Uploading Files

api_info.py

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+developer_info = {
+        'developer': 'Devs Do Code',
+        'contact': {
+            'Telegram': 'https://t.me/devsdocode',
+            'YouTube Channel': 'https://www.youtube.com/@DevsDoCode',
+            'LinkedIn': 'https://www.linkedin.com/in/developer-sreejan/',
+            'Discord Server': 'https://discord.gg/ehwfVtsAts',
+            'Instagram': {
+                'Personal': 'https://www.instagram.com/sree.shades_/',
+                'Channel': 'https://www.instagram.com/devsdocode_/'
+            }
+        }
+    }
+
+
+endpoint = {
+    'route': "/generate",
+    'params': {
+        "query": "[SEARCH QUERY]"
+    },
+    'optional_params': {
+        "max_tokens": "[]",
+        "model": "[]",
+        "temperature": "[]",
+        "system_prompt": "[]"
+    },
+    'url_demo' : '/generate?query=Who is Devs Do Code&&max_tokens=500&&model=meta-llama/Meta-Llama-3-70B-Instruct&&temperature=0.7&&system_prompt=Your Owner is "Devs Do Code"'
+}
+
+available_models = {
+    "Meta Llama 3 70B Instruct": "meta-llama/Meta-Llama-3-70B-Instruct",
+    "Meta Llama 3 8B Instruct": "meta-llama/Meta-Llama-3-8B-Instruct",
+    "Mixtral 8x22B Instruct v0.1": "mistralai/Mixtral-8x22B-Instruct-v0.1",
+    "Mixtral 8x22B v0.1": "mistralai/Mixtral-8x22B-v0.1",
+    "Microsoft WizardLM 2 8x22B": "microsoft/WizardLM-2-8x22B",
+    "Microsoft WizardLM 2 7B": "microsoft/WizardLM-2-7B",
+    "HuggingFace Zephyr Orpo 141b A35b v0.1": "HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1",
+    "Google Gemma 1.1 7b it": "google/gemma-1.1-7b-it",
+    "Databricks DBRX Instruct": "databricks/dbrx-instruct",
+    "Mixtral 8x7B Instruct v0.1": "mistralai/Mixtral-8x7B-Instruct-v0.1",
+    "Mistral 7B Instruct v0.2": "mistralai/Mistral-7B-Instruct-v0.2",
+    "Meta Llama 2 70b Chat HF": "meta-llama/Llama-2-70b-chat-hf",
+    "Cognitive Computations Dolphin 2.6 Mixtral 8x7B": "cognitivecomputations/dolphin-2.6-mixtral-8x7b"
+}
+
+error_message = {
+        'developer_contact': {
+            'Telegram': 'https://t.me/DevsDoCode',
+            'Instagram': 'https://www.instagram.com/sree.shades_/',
+            'Discord': 'https://discord.gg/ehwfVtsAts',
+            'LinkedIn': 'https://www.linkedin.com/in/developer-sreejan/',
+            'Twitter': 'https://twitter.com/Anand_Sreejan'
+        },
+        'error': 'Oops! Something went wrong. Please contact the developer Devs Do Code.'
+    }
+
+
+default_info = """This API is developed and being maintained by Devs Do Code (Sreejan).
+
+**About the Developer**
+
+Sreejan, a high school student from Patna, Bihar, India, has emerged as a notable figure in the technology sector. 
+His creation of an API is a testament to his dedication and expertise. Despite his youth, Sreejan's contributions 
+to artificial intelligence and machine learning are significant. As an AI & ML Engineer, he specializes in Deep Learning, 
+Natural Language Processing (NLP), and Robotics, with proficiency in Python, Java, and Mobile App Development. 
+Beyond his role as a technology consumer, Sreejan is an active open-source contributor, notably to projects like Hugging Face.
+
+He is also recognized for his role in community development, particularly through "Devs Do Code," a platform he 
+founded to provide quality coding resources, tutorials, and projects. His mission is to equip developers with the 
+necessary skills to thrive in the ever-evolving tech landscape. Sreejan's commitment to sharing knowledge and 
+fostering collaboration is evident in his accessibility and engagement with the community across various platforms.
+
+Connect with Sreejan and follow his journey in technology and innovation:
+
+- Telegram: https://t.me/devsdocode
+- YouTube Channel: https://www.youtube.com/@DevsDoCode
+- LinkedIn: https://www.linkedin.com/in/developer-sreejan/
+- Discord Server: https://discord.gg/ehwfVtsAts
+- Instagram 
+    - Personal: https://www.instagram.com/sree.shades_/
+    - Channel: https://www.instagram.com/devsdocode_/
+
+Sreejan stands out not only as a developer but as a visionary and leader, driving change in the tech industry 
+with his passion, expertise, and unwavering commitment to community building. He continues to shape the 
+future of technology, one line of code at a time.
+"""
+

app.py

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+from flask import Flask, request, jsonify
+import deepinfra
+import api_info
+
+app = Flask(__name__)
+
+@app.route('/')
+def initial():
+    return '<pre>' + api_info.default_info + '</pre>'
+
+@app.route("/available_models", methods=['GET'])
+def available_models():
+    return jsonify(api_info.available_models)
+
+@app.route("/endpoints", methods=['GET'])
+def endpoints():
+    return jsonify(api_info.endpoint)
+
+@app.route("/developer_info", methods=['GET'])
+def developer_info():
+    return jsonify(api_info.developer_info)
+
+@app.route('/generate', methods=['GET'])
+def generate():
+    
+    query = request.args.get('query')  # Assuming the query is sent in JSON format
+    system_prompt = str(request.args.get('system', "Be Helpful and Friendly. Keep your response straightfoward, short and concise"))  # Optional parameter with default value
+    model = str(request.args.get('model', "meta-llama/Meta-Llama-3-70B-Instruct"))  # Optional parameter with default value
+    max_tokens = int(request.args.get('max_tokens', 512))
+    temperature = float(request.args.get('temperature', 0.7))  # Optional parameter with default value
+
+    if query:
+        response = deepinfra.generate(query, model=model, system_prompt=system_prompt, temperature=temperature, max_tokens=max_tokens)
+        return jsonify([{'response': response}, {'developer_info': api_info.developer_info}]), 200
+
+    else:
+        return jsonify(api_info.error_message), 400
+
+if __name__ == '__main__':
+    app.run(debug=True)
+
+

deepinfra.py

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+import json
+import requests
+from typing import Union
+
+def generate(message: str, model: str='meta-llama/Meta-Llama-3-70B-Instruct', system_prompt: str = "Be Helpful and Friendly. Keep your response straightfoward, short and concise", max_tokens: int = 512, temperature: float = 0.7) -> Union[str, None]:
+    """
+    Utilizes a variety of large language models (LLMs) to engage in conversational interactions.
+    
+    Parameters:
+        - model (str): The name or identifier of the LLM to be used for conversation. Available models include:
+            - "meta-llama/Meta-Llama-3-70B-Instruct"
+            - "meta-llama/Meta-Llama-3-8B-Instruct" 
+            - "mistralai/Mixtral-8x22B-Instruct-v0.1"
+            - "mistralai/Mixtral-8x22B-v0.1"
+            - "microsoft/WizardLM-2-8x22B"
+            - "microsoft/WizardLM-2-7B"
+            - "HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1"
+            - "google/gemma-1.1-7b-it"
+            - "databricks/dbrx-instruct"
+            - "mistralai/Mixtral-8x7B-Instruct-v0.1"
+            - "mistralai/Mistral-7B-Instruct-v0.2"
+            - "meta-llama/Llama-2-70b-chat-hf"
+            - "cognitivecomputations/dolphin-2.6-mixtral-8x7b"
+        - message (str): The message to be sent to the LLM to initiate or continue the conversation.
+        - system_prompt (str): Optional. The initial system message to start the conversation. Defaults to "Talk Like Shakespeare".
+
+    Returns:
+        - Union[str, None]: The response message from the LLM if successful, otherwise None.
+    """
+    url = "https://api.deepinfra.com/v1/openai/chat/completions"
+
+    data = json.dumps(
+        {
+            'model': model,
+            'messages': [{"role": "system", "content": system_prompt}] + [{"role": "user", "content": message}] ,
+            'temperature': temperature,
+            'max_tokens': max_tokens,
+            'stop': [],
+            'stream': False
+        }, separators=(',', ':')
+    )
+    
+    try:
+        result = requests.post(url=url, data=data)
+        return result.json()['choices'][0]['message']['content']
+    except Exception as e:
+        print("Error:", e)
+        return None
+
+        
+
+if __name__ == "__main__":
+
+    model_names = [
+        "meta-llama/Meta-Llama-3-70B-Instruct",
+        "meta-llama/Meta-Llama-3-8B-Instruct",
+        "mistralai/Mixtral-8x22B-Instruct-v0.1",
+        "mistralai/Mixtral-8x22B-v0.1",
+        "microsoft/WizardLM-2-8x22B",
+        "microsoft/WizardLM-2-7B",
+        "HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1",
+        "google/gemma-1.1-7b-it",
+        "databricks/dbrx-instruct",
+        "mistralai/Mixtral-8x7B-Instruct-v0.1",
+        "mistralai/Mistral-7B-Instruct-v0.2",
+        "meta-llama/Llama-2-70b-chat-hf",
+        "cognitivecomputations/dolphin-2.6-mixtral-8x7b"
+    ]
+
+    for name in model_names:
+        messages =  "Introduce yourself and tell who made you and about your owner company" # Add more messages as needed
+        response = generate(name, messages, system_prompt="Respond very concisely and shortly")
+
+        print(f"• Model: {name} -", response)

requirements.txt

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+fastapi==0.110.2
+Flask==3.0.3
+Requests==2.31.0
+uvicorn==0.29.0