broken link fixes

langfuse · Oct 31, 2024 · f2de84f · f2de84f
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diff --git a/cookbook/integration_dspy.ipynb b/cookbook/integration_dspy.ipynb
@@ -17,7 +17,7 @@
         "\n",
         "Langfuse can help with running DSPy projects by providing a centralized observability platform for debugging and monitoring.\n",
         "\n",
-        "**Note**: This is a community contributed integration ([initial PR](https://github.com/stanfordnlp/dspy/pull/1186) by [@xucailiang](https://github.com/xucailiang)). DSPy documentation covering the integration can be found [here](https://dspy-docs.vercel.app/api/language_model_clients/langfuse). If you encounter issues or want to contribute to the integration, please open an issue or PR.\n",
+        "**Note**: This is a community contributed integration ([initial PR](https://github.com/stanfordnlp/dspy/pull/1186) by [@xucailiang](https://github.com/xucailiang)). DSPy documentation can be found [here](https://dspy-docs.vercel.app/intro/). If you encounter issues or want to contribute to the integration, please open an issue or PR.\n",
         "\n",
         "---\n",
         "\n",

diff --git a/pages/blog/langchain-integration.mdx b/pages/blog/langchain-integration.mdx
@@ -20,7 +20,7 @@ import GetStartedLangchainJsEnv from "@/components-mdx/get-started-langchain-js-
   authors={["maxdeichmann", "marcklingen"]}
 />
 
-For teams building their LLM app with Langchain, adopting Langfuse just got easier. We added a `CallbackHandler` to the Langfuse Python SDK that natively integrates with [Langchain Callbacks](https://python.langchain.com/docs/modules/callbacks/).
+For teams building their LLM app with Langchain, adopting Langfuse just got easier. We added a `CallbackHandler` to the Langfuse Python SDK that natively integrates with [Langchain Callbacks](https://python.langchain.com/docs/how_to/#callbacks).
 
 ## 🪢 + 🦜🔗 → 🤌
 

diff --git a/pages/docs/integrations/dspy.md b/pages/docs/integrations/dspy.md
@@ -9,7 +9,7 @@ This cookbook demonstrates how to use [DSPy](https://github.com/stanfordnlp/dspy
 
 Langfuse can help with running DSPy projects by providing a centralized observability platform for debugging and monitoring.
 
-**Note**: This is a community contributed integration ([initial PR](https://github.com/stanfordnlp/dspy/pull/1186) by [@xucailiang](https://github.com/xucailiang)). DSPy documentation covering the integration can be found [here](https://dspy-docs.vercel.app/api/language_model_clients/langfuse). If you encounter issues or want to contribute to the integration, please open an issue or PR.
+**Note**: This is a community contributed integration ([initial PR](https://github.com/stanfordnlp/dspy/pull/1186) by [@xucailiang](https://github.com/xucailiang)). DSPy documentation can be found [here](https://dspy-docs.vercel.app/intro/). If you encounter issues or want to contribute to the integration, please open an issue or PR.
 
 ---
 

diff --git a/pages/docs/integrations/langchain/tracing.mdx b/pages/docs/integrations/langchain/tracing.mdx
@@ -11,7 +11,7 @@ import GetStartedLangchainJsEnv from "@/components-mdx/get-started-langchain-js-
 
 # Observability & Tracing for Langchain (Python & JS/TS)
 
-[Langfuse Tracing](/docs/tracing) integrates with Langchain using Langchain Callbacks ([Python](https://python.langchain.com/docs/modules/callbacks/), [JS](https://js.langchain.com/docs/modules/callbacks/)). Thereby, the Langfuse SDK automatically creates a nested trace for every run of your Langchain applications. This allows you to log, analyze and debug your LangChain application.
+[Langfuse Tracing](/docs/tracing) integrates with Langchain using Langchain Callbacks ([Python](https://python.langchain.com/docs/how_to/#callbacks), [JS](https://js.langchain.com/docs/how_to/#callbacks)). Thereby, the Langfuse SDK automatically creates a nested trace for every run of your Langchain applications. This allows you to log, analyze and debug your LangChain application.
 
 <CloudflareVideo
   videoId="cb700aef1f55d21418955390d4b0d859"

diff --git a/pages/faq/all/ai-research-assistant-monitoring.mdx b/pages/faq/all/ai-research-assistant-monitoring.mdx
@@ -61,7 +61,7 @@ Utilize dashboards to visualize key performance metrics.
 - **Accuracy Metrics**: Track the correctness/accuracy scores of the AI's outputs.
 - **Usage Statistics**: Monitor how and when the AI assistant is used.
 
-Explore how to use [analytics dashboards](/docs/analytics/dashboards) in Langfuse.
+Explore how to use [analytics dashboards](/docs/analytics/overview) in Langfuse.
 
 ### 4. Testing and Evaluation
 

diff --git a/pages/faq/all/chatbot-analytics.mdx b/pages/faq/all/chatbot-analytics.mdx
@@ -42,7 +42,7 @@ Capture detailed logs of user conversations and system processes. This data is e
 - **Conversation Logs**: Record user inputs and chatbot responses.
 - **System Traces**: Monitor the internal processes, including API calls and database queries.
 
-Learn how to set up [logging and tracing](/docs/logging-and-tracing) with Langfuse.
+Learn how to set up [logging and tracing](/docs/tracing) with Langfuse.
 
 ### 2. Feedback Integration
 
@@ -61,7 +61,7 @@ Visualize key metrics and monitor the chatbot's performance over time.
 - **Engagement Metrics**: Track the number of interactions, session durations, and user retention rates.
 - **Performance Metrics**: Monitor response times and error rates.
 
-Explore how to [analyze](/docs/analytics-dashboards) your chatbot metrics in Langfuse.
+Explore how to [analyze](/docs/analytics/overview) your chatbot metrics in Langfuse.
 
 ### 4. Model Based Evaluations
 
@@ -110,7 +110,7 @@ Understand how users interact with your chatbot.
 - **Interaction Patterns**: Identify common user intents and needs.
 - **Drop-off Analysis**: Find out where users disengage.
 
-Learn more about [user behavior tracking](/docs/analytics/user-behavior).
+Learn more about [user behavior tracking](/docs/analytics/overview).
 
 ### 4. Integrations
 
@@ -119,7 +119,7 @@ Incorporate monitoring tools into your existing tech stack.
 - **SDKs and APIs**: Use provided tools to integrate quickly.
 - **PostHog**: Use the Langfuse PostHog [integration](/docs/analytics/posthog) to analyze your data in one place.
 
-Langfuse offers a range of [integrations and SDKs](/docs/integrations/get-started).
+Langfuse offers a range of [integrations and SDKs](/docs/integrations).
 
 ### 5. Scalability
 
@@ -128,7 +128,7 @@ Ensure your monitoring solution can handle growth.
 - **Performance Optimization**: Maintain efficiency as data volume increases.
 - **Distributed Systems Support**: Monitor chatbots deployed across multiple servers or regions.
 
-Langfuse is designed to [scale with your needs](/docs/scaling).
+Langfuse is designed to scale with your needs.
 
 
 ## Start Tracking your Chatbot with Langfuse

diff --git a/pages/guides/cookbook/integration_dspy.md b/pages/guides/cookbook/integration_dspy.md
@@ -9,7 +9,7 @@ This cookbook demonstrates how to use [DSPy](https://github.com/stanfordnlp/dspy
 
 Langfuse can help with running DSPy projects by providing a centralized observability platform for debugging and monitoring.
 
-**Note**: This is a community contributed integration ([initial PR](https://github.com/stanfordnlp/dspy/pull/1186) by [@xucailiang](https://github.com/xucailiang)). DSPy documentation covering the integration can be found [here](https://dspy-docs.vercel.app/api/language_model_clients/langfuse). If you encounter issues or want to contribute to the integration, please open an issue or PR.
+**Note**: This is a community contributed integration ([initial PR](https://github.com/stanfordnlp/dspy/pull/1186) by [@xucailiang](https://github.com/xucailiang)). DSPy documentation can be found [here](https://dspy-docs.vercel.app/intro/). If you encounter issues or want to contribute to the integration, please open an issue or PR.
 
 ---