example retrieved from documentation

ollama_tools.py

@@ -0,0 +1,44 @@
+from langchain.chains import create_extraction_chain
+
+# Schema
+schema = {
+    "properties": {
+        "name": {"type": "string"},
+        "height": {"type": "integer"},
+        "hair_color": {"type": "string"},
+    },
+    "required": ["name", "height"],
+}
+
+# Input
+input = """Alex is 5 feet tall. Claudia is 1 feet taller than Alex and jumps higher than him. Claudia is a brunette and Alex is blonde."""
+
+
+
+from langchain_experimental.llms.ollama_functions import OllamaFunctions
+
+
+import os
+
+import dotenv
+
+dotenv.load_dotenv()
+
+ 
+OLLMA_BASE_URL = os.getenv("OLLMA_BASE_URL")
+
+
+# supports many more optional parameters. Hover on your `ChatOllama(...)`
+# class to view the latest available supported parameters
+model = llm = OllamaFunctions(
+    model="mistral:instruct",
+    base_url= OLLMA_BASE_URL
+    )
+
+# model = OllamaFunctions(model="mistral")
+
+# Run chain
+# llm = OllamaFunctions(model="mistral:instruct", temperature=0)
+chain = create_extraction_chain(schema, llm)
+output = chain.run(input)
+x = 0