disler · March 21, 2025 22:06 · Nov 14, 2023 · Nov 14, 2023 · Oct 1, 2023
diff --git a/llm.py b/llm.py
@@ -9,7 +9,7 @@
     Provide supporting prompt engineering functions.
 """
 
-
+from dataclasses import dataclass
 import json
 import sys
 from dotenv import load_dotenv
@@ -18,12 +18,6 @@
 import openai
 import tiktoken
 
-@dataclass
-class TurboTool:
-    name: str
-    config: dict
-    function: Callable
-
 # load .env file
 load_dotenv()
 
@@ -34,6 +28,12 @@ class TurboTool:
 
 # ------------------ helpers ------------------
 
+@dataclass
+class TurboTool:
+    name: str # function name
+    config: dict # open ai config
+    function: Callable # function
+
 
 
 def safe_get(data, dot_chained_keys):

diff --git a/llm.py b/llm.py
@@ -1,14 +1,28 @@
 """
+Purpose:
+    Interact with the UPDATED OpenAI API Supports 1.2.3+
+    Provide supporting prompt engineering functions.
+"""
+"""
 Purpose:
     Interact with the OpenAI API.
     Provide supporting prompt engineering functions.
 """
 
+
+import json
 import sys
 from dotenv import load_dotenv
 import os
-from typing import Any, Dict
+from typing import Any, Dict, List, Callable
 import openai
+import tiktoken
+
+@dataclass
+class TurboTool:
+    name: str
+    config: dict
+    function: Callable
 
 # load .env file
 load_dotenv()
@@ -21,6 +35,7 @@
 # ------------------ helpers ------------------
 
 
+
 def safe_get(data, dot_chained_keys):
     """
     {'a': {'b': [{'c': 1}]}}
@@ -45,47 +60,191 @@ def response_parser(response: Dict[str, Any]):
 # ------------------ content generators ------------------
 
 
-def prompt(prompt: str, model: str = "gpt-4") -> str:
-    # validate the openai api key - if it's not valid, raise an error
+def prompt(
+    prompt: str,
+    model: str = "gpt-4-1106-preview",
+    instructions: str = "You are a helpful assistant.",
+) -> str:
+    """
+    Generate a response from a prompt using the OpenAI API.
+    """
+
     if not openai.api_key:
         sys.exit(
             """
-
 ERORR: OpenAI API key not found. Please export your key to OPENAI_API_KEY
+Example bash command:
+    export OPENAI_API_KEY=<your openai apikey>
+            """
+        )
+
+    response = openai.chat.completions.create(
+        model=model,
+        messages=[
+            {
+                "role": "system",
+                "content": instructions,  # Added instructions as a system message
+            },
+            {
+                "role": "user",
+                "content": prompt,
+            },
+        ],
+    )
+
+    return response_parser(response.model_dump())
+
+
+def prompt_func(
+    prompt: str,
+    turbo_tools: List[TurboTool],
+    model: str = "gpt-4-1106-preview",
+    instructions: str = "You are a helpful assistant.",
+) -> str:
+    """
+    Generate a response from a prompt using the OpenAI API.
+    Force function calls to the provided turbo tools.
+
+    :param prompt: The prompt to send to the model.
+    :param turbo_tools: List of TurboTool objects each containing the tool's name, configuration, and function.
+    :param model: The model version to use, default is 'gpt-4-1106-preview'.
+    :return: The response generated by the model.
+    """
+
+    messages = [{"role": "user", "content": prompt}]
+    tools = [turbo_tool.config for turbo_tool in turbo_tools]
+
+    tool_choice = (
+        "auto"
+        if len(turbo_tools) > 1
+        else {"type": "function", "function": {"name": turbo_tools[0].name}}
+    )
+
+    messages.insert(
+        0, {"role": "system", "content": instructions}
+    )  # Insert instructions as the first system message
+    response = openai.chat.completions.create(
+        model=model, messages=messages, tools=tools, tool_choice=tool_choice
+    )
+
+    response_message = response.choices[0].message
+    tool_calls = response_message.tool_calls
+
+    func_responses = []
+
+    if tool_calls:
+        messages.append(response_message)
+
+        for tool_call in tool_calls:
+            for turbo_tool in turbo_tools:
+                if tool_call.function.name == turbo_tool.name:
+                    function_response = turbo_tool.function(
+                        **json.loads(tool_call.function.arguments)
+                    )
+
+                    func_responses.append(function_response)
+
+                    message_to_append = {
+                        "tool_call_id": tool_call.id,
+                        "role": "tool",
+                        "name": turbo_tool.name,
+                        "content": function_response,
+                    }
+                    messages.append(message_to_append)
+                    break
+
+    return func_responses
+
 
+def prompt_json_response(
+    prompt: str,
+    model: str = "gpt-4-1106-preview",
+    instructions: str = "You are a helpful assistant.",
+) -> str:
+    """
+    Generate a response from a prompt using the OpenAI API.
+
+    Example:
+        res = llm.prompt_json_response(
+            f"You're a data innovator. You analyze SQL databases table structure and generate 3 novel insights for your team to reflect on and query.
+            Generate insights for this this prompt: {prompt}.
+            Format your insights in JSON format. Respond in this json format [{{insight, sql, actionable_business_value}}, ...]",
+        )
+    """
+
+    if not openai.api_key:
+        sys.exit(
+            """
+ERORR: OpenAI API key not found. Please export your key to OPENAI_API_KEY
 Example bash command:
     export OPENAI_API_KEY=<your openai apikey>
             """
         )
 
-    response = openai.ChatCompletion.create(
+    response = openai.chat.completions.create(
         model=model,
         messages=[
+            {
+                "role": "system",
+                "content": instructions,  # Added instructions as a system message
+            },
             {
                 "role": "user",
                 "content": prompt,
-            }
+            },
         ],
+        response_format={"type": "json_object"},
     )
 
-    return response_parser(response)
+    return response_parser(response.model_dump())
 
 
 def add_cap_ref(
     prompt: str, prompt_suffix: str, cap_ref: str, cap_ref_content: str
 ) -> str:
     """
     Attaches a capitalized reference to the prompt.
-
     Example
         prompt = 'Refactor this code.'
         prompt_suffix = 'Make it more readable using this EXAMPLE.'
         cap_ref = 'EXAMPLE'
         cap_ref_content = 'def foo():\n    return True'
-
         returns 'Refactor this code. Make it more readable using this EXAMPLE.\n\nEXAMPLE\n\ndef foo():\n    return True'
     """
 
     new_prompt = f"""{prompt} {prompt_suffix}\n\n{cap_ref}\n\n{cap_ref_content}"""
 
     return new_prompt
+
+
+def count_tokens(text: str):
+    """
+    Count the number of tokens in a string.
+    """
+    enc = tiktoken.get_encoding("cl100k_base")
+    return len(enc.encode(text))
+
+
+map_model_to_cost_per_1k_tokens = {
+    "gpt-4": 0.075,  # ($0.03 Input Tokens + $0.06 Output Tokens) / 2
+    "gpt-4-1106-preview": 0.02,  # ($0.01 Input Tokens + $0.03 Output Tokens) / 2
+    "gpt-4-1106-vision-preview": 0.02,  # ($0.01 Input Tokens + $0.03 Output Tokens) / 2
+    "gpt-3.5-turbo-1106": 0.0015,  # ($0.001 Input Tokens + $0.002 Output Tokens) / 2
+}
+
+
+def estimate_price_and_tokens(text, model="gpt-4"):
+    """
+    Conservative estimate the price and tokens for a given text.
+    """
+    # round up to the output tokens
+    COST_PER_1k_TOKENS = map_model_to_cost_per_1k_tokens[model]
+
+    tokens = count_tokens(text)
+
+    estimated_cost = (tokens / 1000) * COST_PER_1k_TOKENS
+
+    # round
+    estimated_cost = round(estimated_cost, 2)
+
+    return estimated_cost, tokens
diff --git a/old_llm.py b/old_llm.py
@@ -0,0 +1,91 @@
+"""
+Purpose:
+    Interact with the OpenAI API.
+    Provide supporting prompt engineering functions.
+"""
+
+import sys
+from dotenv import load_dotenv
+import os
+from typing import Any, Dict
+import openai
+
+# load .env file
+load_dotenv()
+
+assert os.environ.get("OPENAI_API_KEY")
+
+# get openai api key
+openai.api_key = os.environ.get("OPENAI_API_KEY")
+
+# ------------------ helpers ------------------
+
+
+def safe_get(data, dot_chained_keys):
+    """
+    {'a': {'b': [{'c': 1}]}}
+    safe_get(data, 'a.b.0.c') -> 1
+    """
+    keys = dot_chained_keys.split(".")
+    for key in keys:
+        try:
+            if isinstance(data, list):
+                data = data[int(key)]
+            else:
+                data = data[key]
+        except (KeyError, TypeError, IndexError):
+            return None
+    return data
+
+
+def response_parser(response: Dict[str, Any]):
+    return safe_get(response, "choices.0.message.content")
+
+
+# ------------------ content generators ------------------
+
+
+def prompt(prompt: str, model: str = "gpt-4") -> str:
+    # validate the openai api key - if it's not valid, raise an error
+    if not openai.api_key:
+        sys.exit(
+            """
+
+ERORR: OpenAI API key not found. Please export your key to OPENAI_API_KEY
+
+Example bash command:
+    export OPENAI_API_KEY=<your openai apikey>
+            """
+        )
+
+    response = openai.ChatCompletion.create(
+        model=model,
+        messages=[
+            {
+                "role": "user",
+                "content": prompt,
+            }
+        ],
+    )
+
+    return response_parser(response)
+
+
+def add_cap_ref(
+    prompt: str, prompt_suffix: str, cap_ref: str, cap_ref_content: str
+) -> str:
+    """
+    Attaches a capitalized reference to the prompt.
+
+    Example
+        prompt = 'Refactor this code.'
+        prompt_suffix = 'Make it more readable using this EXAMPLE.'
+        cap_ref = 'EXAMPLE'
+        cap_ref_content = 'def foo():\n    return True'
+
+        returns 'Refactor this code. Make it more readable using this EXAMPLE.\n\nEXAMPLE\n\ndef foo():\n    return True'
+    """
+
+    new_prompt = f"""{prompt} {prompt_suffix}\n\n{cap_ref}\n\n{cap_ref_content}"""
+
+    return new_prompt
diff --git a/llm.py b/llm.py
@@ -0,0 +1,91 @@
+"""
+Purpose:
+    Interact with the OpenAI API.
+    Provide supporting prompt engineering functions.
+"""
+
+import sys
+from dotenv import load_dotenv
+import os
+from typing import Any, Dict
+import openai
+
+# load .env file
+load_dotenv()
+
+assert os.environ.get("OPENAI_API_KEY")
+
+# get openai api key
+openai.api_key = os.environ.get("OPENAI_API_KEY")
+
+# ------------------ helpers ------------------
+
+
+def safe_get(data, dot_chained_keys):
+    """
+    {'a': {'b': [{'c': 1}]}}
+    safe_get(data, 'a.b.0.c') -> 1
+    """
+    keys = dot_chained_keys.split(".")
+    for key in keys:
+        try:
+            if isinstance(data, list):
+                data = data[int(key)]
+            else:
+                data = data[key]
+        except (KeyError, TypeError, IndexError):
+            return None
+    return data
+
+
+def response_parser(response: Dict[str, Any]):
+    return safe_get(response, "choices.0.message.content")
+
+
+# ------------------ content generators ------------------
+
+
+def prompt(prompt: str, model: str = "gpt-4") -> str:
+    # validate the openai api key - if it's not valid, raise an error
+    if not openai.api_key:
+        sys.exit(
+            """
+
+ERORR: OpenAI API key not found. Please export your key to OPENAI_API_KEY
+
+Example bash command:
+    export OPENAI_API_KEY=<your openai apikey>
+            """
+        )
+
+    response = openai.ChatCompletion.create(
+        model=model,
+        messages=[
+            {
+                "role": "user",
+                "content": prompt,
+            }
+        ],
+    )
+
+    return response_parser(response)
+
+
+def add_cap_ref(
+    prompt: str, prompt_suffix: str, cap_ref: str, cap_ref_content: str
+) -> str:
+    """
+    Attaches a capitalized reference to the prompt.
+
+    Example
+        prompt = 'Refactor this code.'
+        prompt_suffix = 'Make it more readable using this EXAMPLE.'
+        cap_ref = 'EXAMPLE'
+        cap_ref_content = 'def foo():\n    return True'
+
+        returns 'Refactor this code. Make it more readable using this EXAMPLE.\n\nEXAMPLE\n\ndef foo():\n    return True'
+    """
+
+    new_prompt = f"""{prompt} {prompt_suffix}\n\n{cap_ref}\n\n{cap_ref_content}"""
+
+    return new_prompt