)\\n```\\n\\n**Explanation:**\\n\\nThe Fibonacci sequence is a series of numbers where each number is the sum of the two preceding ones. Mathematically, it\'s defined by the recurrence relation:\\n\\n```math\\nF_n = F_{n-1} + F_{n-2}\\n```\\n\\nwith seed values:\\n\\n```math\\nF_0 = 0,\\\\quad F_1 = 1\\n```\\n\\nIn the script:\\n\\n- We define a function `fibonacci(n)` that generates the sequence up to `n` terms.\\n- We initialize the first two numbers of the sequence (`a` and `b`) as 0 and 1.\\n- We use a loop to calculate subsequent numbers by updating `a` and `b`.\\n\\n**Sample Output:**\\n\\nIf you run the script and input `10`, it will output:\\n\\n```\\nEnter the number of terms: 10\\nFibonacci sequence up to 10 terms:\\n[0, 1, 1, 2, 3, 5, 8, 13, 21, 34]\\n```\\n\\nFeel free to modify the script or let me know if you have any questions!"},"logprobs":null,"finish_reason":"stop"}]}\n\ndata: [DONE]\n\n'

Assistant: Sure, I can help with that! Below is a Python script that acts as an intermediary/middleware to convert requests and responses between the OpenAI API format and the AmigoChat format.

```python
import requests

# AmigoChat headers
amigo_headers = {
    'Host': 'api.amigochat.io',
    'X-Device-Platform': 'android',
    'X-Device-Version': '11',
    'X-Device-Brand': 'samsung',
    'X-Device-Id': 'exynos96101',
    'X-App-Build-Number': '12',
    'X-App-Version': '1.0',
    'X-App-Default-Lang': 'it',
    'Content-Type': 'application/json',
    'User-Agent': 'okhttp/4.12.0',
}

# Function to convert OpenAI request to AmigoChat format
def convert_openai_to_amigochat(openai_request):
    amigochat_request = {
        'messages': [
            {'role': 'system', 'content': openai_request['system_message']},
            {'role': 'user', 'content': openai_request['user_message']}
        ],
        'model': 'o1-preview',
        'frequency_penalty': openai_request.get('frequency_penalty', 0),
        'max_tokens': openai_request.get('max_tokens', 4000),
        'presence_penalty': openai_request.get('presence_penalty', 0),
        'stream': openai_request.get('stream', False),
        'temperature': openai_request.get('temperature', 0.1),
        'top_p': openai_request.get('top_p', 0.95),
    }
    return amigochat_request

# Function to convert AmigoChat response to OpenAI format
def convert_amigochat_to_openai(amigochat_response):
    openai_response = {
        'id': amigochat_response['id'],
        'object': amigochat_response['object'],
        'created': amigochat_response['created'],
        'model': amigochat_response['model'],
        'choices': amigochat_response['choices'],
    }
    return openai_response

# Middleware function to handle the conversion and request
def openai_to_amigochat_middleware(openai_request):
    amigochat_request = convert_openai_to_amigochat(openai_request)
    response = requests.post('https://api.amigochat.io/v1/chat/completions', headers=amigo_headers, json=amigochat_request, verify=False)
    amigochat_response = response.json()
    openai_response = convert_amigochat_to_openai(amigochat_response)
    return openai_response

# Example OpenAI request
openai_request = {
    'system_message': 'You are OpenAI o1. If the response includes mathematical expressions, wrap them in markdown symbols ```math.',
    'user_message': 'Write a python script for fibonacci pls',
    'frequency_penalty': 0,
    'max_tokens': 4000,
    'presence_penalty': 0,
    'stream': False,
    'temperature': 0.1,
    'top_p': 0.95,
}

# Get the response
response = openai_to_amigochat_middleware(openai_request)
print(response)
```

This script defines functions to convert requests and responses between the OpenAI API format and the AmigoChat format, and a middleware function to handle the conversion and make the request to AmigoChat. You can modify the `openai_request` dictionary to test with different inputs. Let me know if you have any questions or need further assistance!
User: Ok, but I want something a bit different: I want to use an external gui client, that supports openai format (as in I can use it with openai api) but I want to use it with the amigochat service.
So I need something that acts as an openai server that the gui can connect to, but handles all the conversion from and to the amigochat service
Assistant:  create a middleware that acts as an OpenAI-compatible server while communicating with the AmigoChat service, you can use a lightweight web framework like Flask. This way, your GUI client can send requests in OpenAI format to your Flask server, which will handle the conversion and communication with AmigoChat.

Below is an example of how to set this up. This script will run a simple Flask web server that listens for OpenAI-compatible requests, converts them to the AmigoChat format, sends them to the AmigoChat API, and then converts the responses back to the OpenAI format before returning them to the client.

### Requirements
Make sure you have Flask and requests installed. You can install them via pip if you don't have them already:

```bash
pip install Flask requests
```

### Middleware Script Using Flask

```python
from flask import Flask, request, jsonify
import requests

app = Flask(__name__)

# AmigoChat headers
amigo_headers = {
    'Host': 'api.amigochat.io',
    'X-Device-Platform': 'android',
    'X-Device-Version': '11',
    'X-Device-Brand': 'samsung',
    'X-Device-Id': 'exynos96101',
    'X-App-Build-Number': '12',
    'X-App-Version': '1.0',
    'X-App-Default-Lang': 'it',
    'Content-Type': 'application/json',
    'User-Agent': 'okhttp/4.12.0',
}

# Function to convert OpenAI request to AmigoChat format
def convert_openai_to_amigochat(request_json):
    amigochat_request = {
        'messages': [
            {'role': 'system', 'content': request_json['messages'][0]['content']},
            {'role': 'user', 'content': request_json['messages'][1]['content']}
        ],
        'model': 'o1-preview',
        'frequency_penalty': request_json.get('frequency_penalty', 0),
        'max_tokens': request_json.get('max_tokens', 4000),
        'presence_penalty': request_json.get('presence_penalty', 0),
        'stream': request_json.get('stream', False),
        'temperature': request_json.get('temperature', 0.1),
        'top_p': request_json.get('top_p', 0.95),
    }
    return amigochat_request

# Function to convert AmigoChat response to OpenAI format
def convert_amigochat_to_openai(amigochat_response):
    choices = amigochat_response['choices']
    openai_response = {
        'id': amigochat_response['id'],
        'object': 'chat.completion',
        'created': amigochat_response['created'],
        'model': amigochat_response['model'],
        'choices': [
            {
                'index': 0,
                'message': {
                    'role': 'assistant',
                    'content': choice['delta']['content']
                },
                'finish_reason': choice['finish_reason']
            }
            for choice in choices
        ]
    }
    return openai_response

@app.route('/v1/engines/davinci-codex/completions', methods=['POST'])
def completions():
    openai_request = request.json
    
    # Convert OpenAI request to AmigoChat format
    amigochat_request = convert_openai_to_amigochat(openai_request)

    # Send the request to AmigoChat
    amigochat_response = requests.post('https://api.amigochat.io/v1/chat/completions', headers=amigo_headers, json=amigochat_request, verify=False)
    
    # Check if the response is successful
    if amigochat_response.status_code != 200:
        return jsonify({'error': 'Error communicating with AmigoChat'}), amigochat_response.status_code
    
    # Convert the AmigoChat response to OpenAI format
    openai_response = convert_amigochat_to_openai(amigochat_response.json())

    return jsonify(openai_response)

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)
```

### Explanation:
1. **Flask App**: The script sets up a Flask web server that listens for POST requests on the `/v1/engines/davinci-codex/completions` endpoint, which is similar to the OpenAI API endpoint for completions.

2. **Request Handling**: When a request comes in, it extracts the relevant parts of the OpenAI format and converts them to the AmigoChat format using the `convert_openai_to_amigochat` function.

3. **API Call to AmigoChat**: It then sends this formatted request to the AmigoChat API.

4. **Response Handling**: After receiving the response from AmigoChat, it converts that back into the OpenAI-compatible format and sends it back to the original requestor.

5. **Running the Server**: You can run this script, and it will serve requests on `http://localhost:5000`. You can adjust the host and port as needed.

### Testing Your Middleware
You can test this middleware using tools like Postman or any OpenAI-compatible client by sending requests structured in the OpenAI format to `http://localhost:5000/v1/engines/davinci-codex/completions`.

Make sure to update the request URL and headers in your GUI client to match this middleware's endpoints while ensuring network connectivity. Let me know if you have any questions or need further clarification!
User: You made a bunch of errors dude.
I've fixed parts of the script cuz you didn't even follow openai api standards. I also added some debugging that we need for now.
Here's the script:
from flask import Flask, request, jsonify
import requests

app = Flask(__name__)

# AmigoChat headers
amigo_headers = {
    'Host': 'api.amigochat.io',
    'X-Device-Platform': 'android',
    'X-Device-Version': '11',
    'X-Device-Brand': 'samsung',
    'X-Device-Id': 'exynos961013',
    'X-App-Build-Number': '12',
    'X-App-Version': '1.0',
    'X-App-Default-Lang': 'it',
    'Content-Type': 'application/json',
    'User-Agent': 'okhttp/4.12.0',
}

# Function to convert OpenAI request to AmigoChat format
def convert_openai_to_amigochat(request_json):
    amigochat_request = {
        'messages': [
            {'role': 'system', 'content': request_json['messages'][0]['content']},
            {'role': 'user', 'content': request_json['messages'][1]['content']}
        ],
        'model': 'o1-preview',
        'frequency_penalty': request_json.get('frequency_penalty', 0),
        'max_tokens': request_json.get('max_tokens', 4000),
        'presence_penalty': request_json.get('presence_penalty', 0),
        'stream': request_json.get('stream', False),
        'temperature': request_json.get('temperature', 0.1),
        'top_p': request_json.get('top_p', 0.95),
    }
    return amigochat_request

# Function to convert AmigoChat response to OpenAI format
def convert_amigochat_to_openai(amigochat_response):
    choices = amigochat_response['choices']
    openai_response = {
        'id': amigochat_response['id'],
        'object': 'chat.completion',
        'created': amigochat_response['created'],
        'model': amigochat_response['model'],
        'choices': [
            {
                'index': 0,
                'message': {
                    'role': 'assistant',
                    'content': choice['delta']['content']
                },
                'finish_reason': choice['finish_reason']
            }
            for choice in choices
        ]
    }
    return openai_response

@app.route('/v1/chat/completions', methods=['POST'])
def completions():
    openai_request = request.json
    
    # Convert OpenAI request to AmigoChat format
    amigochat_request = convert_openai_to_amigochat(openai_request)

    # Send the request to AmigoChat
    amigochat_response = requests.post('https://api.amigochat.io/v1/chat/completions', headers=amigo_headers, json=amigochat_request, verify=False)
    
    print(amigochat_request)
    print("---------------------------")
    print(amigochat_response.content)
    
    # Check if the response is successful
    if amigochat_response.status_code != 200:
        return jsonify({'error': 'Error communicating with AmigoChat'}), amigochat_response.status_code
    
    # Convert the AmigoChat response to OpenAI format
    openai_response = convert_amigochat_to_openai(amigochat_response.json())

    return jsonify(openai_response)

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)


But there are still a bunch of errors and the openai client isn't able to communicate to amigochat through the script. Here's the output of the script:
PS C:\TMP\aiassist\amigochat> python .\proxy.py
 * Serving Flask app 'proxy'
 * Debug mode: off
WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
 * Running on all addresses (0.0.0.0)
 * Running on http://127.0.0.1:5000
 * Running on http://192.168.0.118:5000
Press CTRL+C to quit
C:\Users\Giovanni\AppData\Roaming\Python\Python310\site-packages\urllib3\connectionpool.py:1043: InsecureRequestWarning: Unverified HTTPS request is being made to host 'api.amigochat.io'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advanced-usage.html#ssl-warnings
  warnings.warn(
{'messages': [{'role': 'system', 'content': '\nCurrent model: o1-preview\nCurrent date: 2024-10-27T18:18:02.955Z\n\nYou are a helpful assistant. You can help me by answering my questions. You can also ask me questions.'}, {'role': 'user', 'content': 'Hello, who are you?'}], 'model': 'o1-preview', 'frequency_penalty': 0, 'max_tokens': 4000, 'presence_penalty': 0, 'stream': False, 'temperature': 0.1, 'top_p': 0.95}
---------------------------
b'data: {"id":"chatcmpl-AN27viFeA6VjGygLvci994r8T15Vf","object":"chat.completion.chunk","created":1730053083,"model":"o1-preview-2024-09-12","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"Hello! I\'m an AI language model here to help answer your questions and provide information on a wide range of topics. How can I assist you today?"},"logprobs":null,"finish_reason":"stop"}]}\n\ndata: [DONE]\n\n'
127.0.0.1 - - [27/Oct/2024 19:18:08] "POST /v1/chat/completions HTTP/1.1" 201 -
Assistant: I see that you&#39;re working on refining the Flask middleware to properly handle communication between your OpenAI format client and the AmigoChat service. To address the issues you&#39;re facing with the conversion and the response format, let’s make some adjustments to ensure that everything works correctly.
Issues Identified:

Response Chunking: The response from AmigoChat appears to be chunked (indicating that it might be streaming). We need to properly handle this and extract the complete response content.
OpenAI Compatibility: The format of the response must strictly match the OpenAI API response structure. The current way choices are processed might not fit the expected structure in some cases.
Improper Status Code Handling: The status code returned to the OpenAI client when successful should be 200, but the server is currently responding with 201.

Here’s a revised version of your Flask script:
Revised Flask Middleware Script
from flask import Flask, request, jsonify
import requests
import json

app = Flask(__name__)

# AmigoChat headers
amigo_headers = {
    &#39;Host&#39;: &#39;api.amigochat.io&#39;,
    &#39;X-Device-Platform&#39;: &#39;android&#39;,
    &#39;X-Device-Version&#39;: &#39;11&#39;,
    &#39;X-Device-Brand&#39;: &#39;samsung&#39;,
    &#39;X-Device-Id&#39;: &#39;exynos961013&#39;,
    &#39;X-App-Build-Number&#39;: &#39;12&#39;,
    &#39;X-App-Version&#39;: &#39;1.0&#39;,
    &#39;X-App-Default-Lang&#39;: &#39;it&#39;,
    &#39;Content-Type&#39;: &#39;application/json&#39;,
    &#39;User-Agent&#39;: &#39;okhttp/4.12.0&#39;,
}

# Function to convert OpenAI request to AmigoChat format
def convert_openai_to_amigochat(request_json):
    amigochat_request = {
        &#39;messages&#39;: [
            {&#39;role&#39;: &#39;system&#39;, &#39;content&#39;: request_json[&#39;messages&#39;][0][&#39;content&#39;]},
            {&#39;role&#39;: &#39;user&#39;, &#39;content&#39;: request_json[&#39;messages&#39;][1][&#39;content&#39;]}
        ],
        &#39;model&#39;: &#39;o1-preview&#39;,
        &#39;frequency_penalty&#39;: request_json.get(&#39;frequency_penalty&#39;, 0),
        &#39;max_tokens&#39;: request_json.get(&#39;max_tokens&#39;, 4000),
        &#39;presence_penalty&#39;: request_json.get(&#39;presence_penalty&#39;, 0),
        &#39;stream&#39;: request_json.get(&#39;stream&#39;, False),
        &#39;temperature&#39;: request_json.get(&#39;temperature&#39;, 0.1),
        &#39;top_p&#39;: request_json.get(&#39;top_p&#39;, 0.95),
    }
    return amigochat_request

# Function to extract complete response from AmigoChat
def extract_amigochat_response(amigochat_response_content):
    response_data = &quot;&quot;
    for line in amigochat_response_content.splitlines():
        if line.startswith(&quot;data:&quot;):
            response_data += line[5:]  # Get content after &#39;data:&#39;
    return json.loads(response_data)

# Function to convert AmigoChat response to OpenAI format
def convert_amigochat_to_openai(amigochat_response):
    choices = amigochat_response[&#39;choices&#39;]
    openai_response = {
        &#39;id&#39;: amigochat_response[&#39;id&#39;],
        &#39;object&#39;: &#39;chat.completion&#39;,
        &#39;created&#39;: amigochat_response[&#39;created&#39;],
        &#39;model&#39;: amigochat_response[&#39;model&#39;],
        &#39;choices&#39;: []
    }

    for choice in choices:
        openai_response[&#39;choices&#39;].append({
            &#39;index&#39;: choice[&#39;index&#39;],
            &#39;message&#39;: {
                &#39;role&#39;: &#39;assistant&#39;,
                &#39;content&#39;: choice[&#39;delta&#39;][&#39;content&#39;]
            },
            &#39;finish_reason&#39;: choice[&#39;finish_reason&#39;]
        })
    
    return openai_response

@app.route(&#39;/v1/chat/completions&#39;, methods=[&#39;POST&#39;])
def completions():
    openai_request = request.json
    
    # Convert OpenAI request to AmigoChat format
    amigochat_request = convert_openai_to_amigochat(openai_request)

    # Send the request to AmigoChat
    amigochat_response = requests.post(&#39;https://api.amigochat.io/v1/chat/completions&#39;, headers=amigo_headers, json=amigochat_request, verify=False)
    
    print(&quot;AmigoChat Request:&quot;, amigochat_request)
    print(&quot;AmigoChat Response:&quot;, amigochat_response.content)
    
    # Check if the response is not successful
    if amigochat_response.status_code != 200:
        print(&quot;Error communicating with AmigoChat:&quot;, amigochat_response.content)
        return jsonify({&#39;error&#39;: &#39;Error communicating with AmigoChat&#39;}), amigochat_response.status_code
    
    # Extract the complete response
    amigochat_response_json = extract_amigochat_response(amigochat_response.content.decode())

    # Convert the AmigoChat response to OpenAI format
    openai_response = convert_amigochat_to_openai(amigochat_response_json)

    return jsonify(openai_response), 200  # Return status code 200 for success

if __name__ == &#39;__main__&#39;:
    app.run(host=&#39;0.0.0.0&#39;, port=5000)

Key Changes Made:

Handling Chunked Responses: The extract_amigochat_response function is added to handle splitting and extracting content from the chunked response format being returned by AmigoChat.

Proper Response Structure: The conversion from AmigoChat response to OpenAI format has been ensured to create the choices array according to OpenAI&#39;s specs.

HTTP Status Codes: The successful response is sent back with a 200 status code.


Testing the Middleware

Run the Script: Start the Flask server.
Send Requests: Use your external GUI tool to send JSON requests to http://localhost:5000/v1/chat/completions in the OpenAI format.

Make sure to validate if the AmigoChat response contains the expected structures and data. If you encounter further issues, please share the specifics of the response you get back, and we&#39;ll adjust accordingly. Let me know if you need additional help!

User: Rewrite the code that you wrote in the previous message properly. Only the code
Assistant: