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[need help] blog update: ai agent blog #3169
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LinaLam
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Jan 25, 2025
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- updated with how to integrate for most the platforms
The latest updates on your projects. Learn more about Vercel for Git ↗︎
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Summary
🔍 Fume is reviewing this PR! 🔗 Track the review progress here: |
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2. Set up environment variables | ||
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``` |
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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 | • **Poor documentation:** often outdated or unclear, however, has a large active community for support.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
[](https://app.fumedev.com/commit/ad75e85a-be22-4e9b-b1da-c280637284df)
<sub>⚠️ Fume is an LLM-based tool and can make mistakes.</sub>
</details>
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2. Set up environment variables | ||
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```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 | • **Poor documentation:** often outdated or unclear, however, has a large active community for support.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
[](https://app.fumedev.com/commit/addf876a-5058-4fb7-862a-d028ee758e61)
<sub>⚠️ Fume is an LLM-based tool and can make mistakes.</sub>
</details>
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```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
[](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>**
---
@@ -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. | | |||
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**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:
Testing
Issues Found (through code review)
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