add ollama

examples/ollama/README.md

@@ -1,39 +0,0 @@
-# Running a Local Ollama Model
-
-## Dependencies
-
-- ollama
-- litellm
-- setuptools
-
-## Instructions
-
-1. Install Ollama by visiting the website [https://ollama.ai/download](https://ollama.ai/download) and selecting the appropriate operating system.
-
-2. Once installed, open the Ollama app, which should be running in your taskbar.
-
-3. Open the terminal and download a model. For example, to download the llama2 model, run the command:
-
-```bash
-ollama run llama2
-```
-
-4. In your terminal, start your virtual environment and install the 'litellm[proxy]' package using poetry you can run the command:
-
-```bash
-poetry add 'litellm[proxy]'
-```
-
-5. Next, install setuptools using the command:
-
-```bash
-poetry add setuptools
-```
-
-6. Lastly, start the litellm server with the command: `litellm --model ollama/llama2`. This will expose the port on your local machine.
-
-```bash
-litellm --model ollama/llama2
-```
-
-7. Now you can run the completion!

examples/ollama/run.py

@@ -1,35 +0,0 @@
-from litellm import completion, provider_list
-from pydantic import BaseModel
-
-import instructor
-from instructor.patch import wrap_chatcompletion
-
-completion = wrap_chatcompletion(func=completion, mode=instructor.Mode.MD_JSON)
-
-
-class UserExtract(BaseModel):
-    name: str
-    age: int
-
-
-user = completion(
-    model="ollama/llama2",
-    response_model=UserExtract,
-    messages=[
-        {
-            "role": "system",
-            "content": "You are a JSON extractor. Please extract the following JSON, No Talk. You must return JSON right after the Codeblock",
-        },
-        {
-            "role": "user",
-            "content": "Extract `My name is Jason and I am 25 years old`",
-        },
-    ],
-)
-
-print(user.model_dump_json(indent=2))
-assert isinstance(user, UserExtract), "Should be instance of UserExtract"
-assert user.name.lower() == "jason"
-assert user.age == 25
-assert hasattr(user, "_raw_response")
-assert any(provider in user._raw_response.model for provider in provider_list)

examples/proscons/run.py

@@ -1,46 +1,48 @@
-import instructor
-import openai
-from pydantic import BaseModel
+from openai import OpenAI
+from pydantic import BaseModel, Field
 from typing import List
 
-client = instructor.patch(openai.Client())
+import instructor
 
 
-class Analysis(BaseModel):
-    pros: List[str]
-    cons: List[str]
+class Character(BaseModel):
+    name: str
+    age: int
+    fact: List[str] = Field(..., description="A list of facts about the character")
 
 
-analysis = client.chat.completions.create(
-    model="gpt-3.5-turbo",
-    response_model=Analysis,
-    messages=[
-        {
-            "role": "system",
-            "content": "You are a perfect entity extraction system",
-        },
-        {
-            "role": "user",
-            "content": "Give me a pro-con analysis of joining South Park Commons. ",
-        },
-    ],
+# enables `response_model` in create call
+client = instructor.patch(
+    OpenAI(
+        base_url="http://localhost:11434/v1",
+        api_key="ollama",  # required, but unused
+    ),
+    mode=instructor.Mode.JSON,
 )
 
-print(analysis.model_dump_json(indent=2))
-"""{
-  "pros": [
-    "Access to a supportive community of like-minded individuals",
-    "Opportunities for collaboration and networking",
-    "Access to shared resources and knowledge",
-    "Exposure to diverse perspectives and ideas",
-    "Potential for personal and professional growth"
-  ],
-  "cons": [
-    "Membership fees and financial commitment",
-    "Limited autonomy and flexibility",
-    "Possible conflicts or disagreements within the community",
-    "Adherence to community rules and guidelines",
-    "Time commitment for participation in community activities"
+resp = client.chat.completions.create(
+    model="llama2",
+    messages=[
+        {
+            "role": "user",
+            "content": "Tell me about the Harry Potter",
+        }
+    ],
+    response_model=Character,
+)
+print(resp.model_dump_json(indent=2))
+""" 
+{
+  "name": "Harry James Potter",
+  "age": 37,
+  "fact": [
+    "He is the chosen one.",
+    "He has a lightning-shaped scar on his forehead.",
+    "He is the son of James and Lily Potter.",
+    "He attended Hogwarts School of Witchcraft and Wizardry.",
+    "He is a skilled wizard and sorcerer.",
+    "He fought against Lord Voldemort and his followers.",
+    "He has a pet owl named Snowy."
   ]
 }
 """