forked from phoenix/litellm-mirror
Merge pull request #5260 from BerriAI/google_ai_studio_pass_through
Pass-through endpoints for Gemini - Google AI Studio
This commit is contained in:
commit
ff6ff133ee
9 changed files with 479 additions and 31 deletions
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docs/my-website/docs/pass_through/google_ai_studio.md
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docs/my-website/docs/pass_through/google_ai_studio.md
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@ -0,0 +1,223 @@
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# Google AI Studio (Pass-Through)
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Pass-through endpoints for Google AI Studio - call provider-specific endpoint, in native format (no translation).
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Just replace `https://generativelanguage.googleapis.com` with `LITELLM_PROXY_BASE_URL/gemini` 🚀
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#### **Example Usage**
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```bash
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http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=sk-anything' \
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-H 'Content-Type: application/json' \
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-d '{
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"contents": [{
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"parts":[{
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"text": "The quick brown fox jumps over the lazy dog."
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}]
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}]
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}'
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```
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Supports **ALL** Google AI Studio Endpoints (including streaming).
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[**See All Google AI Studio Endpoints**](https://ai.google.dev/api)
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## Quick Start
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Let's call the Gemini [`/countTokens` endpoint](https://ai.google.dev/api/tokens#method:-models.counttokens)
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1. Add Gemini API Key to your environment
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```bash
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export GEMINI_API_KEY=""
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```
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2. Start LiteLLM Proxy
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```bash
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litellm
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# RUNNING on http://0.0.0.0:4000
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```
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3. Test it!
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Let's call the Google AI Studio token counting endpoint
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```bash
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http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=anything' \
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-H 'Content-Type: application/json' \
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-d '{
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"contents": [{
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"parts":[{
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"text": "The quick brown fox jumps over the lazy dog."
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}]
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}]
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}'
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```
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## Examples
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Anything after `http://0.0.0.0:4000/gemini` is treated as a provider-specific route, and handled accordingly.
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Key Changes:
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| **Original Endpoint** | **Replace With** |
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|------------------------------------------------------|-----------------------------------|
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| `https://generativelanguage.googleapis.com` | `http://0.0.0.0:4000/gemini` (LITELLM_PROXY_BASE_URL="http://0.0.0.0:4000") |
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| `key=$GOOGLE_API_KEY` | `key=anything` (use `key=LITELLM_VIRTUAL_KEY` if Virtual Keys are setup on proxy) |
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### **Example 1: Counting tokens**
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#### LiteLLM Proxy Call
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```bash
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curl http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=anything \
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-H 'Content-Type: application/json' \
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-X POST \
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-d '{
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"contents": [{
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"parts":[{
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"text": "The quick brown fox jumps over the lazy dog."
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}],
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}],
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}'
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```
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#### Direct Google AI Studio Call
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```bash
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curl https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:countTokens?key=$GOOGLE_API_KEY \
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-H 'Content-Type: application/json' \
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-X POST \
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-d '{
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"contents": [{
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"parts":[{
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"text": "The quick brown fox jumps over the lazy dog."
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}],
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}],
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}'
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```
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### **Example 2: Generate content**
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#### LiteLLM Proxy Call
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```bash
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curl "http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:generateContent?key=anything" \
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-H 'Content-Type: application/json' \
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-X POST \
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-d '{
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"contents": [{
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"parts":[{"text": "Write a story about a magic backpack."}]
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}]
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}' 2> /dev/null
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```
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#### Direct Google AI Studio Call
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```bash
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curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent?key=$GOOGLE_API_KEY" \
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-H 'Content-Type: application/json' \
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-X POST \
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-d '{
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"contents": [{
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"parts":[{"text": "Write a story about a magic backpack."}]
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}]
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}' 2> /dev/null
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```
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### **Example 3: Caching**
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```bash
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curl -X POST "http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash-001:generateContent?key=anything" \
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-H 'Content-Type: application/json' \
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-d '{
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"contents": [
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{
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"parts":[{
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"text": "Please summarize this transcript"
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}],
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"role": "user"
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},
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],
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"cachedContent": "'$CACHE_NAME'"
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}'
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```
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#### Direct Google AI Studio Call
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```bash
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curl -X POST "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-001:generateContent?key=$GOOGLE_API_KEY" \
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-H 'Content-Type: application/json' \
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-d '{
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"contents": [
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{
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"parts":[{
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"text": "Please summarize this transcript"
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}],
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"role": "user"
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},
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],
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"cachedContent": "'$CACHE_NAME'"
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}'
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```
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## Advanced - Use with Virtual Keys
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Pre-requisites
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- [Setup proxy with DB](../proxy/virtual_keys.md#setup)
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Use this, to avoid giving developers the raw Google AI Studio key, but still letting them use Google AI Studio endpoints.
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### Usage
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1. Setup environment
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```bash
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export DATABASE_URL=""
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export LITELLM_MASTER_KEY=""
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export GEMINI_API_KEY=""
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```
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```bash
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litellm
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# RUNNING on http://0.0.0.0:4000
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```
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2. Generate virtual key
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```bash
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curl -X POST 'http://0.0.0.0:4000/key/generate' \
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-H 'Authorization: Bearer sk-1234' \
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-H 'Content-Type: application/json' \
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-d '{}'
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```
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Expected Response
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```bash
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{
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...
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"key": "sk-1234ewknldferwedojwojw"
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}
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```
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3. Test it!
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```bash
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http://0.0.0.0:4000/gemini/v1beta/models/gemini-1.5-flash:countTokens?key=sk-1234ewknldferwedojwojw' \
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-H 'Content-Type: application/json' \
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-d '{
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"contents": [{
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"parts":[{
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"text": "The quick brown fox jumps over the lazy dog."
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}]
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}]
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}'
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```
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@ -192,7 +192,8 @@ const sidebars = {
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"batches",
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"fine_tuning",
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"anthropic_completion",
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"vertex_ai"
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"pass_through/vertex_ai",
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"pass_through/google_ai_studio"
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],
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},
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"scheduler",
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|
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@ -412,7 +412,7 @@ def get_replicate_completion_pricing(completion_response=None, total_time=0.0):
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def _select_model_name_for_cost_calc(
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model: Optional[str],
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completion_response: Union[BaseModel, dict],
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completion_response: Union[BaseModel, dict, str],
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base_model: Optional[str] = None,
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custom_pricing: Optional[bool] = None,
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) -> Optional[str]:
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@ -428,7 +428,12 @@ def _select_model_name_for_cost_calc(
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if base_model is not None:
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return base_model
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return_model = model or completion_response.get("model", "") # type: ignore
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return_model = model
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if isinstance(completion_response, str):
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return return_model
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elif return_model is None:
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return_model = completion_response.get("model", "") # type: ignore
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if hasattr(completion_response, "_hidden_params"):
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if (
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completion_response._hidden_params.get("model", None) is not None
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|
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@ -274,6 +274,7 @@ class Logging:
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headers = {}
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data = additional_args.get("complete_input_dict", {})
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api_base = str(additional_args.get("api_base", ""))
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query_params = additional_args.get("query_params", {})
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if "key=" in api_base:
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# Find the position of "key=" in the string
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key_index = api_base.find("key=") + 4
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@ -2362,7 +2363,7 @@ def get_standard_logging_object_payload(
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return payload
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except Exception as e:
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verbose_logger.error(
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verbose_logger.exception(
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"Error creating standard logging object - {}".format(str(e))
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)
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return None
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|
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@ -3,7 +3,7 @@ import asyncio
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import json
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import traceback
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from base64 import b64encode
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from typing import List, Optional
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from typing import AsyncIterable, List, Optional
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import httpx
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from fastapi import (
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|
@ -267,12 +267,25 @@ def forward_headers_from_request(
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return headers
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def get_response_headers(headers: httpx.Headers) -> dict:
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excluded_headers = {"transfer-encoding", "content-encoding"}
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return_headers = {
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key: value
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for key, value in headers.items()
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if key.lower() not in excluded_headers
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}
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return return_headers
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async def pass_through_request(
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request: Request,
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target: str,
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custom_headers: dict,
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user_api_key_dict: UserAPIKeyAuth,
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forward_headers: Optional[bool] = False,
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query_params: Optional[dict] = None,
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stream: Optional[bool] = None,
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):
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try:
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import time
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@ -291,7 +304,7 @@ async def pass_through_request(
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body_str = request_body.decode()
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try:
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_parsed_body = ast.literal_eval(body_str)
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except:
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except Exception:
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_parsed_body = json.loads(body_str)
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verbose_proxy_logger.debug(
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@ -308,23 +321,9 @@ async def pass_through_request(
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)
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async_client = httpx.AsyncClient()
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response = await async_client.request(
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method=request.method,
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url=url,
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headers=headers,
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params=request.query_params,
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json=_parsed_body,
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)
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if response.status_code >= 300:
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raise HTTPException(status_code=response.status_code, detail=response.text)
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content = await response.aread()
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## LOG SUCCESS
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start_time = time.time()
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end_time = time.time()
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# create logging object
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start_time = time.time()
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logging_obj = Logging(
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model="unknown",
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messages=[{"role": "user", "content": "no-message-pass-through-endpoint"}],
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|
@ -334,6 +333,7 @@ async def pass_through_request(
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litellm_call_id=str(uuid.uuid4()),
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function_id="1245",
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)
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# done for supporting 'parallel_request_limiter.py' with pass-through endpoints
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kwargs = {
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"litellm_params": {
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@ -354,6 +354,81 @@ async def pass_through_request(
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call_type="pass_through_endpoint",
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)
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# combine url with query params for logging
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requested_query_params = query_params or request.query_params.__dict__
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requested_query_params_str = "&".join(
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f"{k}={v}" for k, v in requested_query_params.items()
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)
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if "?" in str(url):
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logging_url = str(url) + "&" + requested_query_params_str
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else:
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logging_url = str(url) + "?" + requested_query_params_str
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logging_obj.pre_call(
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input=[{"role": "user", "content": "no-message-pass-through-endpoint"}],
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api_key="",
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additional_args={
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"complete_input_dict": _parsed_body,
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"api_base": logging_url,
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"headers": headers,
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},
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)
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if stream:
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req = async_client.build_request(
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"POST",
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url,
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json=_parsed_body,
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params=requested_query_params,
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headers=headers,
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)
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response = await async_client.send(req, stream=stream)
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# Create an async generator to yield the response content
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async def stream_response() -> AsyncIterable[bytes]:
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async for chunk in response.aiter_bytes():
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yield chunk
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return StreamingResponse(
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stream_response(),
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headers=get_response_headers(response.headers),
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status_code=response.status_code,
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)
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response = await async_client.request(
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method=request.method,
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url=url,
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headers=headers,
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params=requested_query_params,
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json=_parsed_body,
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)
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if (
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response.headers.get("content-type") is not None
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and response.headers["content-type"] == "text/event-stream"
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):
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# streaming response
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# Create an async generator to yield the response content
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async def stream_response() -> AsyncIterable[bytes]:
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async for chunk in response.aiter_bytes():
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yield chunk
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return StreamingResponse(
|
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stream_response(),
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headers=get_response_headers(response.headers),
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status_code=response.status_code,
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)
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if response.status_code >= 300:
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raise HTTPException(status_code=response.status_code, detail=response.text)
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content = await response.aread()
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## LOG SUCCESS
|
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end_time = time.time()
|
||||
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await logging_obj.async_success_handler(
|
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result="",
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||||
start_time=start_time,
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||||
|
@ -361,17 +436,10 @@ async def pass_through_request(
|
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cache_hit=False,
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)
|
||||
|
||||
excluded_headers = {"transfer-encoding", "content-encoding"}
|
||||
headers = {
|
||||
key: value
|
||||
for key, value in response.headers.items()
|
||||
if key.lower() not in excluded_headers
|
||||
}
|
||||
|
||||
return Response(
|
||||
content=content,
|
||||
status_code=response.status_code,
|
||||
headers=headers,
|
||||
headers=get_response_headers(response.headers),
|
||||
)
|
||||
except Exception as e:
|
||||
verbose_proxy_logger.exception(
|
||||
|
@ -431,17 +499,23 @@ def create_pass_through_route(
|
|||
except Exception:
|
||||
verbose_proxy_logger.debug("Defaulting to target being a url.")
|
||||
|
||||
async def endpoint_func(
|
||||
async def endpoint_func( # type: ignore
|
||||
request: Request,
|
||||
fastapi_response: Response,
|
||||
user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
|
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query_params: Optional[dict] = None,
|
||||
stream: Optional[
|
||||
bool
|
||||
] = None, # if pass-through endpoint is a streaming request
|
||||
):
|
||||
return await pass_through_request(
|
||||
return await pass_through_request( # type: ignore
|
||||
request=request,
|
||||
target=target,
|
||||
custom_headers=custom_headers or {},
|
||||
user_api_key_dict=user_api_key_dict,
|
||||
forward_headers=_forward_headers,
|
||||
query_params=query_params,
|
||||
stream=stream,
|
||||
)
|
||||
|
||||
return endpoint_func
|
||||
|
|
|
@ -230,6 +230,9 @@ from litellm.proxy.utils import (
|
|||
send_email,
|
||||
update_spend,
|
||||
)
|
||||
from litellm.proxy.vertex_ai_endpoints.google_ai_studio_endpoints import (
|
||||
router as gemini_router,
|
||||
)
|
||||
from litellm.proxy.vertex_ai_endpoints.vertex_endpoints import router as vertex_router
|
||||
from litellm.proxy.vertex_ai_endpoints.vertex_endpoints import set_default_vertex_config
|
||||
from litellm.router import (
|
||||
|
@ -9734,6 +9737,7 @@ def cleanup_router_config_variables():
|
|||
app.include_router(router)
|
||||
app.include_router(fine_tuning_router)
|
||||
app.include_router(vertex_router)
|
||||
app.include_router(gemini_router)
|
||||
app.include_router(pass_through_router)
|
||||
app.include_router(health_router)
|
||||
app.include_router(key_management_router)
|
||||
|
|
|
@ -3,3 +3,94 @@ What is this?
|
|||
|
||||
Google AI Studio Pass-Through Endpoints
|
||||
"""
|
||||
|
||||
"""
|
||||
1. Create pass-through endpoints for any LITELLM_BASE_URL/gemini/<endpoint> map to https://generativelanguage.googleapis.com/<endpoint>
|
||||
"""
|
||||
|
||||
import ast
|
||||
import asyncio
|
||||
import traceback
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from typing import List, Optional
|
||||
from urllib.parse import urlencode
|
||||
|
||||
import fastapi
|
||||
import httpx
|
||||
from fastapi import (
|
||||
APIRouter,
|
||||
Depends,
|
||||
File,
|
||||
Form,
|
||||
Header,
|
||||
HTTPException,
|
||||
Request,
|
||||
Response,
|
||||
UploadFile,
|
||||
status,
|
||||
)
|
||||
from starlette.datastructures import QueryParams
|
||||
|
||||
import litellm
|
||||
from litellm._logging import verbose_proxy_logger
|
||||
from litellm.batches.main import FileObject
|
||||
from litellm.fine_tuning.main import vertex_fine_tuning_apis_instance
|
||||
from litellm.proxy._types import *
|
||||
from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
|
||||
from litellm.proxy.pass_through_endpoints.pass_through_endpoints import (
|
||||
create_pass_through_route,
|
||||
)
|
||||
|
||||
router = APIRouter()
|
||||
default_vertex_config = None
|
||||
|
||||
|
||||
@router.api_route("/gemini/{endpoint:path}", methods=["GET", "POST", "PUT", "DELETE"])
|
||||
async def gemini_proxy_route(
|
||||
endpoint: str,
|
||||
request: Request,
|
||||
fastapi_response: Response,
|
||||
):
|
||||
## CHECK FOR LITELLM API KEY IN THE QUERY PARAMS - ?..key=LITELLM_API_KEY
|
||||
api_key = request.query_params.get("key")
|
||||
|
||||
user_api_key_dict = await user_api_key_auth(
|
||||
request=request, api_key="Bearer {}".format(api_key)
|
||||
)
|
||||
|
||||
base_target_url = "https://generativelanguage.googleapis.com"
|
||||
encoded_endpoint = httpx.URL(endpoint).path
|
||||
|
||||
# Ensure endpoint starts with '/' for proper URL construction
|
||||
if not encoded_endpoint.startswith("/"):
|
||||
encoded_endpoint = "/" + encoded_endpoint
|
||||
|
||||
# Construct the full target URL using httpx
|
||||
base_url = httpx.URL(base_target_url)
|
||||
updated_url = base_url.copy_with(path=encoded_endpoint)
|
||||
|
||||
# Add or update query parameters
|
||||
gemini_api_key = litellm.utils.get_secret(secret_name="GEMINI_API_KEY")
|
||||
# Merge query parameters, giving precedence to those in updated_url
|
||||
merged_params = dict(request.query_params)
|
||||
merged_params.update({"key": gemini_api_key})
|
||||
|
||||
## check for streaming
|
||||
is_streaming_request = False
|
||||
if "stream" in str(updated_url):
|
||||
is_streaming_request = True
|
||||
|
||||
## CREATE PASS-THROUGH
|
||||
endpoint_func = create_pass_through_route(
|
||||
endpoint=endpoint,
|
||||
target=str(updated_url),
|
||||
) # dynamically construct pass-through endpoint based on incoming path
|
||||
received_value = await endpoint_func(
|
||||
request,
|
||||
fastapi_response,
|
||||
user_api_key_dict,
|
||||
query_params=merged_params,
|
||||
stream=is_streaming_request,
|
||||
)
|
||||
|
||||
return received_value
|
||||
|
|
|
@ -1166,3 +1166,52 @@ async def test_add_callback_via_key_litellm_pre_call_utils(prisma_client):
|
|||
assert new_data["success_callback"] == ["langfuse"]
|
||||
assert "langfuse_public_key" in new_data
|
||||
assert "langfuse_secret_key" in new_data
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_gemini_pass_through_endpoint():
|
||||
from starlette.datastructures import URL
|
||||
|
||||
from litellm.proxy.vertex_ai_endpoints.google_ai_studio_endpoints import (
|
||||
Request,
|
||||
Response,
|
||||
gemini_proxy_route,
|
||||
)
|
||||
|
||||
body = b"""
|
||||
{
|
||||
"contents": [{
|
||||
"parts":[{
|
||||
"text": "The quick brown fox jumps over the lazy dog."
|
||||
}]
|
||||
}]
|
||||
}
|
||||
"""
|
||||
|
||||
# Construct the scope dictionary
|
||||
scope = {
|
||||
"type": "http",
|
||||
"method": "POST",
|
||||
"path": "/gemini/v1beta/models/gemini-1.5-flash:countTokens",
|
||||
"query_string": b"key=sk-1234",
|
||||
"headers": [
|
||||
(b"content-type", b"application/json"),
|
||||
],
|
||||
}
|
||||
|
||||
# Create a new Request object
|
||||
async def async_receive():
|
||||
return {"type": "http.request", "body": body, "more_body": False}
|
||||
|
||||
request = Request(
|
||||
scope=scope,
|
||||
receive=async_receive,
|
||||
)
|
||||
|
||||
resp = await gemini_proxy_route(
|
||||
endpoint="v1beta/models/gemini-1.5-flash:countTokens?key=sk-1234",
|
||||
request=request,
|
||||
fastapi_response=Response(),
|
||||
)
|
||||
|
||||
print(resp.body)
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue