[0.7.4] subclass TuneModel, Groq and Mistral from Openai and remove files

Author: yashbonde

docs/changelog.rst

@@ -7,6 +7,12 @@ minor versions.
 
 All relevant steps to be taken will be mentioned here.
 
+0.7.4
+-----
+
+- Remove ``model_tune.py``, ``model_groq.py`` and ``model_mistral.py`` and subclass those models from ``Openai``.
+
+
 0.7.3
 -----
 

docs/conf.py

@@ -13,7 +13,7 @@
 project = "tuneapi"
 copyright = "2024-2025, Frello Technologies"
 author = "Frello Technologies"
-release = "0.7.3"
+release = "0.7.4"
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

docs/index.rst

@@ -13,6 +13,59 @@ into a single MIT-licensed package. It contains 3 major submodules:
 - ``tuneapi.utils``: Contains all the utility functions that are used across the Tune AI codebase. This is pretty interesting
 - ``tuneapi.endpoints``: Contains all the API endpoints for the Tune Studio
 
+
+Prompt Injection
+----------------
+
+Since ``tuneapi`` is a new and unpopular package most LLMs will not be able to generate code based on it. However you can
+paste the following code snippet in the prompt to generate the code for LLM API calls.
+
+Prompt
+~~~~~~
+
+You are going to use ``tuneapi`` package to use the LLM endpoint. Here's a brief on how to use it:
+
+.. code-block:: python
+
+    from tuneapi import tt, ta
+
+    # define a thread which is a collection of messages with system, user and assistant messages
+    thread = tt.Thread(
+        tt.system(...),   # add optional system message here
+        tt.human(...),    # add user message here
+        tt.assistant(...) # for assistant response
+    )
+
+    # define a model
+    model = ta.Gemini() # Openai, Anthropic
+
+    # get the response
+    resp: str = model.chat(thread)
+
+    # You can also generate structured response for better control
+    from pydantic import BaseModel, Field
+    from typing import List, Optional
+
+    class MathProblem(BaseModel):
+        a: int = Field(..., description="First number")
+        b: int = Field(..., description="Second number")
+        operator: str = Field(..., description="Operator")
+        hint: Optional[str] = Field(None, description="Hint for the problem")
+
+    class MathTest(BaseModel):
+        title: str = Field(..., description="Title of the test")
+        problems: List[MathProblem] = Field(..., description="List of math problems")
+
+    # define a thread which is a collection of messages
+    thread = tt.Thread(
+        tt.human("Give me 5 problems for KG-1 class"),
+        schema=MathTest
+    )
+
+    # get structured output
+    resp: MathTest = model.chat(thread)
+
+
 .. toctree::
    :maxdepth: 2
    :caption: Contents:

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "tuneapi"
-version = "0.7.3"
+version = "0.7.4"
 description = "Tune AI APIs."
 authors = ["Frello Technology Private Limited <[email protected]>"]
 license = "MIT"

tuneapi/apis/__init__.py

@@ -1,10 +1,7 @@
 # Copyright © 2024-2025 Frello Technology Private Limited
 
 # model APIs
-from tuneapi.apis.model_tune import TuneModel
-from tuneapi.apis.model_openai import Openai
+from tuneapi.apis.model_openai import Openai, TuneModel, Groq, Mistral
 from tuneapi.apis.model_anthropic import Anthropic
-from tuneapi.apis.model_groq import Groq
-from tuneapi.apis.model_mistral import Mistral
 from tuneapi.apis.model_gemini import Gemini
 from tuneapi.apis.turbo import distributed_chat, distributed_chat_async

tuneapi/apis/model_anthropic.py

@@ -6,7 +6,7 @@
 
 import httpx
 import requests
-from typing import Optional, Dict, Any, Tuple, List
+from typing import Optional, Dict, Any, List
 
 import tuneapi.utils as tu
 import tuneapi.types as tt