Merge remote-tracking branch 'refs/remotes/origin/main'

README.md

@@ -15,7 +15,7 @@ pip install funcchain
 ## Introduction
 
 `funcchain` is the *most pythonic* way of writing cognitive systems. Leveraging pydantic models as output schemas combined with langchain in the backend allows for a seamless integration of llms into your apps.
-It utilizes perfect with OpenAI Functions or LlamaCpp grammars (json-schema-mode) for efficient structured output.
+It utilizes OpenAI Functions or LlamaCpp grammars (json-schema-mode) for efficient structured output.
 In the backend it compiles the funcchain syntax into langchain runnables so you can easily invoke, stream or batch process your pipelines.
 
 [![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/ricklamers/funcchain-demo)
@@ -112,7 +112,7 @@ class AnalysisResult(BaseModel):
     objects: list[str] = Field(description="A list of objects found in the image")
 
 # easy use of images as input with structured output
-def analyse_image(image: Image.Image) -> AnalysisResult:
+def analyse_image(image: Image) -> AnalysisResult:
     """
     Analyse the image and extract its
     theme, description and objects.

src/funcchain/backend/settings.py

@@ -27,11 +27,12 @@ class FuncchainSettings(BaseSettings):
     retry_parse: int = 3
     retry_parse_sleep: float = 0.1
 
-    # KEYS
+    # KEYS / URLS
     openai_api_key: Optional[str] = None
     azure_api_key: Optional[str] = None
     anthropic_api_key: Optional[str] = None
     google_api_key: Optional[str] = None
+    ollama_base_url: str = "http://localhost:11434"
 
     # MODEL KWARGS
     verbose: bool = False
@@ -60,7 +61,9 @@ def openai_kwargs(self) -> dict:
         }
 
     def ollama_kwargs(self) -> dict:
-        return {}
+        return {
+            "base_url": self.ollama_base_url
+        }
 
     def llamacpp_kwargs(self) -> dict:
         return {

src/funcchain/model/defaults.py

@@ -155,7 +155,7 @@ def univeral_model_selector(
         except Exception as e:
             print(e)
 
-    model_kwargs.pop("model_name")
+    model_kwargs.pop("model_name", None)
 
     if settings.openai_api_key:
         from langchain_openai.chat_models import ChatOpenAI

src/funcchain/syntax/executable.py

@@ -42,6 +42,8 @@ def chain(
 
     # todo maybe this should be done in the prompt processor?
     system = system or settings.system_prompt
+    if system:
+        context = [SystemMessage(content=system)] + context
     instruction = instruction or from_docstring()
 
     # temp image handling
@@ -90,6 +92,8 @@ async def achain(
 
     # todo maybe this should be done in the prompt processor?
     system = system or settings.system_prompt
+    if system:
+        context = [SystemMessage(content=system)] + context
     instruction = instruction or from_docstring()
 
     # temp image handling