Added simple Ollama example (#515)

* Added simple Ollama example * Added example to docs and updated cards * Removed extra logo * re order * Cleared all outputs and resolved comments * Added ollama's own example file * Added generated example using tool * Point examples to generated file --------- Co-authored-by: Akhil Anand <[email protected]> Co-authored-by: reibs <[email protected]> Co-authored-by: Pratyush Shukla <[email protected]>
AgentOps-AI · Nov 22, 2024 · 135cf8a · 135cf8a
1 parent 882f371
commit 135cf8a
Show file tree

Hide file tree

Showing 6 changed files with 489 additions and 0 deletions.
diff --git a/docs/images/external/ollama/ollama-icon.png b/docs/images/external/ollama/ollama-icon.png
diff --git a/docs/mint.json b/docs/mint.json
@@ -92,6 +92,7 @@
         "v1/integrations/langchain",
         "v1/integrations/cohere",
         "v1/integrations/anthropic",
+        "v1/integrations/ollama",
         "v1/integrations/litellm",
         "v1/integrations/multion",
         "v1/integrations/rest"

diff --git a/docs/v1/examples/examples.mdx b/docs/v1/examples/examples.mdx
@@ -31,6 +31,9 @@ mode: "wide"
     <Card title="MultiOn Example" icon="atom" href="/v1/examples/multion">
         Create an autonomous browser agent capable of navigating the web and extracting information
     </Card>
+    <Card title="Ollama Example" icon={<img src="/images/external/ollama/ollama-icon.png" alt="Ollama" />} iconType="image" href="/v1/examples/ollama">
+        Simple Ollama integration with AgentOps
+    </Card>
 </CardGroup>
 
 ## Video Guides

diff --git a/docs/v1/examples/ollama.mdx b/docs/v1/examples/ollama.mdx
@@ -0,0 +1,123 @@
+---
+title: 'Ollama Example'
+description: 'Using Ollama with AgentOps'
+mode: "wide"
+---
+
+{/*  SOURCE_FILE: examples/ollama_examples/ollama_examples.ipynb  */}# AgentOps Ollama Integration
+
+This example demonstrates how to use AgentOps to monitor your Ollama LLM calls.
+
+First let's install the required packages
+
+> ⚠️ **Important**: Make sure you have Ollama installed and running locally before running this notebook. You can install it from [ollama.ai](https://ollama.com).
+
+
+```python
+%pip install -U ollama
+%pip install -U agentops
+%pip install -U python-dotenv
+```
+
+Then import them
+
+
+```python
+import ollama
+import agentops
+import os
+from dotenv import load_dotenv
+
+```
+
+Next, we'll set our API keys. For Ollama, we'll need to make sure Ollama is running locally.
+[Get an AgentOps API key](https://agentops.ai/settings/projects)
+
+1. Create an environment variable in a .env file or other method. By default, the AgentOps `init()` function will look for an environment variable named `AGENTOPS_API_KEY`. Or...
+2. Replace `<your_agentops_key>` below and pass in the optional `api_key` parameter to the AgentOps `init(api_key=...)` function. Remember not to commit your API key to a public repo!
+
+
+```python
+# Let's load our environment variables
+load_dotenv()
+
+AGENTOPS_API_KEY = os.getenv("AGENTOPS_API_KEY") or "<your_agentops_key>"
+```
+
+
+```python
+# Initialize AgentOps with some default tags
+agentops.init(AGENTOPS_API_KEY, default_tags=["ollama-example"])
+```
+
+Now let's make some basic calls to Ollama. Make sure you have pulled the model first, use the following or replace with whichever model you want to use.
+
+
+```python
+ollama.pull("mistral")
+```
+
+
+```python
+# Basic completion,
+response = ollama.chat(model='mistral',
+    messages=[{
+        'role': 'user',
+        'content': 'What are the benefits of using AgentOps for monitoring LLMs?',
+    }]
+)
+print(response['message']['content'])
+```
+
+Let's try streaming responses as well
+
+
+```python
+# Streaming Example
+stream = ollama.chat(
+    model='mistral',
+    messages=[{
+        'role': 'user',
+        'content': 'Write a haiku about monitoring AI agents',
+    }],
+    stream=True
+)
+
+for chunk in stream:
+    print(chunk['message']['content'], end='')
+
+```
+
+
+```python
+# Conversation Example
+messages = [
+    {
+        'role': 'user',
+        'content': 'What is AgentOps?'
+    },
+    {
+        'role': 'assistant',
+        'content': 'AgentOps is a monitoring and observability platform for LLM applications.'
+    },
+    {
+        'role': 'user',
+        'content': 'Can you give me 3 key features?'
+    }
+]
+
+response = ollama.chat(
+    model='mistral',
+    messages=messages
+)
+print(response['message']['content'])
+```
+
+> 💡 **Note**: In production environments, you should add proper error handling around the Ollama calls and use `agentops.end_session("Error")` when exceptions occur.
+
+Finally, let's end our AgentOps session
+
+
+```python
+agentops.end_session("Success")
+```
diff --git a/docs/v1/integrations/ollama.mdx b/docs/v1/integrations/ollama.mdx
@@ -0,0 +1,150 @@
+---
+title: Ollama
+description: "AgentOps provides first class support for Ollama"
+---
+
+import CodeTooltip from '/snippets/add-code-tooltip.mdx'
+import EnvTooltip from '/snippets/add-env-tooltip.mdx'
+
+<Note>
+This is a living integration. Should you need any added functionality, message us on [Discord](https://discord.gg/UgJyyxx7uc)!
+</Note>
+
+<Card title="Ollama" icon={<img src="/images/external/ollama/ollama-icon.png" alt="Ollama" />} iconType="image" href="https://ollama.com">
+    First class support for Ollama
+</Card>
+
+<Steps>
+  <Step title="Install the AgentOps SDK">
+    <CodeGroup>
+      ```bash pip 
+      pip install agentops ollama
+      ```
+      ```bash poetry
+      poetry add agentops ollama
+      ```
+    </CodeGroup>
+  </Step>
+  <Step title="Add 3 lines of code">
+    <CodeTooltip/>
+    <CodeGroup>
+      ```python python
+      import agentops
+      import ollama
+
+      agentops.init(<INSERT YOUR API KEY HERE>)
+      agentops.start_session()
+
+      ollama.pull("<MODEL NAME>")
+
+      response = ollama.chat(model='mistral',
+        messages=[{
+            'role': 'user',
+            'content': 'What are the benefits of using AgentOps for monitoring LLMs?',
+        }]
+      )
+      print(response['message']['content'])
+      ...
+      # End of program (e.g. main.py)
+      agentops.end_session("Success") # Success|Fail|Indeterminate
+      ```
+    </CodeGroup>
+    <EnvTooltip />
+      <CodeGroup>
+        ```python .env
+        # Alternatively, you can set the API key as an environment variable
+        AGENTOPS_API_KEY=<YOUR API KEY>
+        ```
+      </CodeGroup>
+      Read more about environment variables in [Advanced Configuration](/v1/usage/advanced-configuration)
+  </Step>
+  <Step title="Run your Agent">
+    Execute your program and visit [app.agentops.ai/drilldown](https://app.agentops.ai/drilldown) to observe your Agent! 🕵️
+    <Tip>
+      After your run, AgentOps prints a clickable url to console linking directly to your session in the Dashboard
+    </Tip>
+    <div/>
+  </Step>
+</Steps>
+
+## Full Examples
+
+<CodeGroup>
+  ```python basic completion
+  import ollama
+  import agentops
+
+  agentops.init(<INSERT YOUR API KEY HERE>)
+
+  ollama.pull("<MODEL NAME>")
+  response = ollama.chat(
+      model="<MODEL NAME>",
+      max_tokens=1024,
+      messages=[{
+          "role": "user",
+          "content": "Write a haiku about AI and humans working together"
+      }]
+  )
+
+  print(response['message']['content'])
+  agentops.end_session('Success')
+  ```
+
+  ```python streaming
+  import agentops
+  import ollama
+
+  async def main():
+      agentops.init(<INSERT YOUR API KEY HERE>)
+      ollama.pull("<MODEL NAME>")
+
+      stream = ollama.chat(
+        model="<MODEL NAME>",
+          messages=[{
+              'role': 'user',
+              'content': 'Write a haiku about monitoring AI agents',
+          }], 
+          stream=True
+      )
+
+      for chunk in stream:
+          print(chunk['message']['content'], end='')
+
+      agentops.end_session('Success')
+  ```
+
+  ```python conversation
+  import ollama
+  import agentops
+
+  agentops.init(<INSERT YOUR API KEY HERE>)
+  ollama.pull("<MODEL NAME>")
+
+  messages = [
+    {
+        'role': 'user',
+        'content': 'What is AgentOps?'
+    },
+    {
+        'role': 'assistant',
+        'content': 'AgentOps is a monitoring and observability platform for LLM applications.'
+    },
+    {
+        'role': 'user',
+        'content': 'Can you give me 3 key features?'
+    }
+]
+
+  response = ollama.chat(
+      model="<MODEL NAME>",
+      messages=messages
+  )
+  print(response['message']['content'])   
+  agentops.end_session('Success')
+  ```
+</CodeGroup>
+
+<script type="module" src="/scripts/github_stars.js"></script>
+<script type="module" src="/scripts/scroll-img-fadein-animation.js"></script>
+<script type="module" src="/scripts/button_heartbeat_animation.js"></script>
+<script type="css" src="/styles/styles.css"></script>