Added changes to pattern match existing docs.

fern/docs.yml

@@ -61,6 +61,8 @@ navigation:
             path: ./pages/openllmetry/tracing/entities-traces.mdx
           - page: Tracking User Feedback
             path: ./pages/openllmetry/tracing/tracking-feedback.mdx
+          - page: Manually reporting calls to LLMs and Vector DBs
+            path: ./pages/openllmetry/tracing/manually-reporting-calls.mdx
           - page: Manual Implementations (Typescript / Javascript)
             path: ./pages/openllmetry/tracing/manual-implementations.mdx
           - page: Usage with Threads (Python)

fern/pages/documentation/prompt-management/fetching-prompts.mdx

@@ -12,8 +12,8 @@ To disable polling all together, set the `TRACELOOP_SYNC_ENABLED` environment va
 
 Make sure you’ve configured the SDK with the right environment and API Key. See the [SDK documentation](/docs/openllmetry/integrations/traceloop) for more information.
 
-<Callout intent="info">
-The SDK uses smart caching mechanisms to proide zero latency for fetching prompts.
+<Callout intent="note">
+The SDK uses smart caching mechanisms to provide zero latency for fetching prompts.
 </Callout>
 
 ## Get Prompt API
@@ -67,6 +67,6 @@ Then, you can retrieve it with in your code using `get_prompt`:
     </CodeBlock>
 </CodeBlocks>
 
-<Callout intent="info">
+<Callout intent="note">
 The returned variable `prompt_args` is compatible with the API used by the foundation models SDKs (OpenAI, Anthropic, etc.) which means you should directly plug in the response to the appropriate API call.
 </Callout>

fern/pages/documentation/prompt-management/prompt-registry.mdx

@@ -15,7 +15,7 @@ The prompt configuration is composed of two parts:
 - The prompt template (system and/or user prompts)
 - The model configuration (`temperature`, `top_p`, etc.)
 
-<Callout intent="info">
+<Callout intent="tip">
 Your prompt template can include variables. Variables are defined according to the syntax of the parser specified. For example, if using `jinjia2` the syntax will be `{{ variable_name }}`. You can then pass variable values to the SDK when calling `get_prompt`. See the example on the [SDK Usage](/fetching-prompts) section.
 </Callout>
 
@@ -49,7 +49,7 @@ Choose the `Deploy` Tab to navigate to the deployments page for your prompt.
 
 Here, you can see all recent prompt versions, and which environments they are deployed to. Simply click on the `Deploy` button to deploy a prompt version to an environment. Similarly, click `Rollback` to revert to a previous prompt version for a specific environment.
 
-<Callout intent="info">
+<Callout intent="note">
 As a safeguard, you cannot deploy a prompt to the `Staging` environment before first deploying it to `Development`. Similarly, you cannot deploy to `Production` without first deploying to `Staging`.
 </Callout>
 
@@ -59,6 +59,6 @@ To fetch prompts from a specific environment, you must supply that environment
 
 If you want to make changes to your prompt after deployment, simply create a new version by clicking on the `New Version` button. New versions will be created in `Draft Mode`.
 
-<Callout intent="warn">
+<Callout intent="warning">
 If you change the names of variables or add/remove existing variables, you will be required to create a new prompt.
 </Callout>

fern/pages/openllmetry/contribute/gen-ai.mdx

@@ -11,7 +11,7 @@ This is a work in progress, and we welcome your feedback and contributions!
 
 ## Definitions
 
-## LLM Foundation Models
+### LLM Foundation Models
 
 | Field                        | Description                                                                                      |
 |------------------------------|--------------------------------------------------------------------------------------------------|
@@ -34,14 +34,14 @@ This is a work in progress, and we welcome your feedback and contributions!
 | `llm.user`                     | The user ID sent with the request                                                              |
 | `llm.headers`                  | The headers used for the request                                                               |
 
-## Vector DBs
+### Vector DBs
 
 | Field                    | Description                                                    |
 |--------------------------|----------------------------------------------------------------|
 | `vector_db.vendor`         | The vendor of the Vector DB (e.g. Chroma, Pinecone, etc.)    |
 | `vector_db.query.top_k`    | The top k used for the query                                 |
 
-## LLM Frameworks
+### LLM Frameworks
 
 | Field                           | Description                                                                                       |
 |---------------------------------|---------------------------------------------------------------------------------------------------|

fern/pages/openllmetry/contribute/overview.mdx

@@ -1,4 +1,6 @@
-<h1>We welcome any contributions to OpenLLMetry, big or small.</h1>
+---
+excerpt: We welcome any contributions to OpenLLMetry, big or small
+---
 
 ## Community
 

fern/pages/openllmetry/integrations/azure-insights.mdx

@@ -10,15 +10,15 @@ Review how to setup [OpenTelemetry with Python in Azure Application Insights](ht
 ![integrations-azure](https://fern-image-hosting.s3.amazonaws.com/traceloop/integrations-azure.png)
 </Frame>
 
-## Provision an Application Insights instance in the [Azure portal](https://portal.azure.com/).
+1. Provision an Application Insights instance in the [Azure portal](https://portal.azure.com/).
 
-## Get your Connection String from the instance - [details here](https://learn.microsoft.com/en-us/azure/azure-monitor/app/sdk-connection-string?tabs=python).
+2. Get your Connection String from the instance - [details here](https://learn.microsoft.com/en-us/azure/azure-monitor/app/sdk-connection-string?tabs=python).
 
-## Install required packages
+3. Install required packages
 
 `pip install azure-monitor-opentelemetry-exporter traceloop-sdk openai`
 
-## Example implementation
+4. Example implementation
 
 ```python
 import os

fern/pages/openllmetry/integrations/dynatrace.mdx

@@ -6,19 +6,12 @@ excerpt: LLM Observability with Dynatrace and OpenLLMetry
 ![integrations-dynatrace](https://fern-image-hosting.s3.amazonaws.com/traceloop/integrations-dynatrace.png)
 </Frame>
 
-
-## Initialize Dynatrace OpenTelemetry Integration
-
 Analyze all collected LLM traces within Dynatrace by using the native OpenTelemetry ingest endpoint of your Dynatrace environment.
 
-## Generate Access Token for Dynatrace Environment
-
 Go to your Dynatrace environment and create a new access token under **Manage Access Tokens**.
 
 The access token needs the following permission scopes that allow the ingest of OpenTelemetry spans, metrics and logs (`openTelemetryTrace.ingest`, `metrics.ingest`, `logs.ingest`).
 
-## Set Environment Variables for Dynatrace Integration
-
 Set `TRACELOOP_BASE_URL` environment variable to the URL of your Dynatrace OpenTelemetry ingest endpoint.
 
 ```
@@ -31,7 +24,4 @@ Set the `TRACELOOP_HEADERS` environment variable to include your previously crea
 TRACELOOP_HEADERS=Authorization=Api-Token%20<YOUR_ACCESS_TOKEN>
 ```
 
-
-You're all set! 
-
-All the exported spans along with their span attributes will show up within the Dynatrace trace view.
+You're all set! All the exported spans along with their span attributes will show up within the Dynatrace trace view.

fern/pages/openllmetry/integrations/grafana.mdx

@@ -21,9 +21,8 @@ Note also the **Stack ID** value.
 You can find it in the URL `https://grafana.com/orgs/<Your Org Name>/stacks/<Stack ID>`.
 
 ## With Grafana Agent
-Make sure you have an agent installed and running in your cluster. The host to target your traces is constructed is the hostname of the `URL` noted above, without the `https://` and the trailing `/tempo`.
 
-### Update Agent Configuration
+Make sure you have an agent installed and running in your cluster. The host to target your traces is constructed is the hostname of the `URL` noted above, without the `https://` and the trailing `/tempo`.
 
 Add this to the configuration of your agent:
 
@@ -42,12 +41,10 @@ traces:
             grpc:
 ```
 
-<Callout intent="warn">
+<Callout intent="warning">
 Note the endpoint. The URL you need to use is without `https` and the trailing `/`. So `https://tempo-us-central1.grafana.net/tempo` should be used as `tempo-us-central1.grafana.net:443`.
 </Callout>
 
-### Set Environmental Variable
-
 Set this as an environment variable in your app:
 
 ```
@@ -56,12 +53,10 @@ TRACELOOP_BASE_URL=http://<grafana-agent-hostname>:4318
 
 ## Without Grana Agent
 
-<Callout intent="info">
+<Callout intent="note">
 Grafana cloud currently only supports sending traces to some of its regions. Before you begin, [check out this list](https://grafana.com/docs/grafana-cloud/monitor-infrastructure/otlp/send-data-otlp/) and make sure your region is supported.
 </Callout>
 
-### Get your encoded User ID and API Key
-
 In a terminal, type:
 
 ```
@@ -70,12 +65,8 @@ echo -n "<your stack id>:<your api key>" | base64
 
 The result which is a base64 encoding of your user id and api key.
 
-### Get your URL
-
 The URL you’ll use as the destination for the traces depends on your region/zone. For example, for AWS US Central this will be `prod-us-central-0`. See [here](https://grafana.com/docs/grafana-cloud/monitor-infrastructure/otlp/send-data-otlp/#before-you-begin) for the names of the zones you should use below.
 
-### Set your environmental variables
-
 Finally, you can set the following environment variables when running your app with Traceloop SDK installed:
 
 ```

fern/pages/openllmetry/integrations/instana.mdx

@@ -8,7 +8,6 @@ excerpt: LLM Observability with Instana and OpenLLMetry
 
 With Instana, you can export directly to an Instana Agent in your cluster. The Instana Agent will report back the tracing and metrics to the Instana Backend and display them on the Instana UI.
 
-
 ## Edit the agent config file
 
 After an Instana OS agent is installed, edit the agent config file `configuration.yaml` under the `/opt/instana/agent/etc/instana folder`.

fern/pages/openllmetry/integrations/traceloop.mdx

@@ -12,20 +12,19 @@ excerpt: LLM Observability with Traceloop
 
 On Traceloop, API keys can be generated from the [Traceloop Dashboard](https://app.traceloop.com/settings/api-keys), for each of the three supported environments (Development, Staging, Production).
 
-
-### Go to [Traceloop Environments Management](https://app.traceloop.com/settings/api-keys)
+Go to [Traceloop Environments Management](https://app.traceloop.com/settings/api-keys)
 
 You can also reach here by clicking on **Environments** on the left-hand navigation bar.
 
-### Click on **Generate API Key**
+Click on **Generate API Key**
 
-### Click **Copy Key** to copy the API key
+Click **Copy Key** to copy the API key
 
 <Callout intent="info">
 API Keys are only displayed once, at the time of their creation and are not stored anywhere. If you lose your API key, you will need to revoke the old one and generate a new one.
 </Callout>
 
-### Set the API key as an environment variable named `TRACELOOP_API_KEY`.
+Set the API key as an environment variable named `TRACELOOP_API_KEY`.
 
 Done! You’ll get instant visibility into everything that’s happening with your LLM. If you’re calling a vector DB, or any other external service or database, you’ll also see it in the Traceloop dashboard.
 

fern/pages/openllmetry/intro/what-is-llmetry.mdx

@@ -4,7 +4,7 @@
 
 OpenLLMetry is an open source project that allows you to easily start monitoring and debugging the execution of your LLM app. Tracing is done in a non-intrusive way, built on top of OpenTelemetry. You can choose to export the traces to Traceloop, or to your existing observability stack.
 
-<Callout intent="info">
+<Callout intent="tip">
 You can use OpenLLMetry whether you use a framework like LangChain, or directly interact with a foundation model API.
 </Callout>
 

fern/pages/openllmetry/privacy/prompts-completions-embeddings.mdx

@@ -52,7 +52,6 @@ You can decide to selectively enable prompt logging for specific workflows, task
 
 You can decide to selectively enable or disable prompt logging for specific users or workflows.
 
-
 ### Using the Traceloop Platform
 
 We have an API to enable content tracing for specific users, as defined by [association entities](/docs/openllmetry/tracing/associating-entities-with-traces). See the [Traceloop API documentation](/dashboard-api/endpoints) for more information.

fern/pages/openllmetry/quickstart/go.mdx

@@ -105,7 +105,7 @@ For Traceloop, read on. For other options, see [Exporting](/docs/openllmetry/int
 
 Go to [Traceloop](https://app.traceloop.com/), and create a new account. Then, click on **Environments** on the left-hand navigation bar. Or go to directly to https://app.traceloop.com/settings/api-keys. Click **Generate API Key** to generate an API key for the development environment and click **Copy API Key** to copy it over.
 
-<Callout intent="warn">
+<Callout intent="warning">
 Make sure to copy it as it won’t be shown again.
 </Callout>
 

fern/pages/openllmetry/quickstart/next.mdx

@@ -58,7 +58,7 @@ Run the following command in your terminal:
   });
   ```
 
-  <Callout intent="warn">
+  <Callout intent="warning">
   Make sure to explictly pass any LLM modules you want to instrument as otherwise auto-instrumentation won’t work on Next.js. Also make sure to set `disableBatch` to `true`.
   </Callout>
 
@@ -75,7 +75,7 @@ Run the following command in your terminal:
   module.exports = nextConfig;
   ```
 
-  <Callout intent="info">
+  <Callout intent="tip">
   See official Next.js [OpenTelemetry docs](https://nextjs.org/docs/pages/building-your-application/optimizing/open-telemetry) for more information.
   </Callout>
 
@@ -141,7 +141,7 @@ traceloop.initialize({
 });
 ```
 
-<Callout intent="info">
+<Callout intent="tip">
 See official Next.js [OpenTelemetry docs](https://nextjs.org/docs/pages/building-your-application/optimizing/open-telemetry) for more information.
 </Callout>
 
@@ -157,7 +157,7 @@ We have a set of [methods and decorators](/docs/openllmetry/tracing/workflows-ta
 
 We also have compatible Typescript decorators for class methods which are more convenient.
 
-<Callout intent="info">
+<Callout intent="note">
 If you’re using an LLM framework like Haystack, Langchain or LlamaIndex - we’ll do that for you. No need to add any annotations to your code.
 </Callout>
 
@@ -195,12 +195,15 @@ For Traceloop, read on. For other options, see [Exporting](/docs/openllmetry/int
 
 Go to [Traceloop](https://app.traceloop.com/), and create a new account. Then, click on **Environments** on the left-hand navigation bar. Or go to directly to https://app.traceloop.com/settings/api-keys. Click **Generate API Key** to generate an API key for the development environment and click **Copy API Key** to copy it over.
 
-<Callout intent="warn">
+<Callout intent="warning">
 Make sure to copy it as it won’t be shown again.
 </Callout>
 
-Set the copied Traceloop’s API key as an environment variable in your app named `TRACELOOP_API_KEY`.
-
 <Frame>
 ![openllmetry-next-2](https://fern-image-hosting.s3.amazonaws.com/traceloop/openllmetry-next-2.png)
-</Frame>
+</Frame>
+
+Set the copied Traceloop’s API key as an environment variable in your app named `TRACELOOP_API_KEY`.
+
+You're all set! You’ll get instant visibility into everything that’s happening with your LLM. If you’re calling a vector DB, or any other external service or database, you’ll also see it in the Traceloop dashboard.
+

fern/pages/openllmetry/quickstart/node.mdx

@@ -2,7 +2,7 @@
 excerpt: Install OpenLLMetry for Node.js by following these 3 easy steps and get instant monitoring.
 ---
 
-<Callout intent="info">
+<Callout intent="note">
 If you’re on Next.js, follow the [Next.js guide](/next).
 </Callout>
 
@@ -35,7 +35,7 @@ import * as traceloop from "@traceloop/node-server-sdk";
 traceloop.initialize();
 ```
 
-<Callout intent="info">
+<Callout intent="warning">
 Because of the way Javascript works, you must import the Traceloop SDK before importing any LLM module like OpenAI.
 </Callout>
 
@@ -57,7 +57,7 @@ We have a set of [methods and decorators](/docs/openllmetry/tracing/workflows-ta
 
 We also have compatible Typescript decorators for class methods which are more convenient.
 
-<Callout intent="info">
+<Callout intent="launch">
 If you’re using an LLM framework like Haystack, Langchain or LlamaIndex - we’ll do that for you. No need to add any annotations to your code.
 </Callout>
 
@@ -95,7 +95,7 @@ For Traceloop, read on. For other options, see [Exporting](/docs/openllmetry/int
 
 Go to [Traceloop](https://app.traceloop.com/), and create a new account. Then, click on **Environments** on the left-hand navigation bar. Or go to directly to https://app.traceloop.com/settings/api-keys. Click **Generate API Key** to generate an API key for the development environment and click **Copy API Key** to copy it over.
 
-<Callout intent="warn">
+<Callout intent="warning">
 Make sure to copy it as it won’t be shown again.
 </Callout>
 

fern/pages/openllmetry/quickstart/python.mdx

@@ -45,7 +45,7 @@ If you have complex workflows or chains, you can annotate them to get a better u
 
 We have a set of [decorators](/docs/openllmetry/tracing/workflows-tasks-agents-and-tools) to make this easier. Assume you have a function that renders a prompt and calls an LLM, simply add `@workflow` (or for asynchronous methods - `@aworkflow`).
 
-<Callout intent="info">
+<Callout intent="note">
 If you’re using an LLM framework like Haystack, Langchain or LlamaIndex - we’ll do that for you. No need to add any annotations to your code.
 </Callout>
 
@@ -71,7 +71,7 @@ For Traceloop, read on. For other options, see [Exporting](/docs/openllmetry/int
 
 Go to [Traceloop](https://app.traceloop.com/), and create a new account. Then, click on **Environments** on the left-hand navigation bar. Or go to directly to https://app.traceloop.com/settings/api-keys. Click **Generate API Key** to generate an API key for the developement environment and click **Copy API Key** to copy it over.
 
-<Callout intent="warn">
+<Callout intent="warning">
 Make sure to copy it as it won’t be shown again.
 </Callout>
 

fern/pages/openllmetry/quickstart/ruby.mdx

@@ -2,7 +2,7 @@
 excerpt: Install OpenLLMetry for Ruby by following these 3 easy steps and get instant monitoring.
 ---
 
-<Callout intent="info">
+<Callout intent="note">
 This is still in beta. Give us feedback at [[email protected]](mailto:[email protected])
 </Callout>
 
@@ -31,7 +31,7 @@ require "traceloop/sdk"
 traceloop = Traceloop::SDK::Traceloop.new
 ```
 
-<Callout intent="info">
+<Callout intent="tip">
 If you’re using Rails, this needs to be in `config/initializers/traceloop.rb`
 </Callout>
 
@@ -77,7 +77,7 @@ For Traceloop, read on. For other options, see [Exporting](/docs/openllmetry/int
 
 Go to [Traceloop](https://app.traceloop.com/), and create a new account. Then, click on **Environments** on the left-hand navigation bar. Or go to directly to https://app.traceloop.com/settings/api-keys. Click **Generate API Key** to generate an API key for the development environment and click **Copy API Key** to copy it over.
 
-<Callout intent="warn">
+<Callout intent="warning">
 Make sure to copy it as it won’t be shown again.
 </Callout>