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[need help] blog update: ai agent blog #3169

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@LinaLam LinaLam commented Jan 25, 2025

  • updated with how to integrate for most the platforms

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fumedev bot commented Jan 25, 2025

Summary

  • Added integration guides for LLM observability with Dify, LlamaIndex, CrewAI, and LangChain
  • Reorganized comparison links under "Other Comparisons" sections for better structure
  • Added detailed code examples and configuration steps for integrating Helicone with each framework
  • Updated formatting and styling of framework comparisons to improve readability

🔍 Fume is reviewing this PR!

🔗 Track the review progress here:
https://app.fumedev.com/chat/e79ce617-1767-4cf9-885a-511c1a68c7ee


2. Set up environment variables

```
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Please specify the language for this code block by adding bash at the start

🔨 See the suggested fix
@@ -268,11 +268,7 @@
 | • **Scalability:** Useful for prototyping complex AI solutions and large datasets efficiently.                                     | • **Poor documentation:** often outdated or unclear, however, has a large active community for support.                           |
 | • **Integrations:** Has many integrations which requires more coding effort, but offers flexibility for custom models.             | • **Not suitable for production environments**: due to instability and frequent changes.                                          |
 
-### Integrating LLM Observability with LangChain
-
-1. Create an <a href="https://www.helicone.ai/signup" target="_blank" rel="noopener">Helicone</a> account, then generate a `write-only` API key.
-
-2. Set up environment variables
+3. Modify your LangChain OpenAI configuration to use Helicone:
 

export HELICONE_API_KEY=your_helicone_api_key


[![Click Here](https://fume.b-cdn.net/commit_changes.svg)](https://app.fumedev.com/commit/ad75e85a-be22-4e9b-b1da-c280637284df)
<sub>⚠️ Fume is an LLM-based tool and can make mistakes.</sub>
</details>


2. Set up environment variables

```bash
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For consistency with other sections, please use an f-string here instead of string concatenation: f'https://oai.helicone.ai/{HELICONE_API_KEY}/v1'

🔨 See the suggested fix
@@ -268,11 +268,8 @@
 | • **Scalability:** Useful for prototyping complex AI solutions and large datasets efficiently.                                     | • **Poor documentation:** often outdated or unclear, however, has a large active community for support.                           |
 | • **Integrations:** Has many integrations which requires more coding effort, but offers flexibility for custom models.             | • **Not suitable for production environments**: due to instability and frequent changes.                                          |
 
-### Integrating LLM Observability with LangChain
-
-1. Create an <a href="https://www.helicone.ai/signup" target="_blank" rel="noopener">Helicone</a> account, then generate a `write-only` API key.
-
-2. Set up environment variables
+- All LLM calls made by the agent will be automatically logged and monitored by Helicone. For Antrhopic's Claude, a similar approach can be used.
+- See <a href="https://docs.helicone.ai/integrations/openai/langchain" target="_blank" rel="noopener">OpenAI LangChain docs</a> or <a href="https://docs.helicone.ai/integrations/anthropic/langchain" target="_blank" rel="noopener">Anthropic LangChain docs</a> for details.
 

export HELICONE_API_KEY=your_helicone_api_key


[![Click Here](https://fume.b-cdn.net/commit_changes.svg)](https://app.fumedev.com/commit/addf876a-5058-4fb7-862a-d028ee758e61)
<sub>⚠️ Fume is an LLM-based tool and can make mistakes.</sub>
</details>


```javascript
const llm = new OpenAI({
modelName: "gpt-3.5-turbo",
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The OpenAI API configuration property should be 'model' instead of 'modelName'

🔨 See the suggested fix
@@ -268,11 +268,20 @@
 | • **Scalability:** Useful for prototyping complex AI solutions and large datasets efficiently.                                     | • **Poor documentation:** often outdated or unclear, however, has a large active community for support.                           |
 | • **Integrations:** Has many integrations which requires more coding effort, but offers flexibility for custom models.             | • **Not suitable for production environments**: due to instability and frequent changes.                                          |
 
-### Integrating LLM Observability with LangChain
-
-1. Create an <a href="https://www.helicone.ai/signup" target="_blank" rel="noopener">Helicone</a> account, then generate a `write-only` API key.
-
-2. Set up environment variables
+3. Modify your LangChain OpenAI configuration to use Helicone:
+
+const llm = new OpenAI({
+  model: "gpt-3.5-turbo",
+  configuration: {
+    basePath: "https://oai.helicone.ai/v1",
+    defaultHeaders: {
+      "Helicone-Auth": `Bearer ${process.env.HELICONE_API_KEY}`,
+    },
+  },
+});
+
+- All LLM calls made by the agent will be automatically logged and monitored by Helicone. For Antrhopic's Claude, a similar approach can be used.
+- See <a href="https://docs.helicone.ai/integrations/openai/langchain" target="_blank" rel="noopener">OpenAI LangChain docs</a> or <a href="https://docs.helicone.ai/integrations/anthropic/langchain" target="_blank" rel="noopener">Anthropic LangChain docs</a> for details.
 

export HELICONE_API_KEY=your_helicone_api_key


[![Click Here](https://fume.b-cdn.net/commit_changes.svg)](https://app.fumedev.com/commit/8a1aa6c3-6916-49d8-b514-632466fae10c)
<sub>⚠️ Fume is an LLM-based tool and can make mistakes.</sub>
</details>

configuration: {
basePath: "https://oai.helicone.ai/v1",
defaultHeaders: {
"Helicone-Auth": `Bearer ${process.env.HELICONE_API_KEY}`,
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Please use 'Helicone-Auth-Token' instead of 'Helicone-Auth' as the authentication header

🔨 See the suggested fix
@@ -215,9 +215,7 @@
 
 ### Integrating LLM Observability with CrewAI
 
-1. Create an <a href="https://www.helicone.ai/signup" target="_blank" rel="noopener">Helicone</a> account, then generate a `write-only` API key.
-
-2. Set up environment variables
+3. Modify your LangChain OpenAI configuration to use Helicone:
 
 ```bash
 import os
@@ -281,23 +279,8 @@
 3. Modify your LangChain OpenAI configuration to use Helicone:
 
 ```javascript
-const llm = new OpenAI({
-  modelName: "gpt-3.5-turbo",
-  configuration: {
-    basePath: "https://oai.helicone.ai/v1",
-    defaultHeaders: {
-      "Helicone-Auth": `Bearer ${process.env.HELICONE_API_KEY}`,
-    },
-  },
-});
-```
-
 - All LLM calls made by the agent will be automatically logged and monitored by Helicone. For Antrhopic's Claude, a similar approach can be used.
 - See <a href="https://docs.helicone.ai/integrations/openai/langchain" target="_blank" rel="noopener">OpenAI LangChain docs</a> or <a href="https://docs.helicone.ai/integrations/anthropic/langchain" target="_blank" rel="noopener">Anthropic LangChain docs</a> for details.
-
-### Other LangChain Comparisons:
-
-- **<a href="https://www.helicone.ai/blog/llamaindex-vs-langchain" rel="noopener" target="_blank">LangChain vs. LlamaIndex</a>**
 
 ---
 

Click Here
⚠️ Fume is an LLM-based tool and can make mistakes.

@@ -87,7 +87,15 @@ Dify AI is an open-source platform that simplifies the development of AI agents
| • **Strong data security**: Robust encryption and protection mechanisms to ensure data confidentiality and safety. | • **Complex data processing**: Constraints in handling intricate machine learning models or extensive computational tasks. |
| • **Seamless integration**: Connects with popular AI models and supports integration with external tools like Zapier, Make, etc. | • **Scalability**: While there are limitations when it comes to building highly complex or large-scale tasks, Dify is suitable for building most AI apps. |

**You might be interested in**: <a href="https://www.helicone.ai/blog/crewai-vs-dify-ai" rel="noopener" target="_blank">Dify vs. CrewAI</a>.
### Integrating LLM Observability with Dify
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Please add specific steps on how to configure the API Base in Dify's UI (where to find it, what value to enter) and include a verification step to ensure the integration is working correctly

🔨 See the suggested fix
@@ -91,7 +91,19 @@
 
 1. Create an <a href="https://www.helicone.ai/signup" target="_blank" rel="noopener">Helicone</a> account, then generate an API key.
 
-2. Configure API Base in Dify to use Helicone. See <a href="https://docs.helicone.ai/other-integrations/dify" target="_blank" rel="noopener">Dify Integration docs</a> for details.
+2. Configure API Base in Dify to use Helicone:
+   - Navigate to your Dify dashboard
+   - Go to "Settings" > "Model Providers"
+   - Select "OpenAI" or add it if not present
+   - In the "API Base" field, enter: `https://oai.helicone.ai`
+   - Add your Helicone API key to the "Authorization" header with format: `Bearer YOUR_HELICONE_API_KEY`
+   - Click "Save" to apply the changes
+
+3. Verify the integration:
+   - Create a test conversation in your Dify application
+   - Send a few messages to generate LLM calls
+   - Visit your Helicone dashboard
+   - Check the "Requests" section to confirm the calls are being logged
 
 ### Other Dify Comparisons:
 

Click Here
⚠️ Fume is an LLM-based tool and can make mistakes.

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fumedev bot commented Jan 25, 2025

Testing

  • Created and ran CrewAI integration test:

    • Environment variable setup works correctly
    • API URL format with auth token is valid
    • All tests passed
  • Unable to test LangChain and LlamaIndex integrations due to Python package installation restrictions.

Issues Found (through code review)

  • LangChain JavaScript config:
    • modelName property should be model
    • Helicone-Auth header should be Helicone-Auth-Token
  • API endpoint URLs need updating from helicone.ai to hconeapi.com
  • Dify integration lacks specific configuration steps, only links to docs

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