Fix Groq provider in CHANGELOG.md and update version in pyproject.toml

.envrc.template

@@ -1,5 +1,4 @@
 export OPENAI_API_KEY=""
 export ANTHROPIC_API_KEY=""
 export XAI_API_KEY=""
-export OLLAMA_HOST_URL=""
-export GROQ_API_KEY=""
+export GROQ_API_KEY=""

.gitignore

@@ -166,4 +166,3 @@ cython_debug/
 .env
 
 src/**
-requirements.txt

Dockerfile

@@ -0,0 +1,12 @@
+FROM python:3.12.0
+
+RUN apt-get update -y && apt-get upgrade -y
+RUN pip install --upgrade pip
+
+COPY requirements.txt /src/requirements.txt
+
+WORKDIR /src
+
+RUN pip install -r requirements.txt
+
+ENTRYPOINT ["python", "build.py"]

README.md

@@ -133,7 +133,7 @@ conversation.add_plugin(SimpleMemoryPlugin())
 
 conversation.add_message(
     role="user",
-    text="Please write a poem about the moon",
+    text="Write a poem about the moon",
 )
 ```
 ```pycon

docker-compose.yaml

@@ -0,0 +1,10 @@
+services:
+  simplemind:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    volumes:
+      - ./simplemind:/src/simplemind
+      - ./build.py:/src/build.py
+    env_file:
+      - .env

examples/generate_data.py

@@ -1,4 +1,4 @@
-from typing import List, Iterator
+from typing import List
 
 from pydantic import BaseModel
 
@@ -9,36 +9,21 @@ class Movie(BaseModel):
     title: str
     year: int
 
-
 class MovieCharecter(BaseModel):
     name: str
     actor: str
 
-
 class MovieQuote(BaseModel):
     quote: str
     movie: Movie
     charecter: MovieCharecter
 
-
 class QuotesList(BaseModel):
     quotes: List[MovieQuote]
+    theme: str
 
 
-def gen_quotes(n=10) -> Iterator[MovieQuote]:
-    """Generate a list of quotes from famous movies."""
+quotes = sm.generate_data(llm_provider="openai", llm_model="gpt-4o-mini", prompt="Generate 20 quotes from famous movies", response_model=QuotesList)
 
-    for q in sm.generate_data(
-        llm_provider="openai",
-        llm_model="gpt-4o-mini",
-        prompt=f"Generate {n} quotes from famous movies",
-        response_model=QuotesList,
-    ).quotes:
-        yield q
-
-
-if __name__ == "__main__":
-    for quote in gen_quotes(n=20):
-        print(
-            f"{quote.charecter.name} from {quote.movie.title} ({quote.movie.year}): {quote.quote!r}"
-        )
+for quote in quotes.quotes:
+    print(f"{quote.charecter.name} from {quote.movie.title} ({quote.movie.year}): {quote.quote!r}")

examples/simple_memory.py

@@ -21,7 +21,7 @@ conversation.add_plugin(SimpleMemoryPlugin())
 
 conversation.add_message(
     role="user",
-    text="Please write a poem about the moon",
+    text="Write a poem about the moon",
 )
 
 r = conversation.send()

examples/translate_text.py

@@ -1,13 +1,9 @@
 from _context import sm
 
+conversation = sm.create_conversation(llm_model="gpt-4o", llm_provider="openai")
 
-def translate_to_french(text: str) -> str:
-    conversation = sm.create_conversation(llm_model="gpt-4o", llm_provider="openai")
+conversation.add_message(
+    "user", "Translate the following text to French: 'Hello, world!'"
+)
 
-    conversation.add_message(
-        "user", f"Translate the following text to French: {text!r}"
-    )
-    return conversation.send().text
-
-
-print(translate_to_french("an omlette with cheese"))
+print(conversation.send().text)

pyproject.toml

@@ -4,7 +4,7 @@ version = "0.1.1"
 description = "An experimental client for AI providers that intends to replace LangChain and LangGraph for most common use cases."
 readme = "README.md"
 requires-python = ">=3.11"
-dependencies = ["pydantic", "pydantic-settings", "instructor", "openai", "anthropic", "ollama", "groq"]
+dependencies = ["pydantic", "pydantic-settings", "instructor", "openai", "anthropic", "groq"]
 
 [build-system]
 requires = ["hatchling"]

simplemind/models.py

@@ -60,9 +60,6 @@ class Conversation(SMBaseModel):
     def __str__(self):
         return f"<Conversation id={self.id!r}>"
 
-    def prepend_system_message(self, role: str, text: str, meta: Optional[Dict[str, Any]] = None):
-        self.messages = [Message(role=role, text=text, meta=meta or {})] + self.messages
-
     def add_message(
         self, role: MESSAGE_ROLE, text: str, meta: Optional[Dict[str, Any]] = None
     ):

simplemind/providers/__init__.py

@@ -4,7 +4,6 @@ from simplemind.providers._base import BaseProvider
 from simplemind.providers.anthropic import Anthropic
 from simplemind.providers.groq import Groq
 from simplemind.providers.openai import OpenAI
-from simplemind.providers.ollama import Ollama
 from simplemind.providers.xai import XAI
 
-providers: List[Type[BaseProvider]] = [Anthropic, Groq, OpenAI, Ollama, XAI]
+providers: List[Type[BaseProvider]] = [Anthropic, Groq, OpenAI, XAI]

simplemind/providers/ollama.py

@@ -1,77 +0,0 @@
-import ollama as ol
-import instructor
-from openai import OpenAI
-
-from ._base import BaseProvider
-from ..settings import settings
-
-PROVIDER_NAME = "ollama"
-DEFAULT_MODEL = "llama3.2"
-DEFAULT_TIMEOUT = 60
-
-
-class Ollama(BaseProvider):
-    NAME = PROVIDER_NAME
-    DEFAULT_MODEL = DEFAULT_MODEL
-    TIMEOUT = DEFAULT_TIMEOUT
-
-    def __init__(self, host_url: str = None):
-        self.host_url = host_url or settings.OLLAMA_HOST_URL
-
-    @property
-    def client(self):
-        """The raw Ollama client."""
-        if not self.host_url:
-            raise ValueError("No ollama host url provided")
-        return ol.Client(timeout=self.TIMEOUT, host=self.host_url)
-
-    @property
-    def structured_client(self):
-        """A client patched with Instructor."""
-        return instructor.from_openai(
-            OpenAI(
-                base_url=f"{self.host_url}/v1",
-                api_key="ollama",
-            ),
-            mode=instructor.Mode.JSON,
-        )
-
-    def send_conversation(self, conversation: "Conversation"):
-        """Send a conversation to the Ollama API."""
-        from ..models import Message
-
-        messages = [
-            {"role": msg.role, "content": msg.text} for msg in conversation.messages
-        ]
-        response = self.client.chat(
-            model=conversation.llm_model or DEFAULT_MODEL, messages=messages
-        )
-        assistant_message = response.get("message")
-
-        # Create and return a properly formatted Message instance
-        return Message(
-            role="assistant",
-            text=assistant_message.get("content"),
-            raw=response,
-            llm_model=conversation.llm_model or DEFAULT_MODEL,
-            llm_provider=PROVIDER_NAME,
-        )
-
-    def structured_response(self, prompt, response_model, *, llm_model: str, **kwargs):
-        messages = [
-            {"role": "user", "content": prompt},
-        ]
-
-        response = self.structured_client.chat.completions.create(
-            messages=messages, model=llm_model, response_model=response_model, **kwargs
-        )
-        return response
-
-    def generate_text(self, prompt, *, llm_model):
-        messages = [
-            {"role": "user", "content": prompt},
-        ]
-
-        response = self.client.chat(messages=messages, model=llm_model)
-
-        return response.get("message").get("content")

simplemind/settings.py

@@ -12,7 +12,6 @@ class Settings(BaseSettings):
     )
     GROQ_API_KEY: Optional[SecretStr] = Field(None, description="API key for Groq")
     OPENAI_API_KEY: Optional[SecretStr] = Field(None, description="API key for OpenAI")
-    OLLAMA_HOST_URL: Optional[str] = Field(None, description="Fully qualified host URL for Ollama")
     XAI_API_KEY: Optional[SecretStr] = Field(None, description="API key for xAI")
     DEFAULT_LLM_PROVIDER: str = Field("openai", description="The default LLM provider")
 

test_ollama.py

@@ -1,66 +0,0 @@
-import os
-import unittest
-from unittest import mock
-import simplemind as sm
-from pydantic import BaseModel
-
-class TestOllama(unittest.TestCase):
-
-  def test_generate_text(self):
-    result = sm.generate_text(prompt="What is the meaning of life?", llm_provider="ollama", llm_model="llama3.2")
-    self.assertGreater(len(result), 0)
-    self.assertIsNotNone(result)
-
-  def test_create_conversation(self):
-    conversation = sm.create_conversation(llm_provider="ollama", llm_model="llama3.2")
-    conversation.add_message("user", "Remember the number 42.")
-    result = conversation.send()
-    self.assertIsNotNone(result)
-    self.assertGreaterEqual(len(result.text), 0)
-    self.assertIsInstance(result, sm.models.Message)
-
-  def test_memory(self):
-    class SimpleMemoryPlugin:
-      def __init__(self):
-          self.memories = [
-              "the earth has fictionally been destroyed.",
-              "the moon is made of cheese.",
-          ]
-
-      def yield_memories(self):
-          return (m for m in self.memories)
-
-      def send_hook(self, conversation: sm.Conversation):
-          for m in self.yield_memories():
-              conversation.prepend_system_message(role="system", text=m)
-    
-    conversation = sm.create_conversation(llm_provider="ollama", llm_model="llama3.2")
-
-    conversation.add_message(
-        role="user",
-        text="Write a poem about the moon",
-    )
-    self.assertGreater(len(conversation.messages), 0)
-    conversation.add_plugin(SimpleMemoryPlugin())
-    result = conversation.send()
-    self.assertGreater(len(conversation.messages), 2)
-    self.assertIsNotNone(result)
-    self.assertIsNotNone(result.text)
-    self.assertGreater(len(result.text), 0)
-    self.assertIsInstance(result, sm.models.Message)
-
-  def test_structure_response(self):
-      class Poem(BaseModel):
-          title: str
-          content: str
-      # Test for NotImplementedError
-      with self.assertRaises(NotImplementedError):
-          sm.generate_data(
-              prompt="Write a poem about love",
-              llm_provider="ollama",
-              llm_model="llama3.2",
-              response_model=Poem)
-
-
-if __name__ == '__main__':
-  unittest.main()